THE ROLE OF INFORMATION IN THE SELECTION
PROCESS OF A PRIMARY CARE PHYSICIAN
DISSERTATION
Presented to the Graduate Council of the
University of North Texas in Partial
Fulfillment of the Requirements
For the Degree of
DOCTOR OF PHILOSOPHY
By
E. Sonny Butler, B.S., M.S.
Denton, Texas
December, 1993
0^ Butler, E. Sonny, The Role of Information in the
Selection Process of a Primary Care Physician. Doctor of
Philosophy (Information Science), December, 1993, 17 tables,
3 illustrations, 5 appendices, references, 301 titles.
The purpose of this study was to determine if there are
critical information factors considered by consumers in the
selection of primary care physicians (POP); to identify what
those factors are, and to determine the significance of each
factor and combinations of the factors in the selection
process.
Data for this study was collected from patients at six
(6) selected clinics by requesting that they complete a
survey while waiting to be seen by their physician. Three
hundred (300) patients provided usable information.
Additional data were gathered through fifty-eight (58)
follow-up telephone interviews with patients who indicted
they would be willing to be interviewed.
Analysis of the data reveals that the patients
responding felt ten factors were important. The ten factors,
in order of importance were: (1) communications, (2)
insurance, (3) technology, (4) perceptuals, (5)
environmental, (6) physician reputation, (7) self-efficacy,
(8) economic, (9) opportunity, (10) physician socio-
demographic.
The more significant findings are: patient's who
evidenced interest in the physician's reputation had less
formal education; lack of knowledge concerning medicine was
not a significant factor in selecting a PCP; insurance
factors were more important than other economic factors;
people with insurance are not concerned with factors that
tend to increase health care costs; gender influences the
way one chooses a PCP; females are more concerned with
selection of a PCP than are males; ethnicity was significant
in some factors, and the more effective the communications
between the physician and patient the more frequently the
patient visited the physician.
The findings suggest that although consumers are
concerned and interested in who they select as a PCP, they
do not know where and how to check and validate information
concerning their primary care physician.
THE ROLE OF INFORMATION IN THE SELECTION
PROCESS OF A PRIMARY CARE PHYSICIAN
DISSERTATION
Presented to the Graduate Council of the
University of North Texas in Partial
Fulfillment of the Requirements
For the Degree of
DOCTOR OF PHILOSOPHY
By
E. Sonny Butler, B.S., M.S.
Denton, Texas
December, 1993
ACKNOWLEDGEMENTS
It is with a great deal of humility and gratitude that
I express my appreciation to the following people. First to
Dr. Paul S. Fisher, who actually afforded me the opportunity
to complete this degree. His assistance and belief in me are
gratefully acknowledged.
Dr. Ana D. Cleveland, my major professor, has been
outstanding. She has always been willing to take time from
her busy schedule to advise and assist. Without her and her
sense of humor, this research could not have been
successfully completed.
Dr. Raymond von Dran, who actually led me in the
direction of the subject for this dissertation, thanks.
Throughout many discussions and walks around campus his
insightful suggestions and listening are very much
appreciated. Dr. Donald B. Cleveland is also thanked for his
comments and guidance, both indirectly and directly in the
preparation of this dissertation. Thanks also to Dr. Jose R.
Toledo, who was willing to use some of his valuable time to
serve on my committee.
Last, but by no means least, I would like to thank my
wife, Sondra and my two daughters Lindy and Tracy for their
encouragement and patience. I am deeply grateful.
i n
TABLE OF CONTENTS
Page
ACKNOWLEDGEMENT iii
LIST OF TABLES vi
LIST OF ILLUSTRATIONS viii
Chapter
I. INTRODUCTION 1
Background of the Study-Statement of the Problem Significance of the Study-Definition of Terms Medical Cost Escalation Consumer Options Alternative Health Care Providers Primary Care Physician Choices Role of Information Hypotheses
II. REVIEW OF THE LITERATURE 57
Medical Licensing Information Search and Choice Physician Selection Behavior and Roles Health Maintenance Organizations Hospital Choice Marketing of Health Care Services Decision Making Models Summary
III. METHODOLOGY 96
The Search Decision Process Model Description of the Population Data Collection Procedures Description of the Survey Instrument Description of the Variables Data Analysis Methodology-Limitations of the Study
IV
IV. DATA ANALYSIS 113
Respondent Characteristics Factors and Components Ranked by Mean Factors by Demographics Demographics by Factor Related Non-Demographics Factors Stepwise Regression Significance of the Findings Supplemental Questionnaire Responses
V. CONCLUSION 146
Summary of Findings Health Care Reform Future Research Needs
APPENDICES 167
A. Survey Instrument
1. Cover Letter 2. Written Questionnaire
3. Telephone Survey Questionnaire
B. SPSS Listings
1. Factor Analysis Listing 2. ANOVA Listing 3. MANOVA Listing 4. Regression Listing
C. Tables
1. List of Factors
2. Demographics from Census
D. Graphical Presentation of Data
1. Clinic Information 2. Demographics
v
E. Graphical Presentation of Data by Factor
1. Physician Reputation 2. Physician Socio-Demographic 3. Economic 4. Environmental 5. Perceptuals 6. Self-Efficacy 7. Insurance 8. Communication 9. Technology 10.Opportunity
REFERENCES 399
VI
LIST OF TABLES
Table Page
1-1. Students' Selection of Primary Care Residencies. 12 in the National Residency Matching Program.
1-2. Median Net Income of U.S. Physicians (1991). . . 14
1-3. Cost Escalation in National Health Care, 1980,. . 16 Projected through 2000.
1-4. Projected Annual Growth in Medicare Expenditures 17 1993 to 1997.
1-5. Key Components of the Health Belief Model, 1989. 35
3-1. Clinic Staffing and Average No. of Patients/Day. 105
4-1. Number and Percent of Respondents by Data. . . . 115 Collection Site.
4-2. Age of Respondents 115
4-3. Gender and Ethnic Background of Respondents. . . 116
4-4. Marital Status of Respondents 117
4-5. Educational Background of Respondents 118
4-6. Yearly Household Income of Respondents 119
4-7. Occupation by Number and Percent 119
4-8. Place of Residence of Respondents 120
4-9. Length of Residence 120
4-10. Significance by Demographics and Factors. . . . 123
4-11. Correlation Values 123
VI1
LIST OF ILLUSTRATIONS
Figure Page
1. Search Decision Process (SDP) Model 97
2. SDP Model With Survey Relationships 98
3. SDP Model Relationships 100
vixi
CHAPTER I
INTRODUCTION
Background of the Study
The purpose of this study is to analyze the role
information plays during the selection process of a health
care provider (primary care physician). The study surveys
consumers regarding their choices of primary care physicians
and uses the results to validate the search decision process
(SDP) model.
Compared to other social science disciplines, the
scientific study of consumer behavior in the selection of
services is in its nascent stage of development. Many
research studies (Punj & Staelin, 1970; Beatty & Smith,
1987; Gensch & Javalgi, 1987) have analyzed consumer
behavior in the selection of specific products. However, few
studies have focused on the factors influencing the purchase
of services. Moloney and Paul (1991) mention that, according
to Business Week, the buyer's pursuit of better services is
driving the "Decade of the Customer," the 1990s. With the
proliferation of alternative health care providers,
understanding how consumers use information achieves greater
importance (Stewart, Hickson, Pechmann, Koslow, & Altemeier,
1992) .
2
With the avowed goal of overhauling the $800 billion
health care industry, Hilary Rodham Clinton, Ira Magaziner,
and the Health Care Task Force (Zagorin, 1993) are
suggesting that the public become more aware of their
choices in health care providers and how and why a consumer
chooses a certain provider. According to Time reporter Adam
Zagorin in the April 19, 1993, issue, the proposal that will
come from the White House study "emphasizes the ability of
citizens to choose their own doctors." (p. 36)
Statement of the Problem
There is a paucity of information about the various
factors that influence the selection of primary care
physicians. Also, the relative significance of these factors
is not known, making it difficult to properly address ways
to improve the information flow to patients when they select
a primary care physician.
Significance of the Study
The cost of health care to society today is
approximately 14 percent of the gross domestic product (GDP)
of the United States. This translates to billions of dollars
annually and continues to grow by 10 to 15 percent per year.
One major issue and possibly the biggest challenge which
must be solved is how health care is to be delivered in the
future. An almost ubiquitous theme that is discussed
concerning the delivery of health care is the ability of
consumers to choose their own health care provider. This
3
study addresses this critical issue and discusses the most
common factors consumers consider when making the choice of
a primary care provider.
Consumer behavior is by definition chaotic. Imagine
the influence of the fluttering of a butterfly's wing
against nature's background. This seemingly benign creature
could, with a flap of its wings, begin a chain of reactions
that would lead to violent storms. Tiny fluctuations in
input can very rapidly become major differences in output.
In weather, this phenomenon is known as the Butterfly Effect
(Gleick, 1987). The Butterfly Effect is the notion that "a
butterfly stirring the air today in Peking can transform
storm systems next month in New York" (p. 8, Gleick, 1987) .
Weather is a complex natural happening; and although
meteorologists attempt to predict it, ultimately, they
cannot, beyond a short cycle, because of the infinite number
of variables that have an influence on the weather.
The weather is a chaotic system. A chaotic system is
one that has "sensitive dependence on initial conditions"
(p. 8, Gleick, 1987). A chaotic system describes a system
where any alteration can have a dramatic effect. In chaos,
everything depends upon the initial starting point. If
things get changed, even slightly, something which is
totally different results.
Consumer behavior is also characteristic of a
dynamical system and the role of the feedback loop. This is
4
not the feedback arrow that one sees everywhere in
evaluation and knowledge-transfer diagrams. That is the
arrow which systematically links one problem-solving stage
of activity to another in a rational progression that
implies a linear progression upward into improved
functioning. The feedback loop in dynamical systems has a
much more frequent iteration, one that leads to individual
and organizational performance that only in certain
conditions is predictable. Very subtle, minor variation in a
defining parameter or initial condition can lead to periods
of extraordinary turbulence, a splitting of performance into
new patterns, sudden collapse, or extraordinary growth. The
common sense description of this process is that the results
of what has just been done directly and immediately affects
what will be done, and the cumulative iterative chain of
events has a causal force that exceeds the importance of the
particular, individual feedback event (Kiresuk, 1993).
Much the same kind of phenomena exists in the
selection of a primary care provider. The set of skills,
beliefs, and knowledge one possesses will significantly
impact the future course of events for the patients, from
teatment methodologies to hospital stays to outcomes.
Definition of Terms
Family care is health care for all members of a
family. Family care practice is the practice of medicine
providing health care for families.
5
In the 197 0s primary care was defined as care with a
longitudinal relationship between the patient and the
physician which provides first contact care and entry into
the health care system for the patient (Kuperberg, 1982).
Any access point into the health care system could be
considered primary care, so there is debate regarding what
is primary care. The American Hospital Association's (AHA)
definition of primary care is "basic ambulatory health
services that provide point of entry to the health care
system." (p. 24, Koska, 1990)
Physicians in family practice, internal medicine,
pediatrics, gynecologists, or dentists, pharmacists,
physician assistants or nurse practitioners generally
administer primary care (Koska, 1990). Robert Graham,
president of the American Academy of Family Physicians, does
not consider primary care a useful term. He feels that most
of what people call primary care is office-based, general
medical practice in the specialties of family medicine,
internal medicine, and pediatrics.
Spokespersons for the Health Care Policy and Research
Office in Silver Spring, Maryland, point out that some
primary care services, like pap smears and screening for
hypertension, are preventive health care. Overlap between
primary care and psychiatric care also exists when mental
health screening is done. Others have defined primary care
as ongoing care based on a continuous relationship with a
6
provider who is concerned with the patient's psycho-social
as well as physical well-being (Koska, 1990) .
For this study, a primary care provider or physician
is defined as a physician or provider who provides
longitudinal care and who knows the whole patient and is
concerned with preventive care as well as health/medical
care.
Medical care refers to that care which is primarily
geared to the cure of sick patients versus preventive care
which focuses on the prevention of disease in healthy
clients (Bloch, 1984). Preventive care also includes the
perception of health maintenance possibly using alternative
or complementary care providers in addition to or instead of
the primary care physician.
Alternative health care providers are defined for this
study as one or more health practitioners who may or may not
be linked together in an organization to provide either
medical care or preventive health care to the public. These
providers are usually paid primarily through insurance
plans, either publicly funded, employer funded, or
individually funded.
Complementary care providers are defined as those
health care providers that complement services recognized as
health care services. These may include nurse practitioners,
chiropractors, acupuncturors, practitioners of homeopathy,
etc. The American Medical Association (AMA) labels
7
complementary care providers as practitioners of
unconventional, alternative, or unorthodox therapies or
medicine (Eisenberg, Kessler, Foster, Norlock, Calkins, &
Delbanco, 1993). Several studies since 1982 suggest that the
use of complementary medicine is widespread (Eisenberg,
Kessler, Foster, Norlock, Calkins, & Delbanco, 1993). In
these studies, the surveyors defined medical doctors as a
"medical doctor (M.D.) or an osteopath (D.O.), not a
chiropractor or other nonmedical doctor." (Eisenberg,
Kessler, Foster, Norlock, Calkins, & Delbanco, 1993, p.
247) . In 1990, the estimated number of ambulatory visits to
providers of complementary care providers was 425 million.
This number exceeds the estimated 388 million visits in 1990
to all primary care physicians combined (Eisenberg,Kessler,
Foster, Norlock, Calkins, & Delbanco, 1993) .
Another term economic credentialing is new to the
healthcare literature and has historically been related to
exclusive contracts that are executed with hospital based
physicians. Economic factors have rarely been utilized in
the credentialing process for physicians. The current
process relies extensively on the use of clinical data,
professional competency and professional conduct. There has
been little written on the criterion to be established and
utilized in an economic credentialing process. Healthcare
providers have been concerned with structuring fair hearings
and due process into their medical staff by-laws, but new
8
efforts to contain costs will force managed care networks to
look closely at efficient and effective use of resources in
the treatment of patients. New forms of active economic
credentialing will entail a close examination of under and
over utilization of healthcare resources (West, 1993).
Scheduled for October 1993, President Clinton's Health
Care Task Force will be making recommendations for
restructuring the system of health care for the United
States. Following are the definitions of some of the terms
with which the American consumer, physicians, health care
providers, and others are becoming familiar:
Managed competition - First proposed in 1978 as a
possible cost reducing health care system, managed
competition is a mixture of free-market forces and
government regulation. To increase their market impact,
employers and other consumers form large purchasing
networks. Insurance companies, HMOs, or other health plans
then bid for their business. The bidders offer attractive
core-benefits packages. In theory, the tremendous buying
power of the networks creates competition among health plans
and ensures quality and low prices ("Words to Live By,"
1993). In most managed competition proposals, competition is
regulated by one or more government agencies who have many
important responsibilities: certifying specific managed
care plans, establishing the minimum slate of services to be
offered, ensuring that consumers have access to these plans,
9
and overseeing the quality of care in various managed care
plans. This system of regulation is a radical departure from
our traditional medical system, where health care providers
are relatively unaccountable for the care they provide
(Iglehart, 1992).
Managed care - Managed care is a general term for
organizing networks of doctors and hospitals in order to
give people available, quality, cost-effective health care.
HMOs and PPOs are examples of managed care.
Health Insurance Purchasing Cooperative (HIPCs)-These
are regional consumer groups that would shop for the
highest-quality care at the lowest price on behalf of a
large number of people, including employees of small
businesses.
Fee for service - Fee for service is when patients pay
doctors and hospitals for each service rendered.
All-payer system - Uniform prices are placed on
medical services, regardless of who is paying.
Single-payer system - This is a centralized health-
care payment system with the government paying all the
bills, similar to Canada's health care plan. In Canada,
people go to the doctors and hospitals of their choice and
the government is billed according to a standard fee
schedule.
10
Capitation - This system is a managed-care plan which
pays a doctor or hospital a fixed amount to care for a
patient over a given period of time.
Point-of-service plan - Point-of-service (POS)
designates a plan in managed care but differs from regular
HMOs by allowing patients who decide to go outside the plan
to get 60 to 70 percent of their expenses reimbursed ("Words
to Live By," 1993) .
In the search for information, the consumer will first
use their current knowledge or internal search methodology
and then use external search techniques. For this study,
these terms are defined as follows:
• Internal search refers to the acquisition of
information that is available in memory
(Bettman, 1979) .
• External search effort refers to information
seeking activity by the consumer from different
sources (Elliott, 1991).
The Historical Perspective
The shortage of primary care physicians
The use of physicians and the types of physicians have
changed over the years. Family care and family practice
evolved as a specialty in the 1970s to supplant and augment
the definition for the general practitioner. The general
practitioner worked long hours, received less renumeration,
and held less status than specialty physicians (Lewy, 1977).
11
The Flexner report of 1910 impacted medical schools and
caused a profound change from the European model of medical
schools to strong research based academic medical centers.
Full time salaried physicians with special scientific and
technical skills replaced the largely non-specific
generalists. Because of this replacement, general medicine
practitioners had less and less contact with medical
students. Aspiring doctors looked to medical and surgical
subspecialists as models. During World War II, the armed
forces rewarded medical specialists with higher rank and pay
than those given to general physicians.
Because medical training emphasized medical students'
experience with hospitalized patients, medical skills which
could enable the medical student to recognize and manage
either life-threatening conditions or the less common
diseases and conditions became the skills basic to medical
education (Rogers, 1977). In addition, after World War II
the availability of large amounts of government and private
research funds helped to create the "scientist-physician"
(Lewy,1977).
From 1931, when the percentage of all private practice
physicians in general practice reached 84 percent, to 1965
when the corresponding percentage had dropped to 45 percent,
the change in specialty distribution of physicians has been
dramatic (Huntington, Sweeney, & Graham, 1992). In 1990,
family physicians and general practitioners comprised 11.4
12
percent of physicians (7.7 percent, family physicians, and
3.7 percent, general practitioners) (Huntington, Sweeney, &
Graham, 1992)(See Appendix Dl-1).
The indication of this continuing reduction in the
supply of generalists physicians is shown in the Table 1-1.
Field chosen in NRMP 1986 1992
US Foreign Tot US Foreign Tot
Internal medicine Categorical 3884 1015 4899 2669 1405 4074 Primary care 149 23 172 244 77 321 Medicine/Pediatrics 110 11 121 166 24 190 Total 4143 1049 5192 3079 1506 4585 Family Practice 1680 280 1960 1398 280 1678 Pediatrics 1366 357 1723 1325 370 1695 Ultimate practice General internal med. 1475 360 2865 761 315 1076 General pediatrics 956 250 1206 398 111 509 Total primary care 4111 890 4782 2557 706 3263
Table 1-1. Students' Selection of Primary Care Residencies in the National Residency Matching Program (NRMP), 1986 and 1992 .
(Information in Table 1 reprinted from p. 657, Levinsky, 1993)
At the close of World War II, the government invested
unprecedented sums of money in biomedical research planting
the roots of the current problem of specialty mis-
distribution. The federal government became the dominant
source of funds for this research through the National
Institutes of Health (NIH). NIH channelled their funds
principally to the nation's medical schools and
universities. In 1940, the federal government's share of
funds spent on biomedical research and development amounted
13
to about $3 million (Huntington, Sweeney, Graham, 1992). By
1991 that share had grown to $8.5 billion. Of this total,
the academic medical centers received $6.7 billion. These
free flowing funds fueled the rise in subspecialization
(Huntington, Sweeney, & Graham, 1992).
Rapid advances in biomedical knowledge and application
and the increased demand for lower cost labor furnished to
the large medical centers by interns and residents also
influenced the direction of medical education (Huntington,
Sweeney, & Graham, 1992). According to critics, graduate
medical education (GME) in academic medical centers inhibit
the dispersion of primary care physicians to patient
populations who need them because of the following:
• teaching hospitals emphasize research.
• teaching hospitals emphasize the delivery of
tertiary care and undervalue integration of
care.
• teaching hospitals replicate themselves and
overrun the system with subspecialists (Anderson,
1992).
Specialty care represents all of the strengths of the
U.S. health care system with its use of the latest
diagnostic and therapeutic techniques, all extremely
expensive (Schroeder and Gandy, 1993). Two factors which
seem to discourage medical students from choosing general
practice are:
14
the large and growing disparity in income between
generalists and specialists. For example,
the median net income of a family practice
physician is $108,000, compared with almost
$200,000 for a thoracic surgeon, one of the
lowest paid surgery specialties. The median
income for neurosurgeons, one of the highest
paid specialties was almost $400,000 in 1991.
A more complete comparison is given in Table
1-2. Appendix Dl-2 presents this trend in
specialists along with median income of U.S.
physicians for 1991.
the strongly pro-specialist environment of our
medical education system (Schroeder & Gandy,
1993) .
Neurosurgery $388, 300 Urology $223, 050 Cardiovascular surg $363, 850 Dermatology $214, 300 Gastroenterology $300, 000 Pathology $206, 250 Orthopedic surg $294, 500 Neurology $198, 550 Cardiology $283, 589 General surg $197, 050 Radiology/Diagnostics $272, 750 Thoracic surg $188, 750 Ophthalmology $258, 850 Psychiatry $144, 600 Otolarynogology $247, 700 Internal medicine $143, 250 Anethesiology $244, 800 Pediatrics $131, 100 Plastic Surg $243, 100 Family practice $108, 900 Al1ergy/Immuno1ogy $224, 964 General practice $ 90, 910 Ob/Gyn $224, 750
Table 1-2. Median Net Income of U.S. Physicians (1991)
Sources: Texas State Board of Medical Examiners, Society of Professional Business Consultants in Portland, Ore.
15
Norman Levinsky summarized these factors as the "misdirected
education of students and residents and ... problems with
practice conditions and economic factors" (p. 657, 1993).
Primary care physicians have become gatekeepers in
American health care. As "gatekeepers", primary care
physicians not only provide medical care and referrals to
specialists, but also serve as important sources of
education and information as well as guides in consumer
involvement in health decisions and prevention (Bloch,
1984). With this gatekeeping role gaining more importance in
the American health care reform scheme, primary care
physicians recognize that their role is a function of their
professional training and as such, gatekeeping becomes the
core function of primary patient care and becomes the
process of matching patients' needs with the judicious use
of health care services, including the protection of
patients from possible adverse effects of unnecessary care
(Franks, Clancy, & Nutting, 1992).
Medical Cost Escalation
Congress inaugurated Medicare on July 1, 1966, to
provide a number of health care benefits to those over 65
who were covered by the Social Security System. In 1972
amendments to Title XVIII of the Social Security Act
extended benefits to disabled, to those elderly willing to
pay premiums, and to those with chronic renal disease.
Medicare has two complementary but distinct parts:
16
• hospital insurance and
• supplemental medical insurance (Renn, 1987).
Also in 1966 Congress started another government
health care financing program, Medicaid, when it enacted
Title XIX of the Social Security Act. Medicaid is a joint
federal-state program to benefit the poor. Each state
administers its own program including the definition of
eligibility requirements and covered services. Actually
there are 50 different Medicaid programs. Therefore, while
estimates place the percentage of coverage of California
poor at 95%, only 25% of the poor in Texas are recipients of
Medicaid benefits. Medicaid is financed through general tax
revenues from states and from federal income taxes (Renn,
1987) .
Both Medicare and Medicaid pay providers on a cost-
based, fee-for-service basis. After the enactment of these
two acts in 1966, the volume of health care services
reimbursed on a cost or cost-plus basis doubled. Table 1-3
shows the national health care spending trends from 1980
through projections for 1995 and 2000 (Tokarski, 1990).
1980 1985 1987 1995 2000
National total in billions
$248.1 $419.0 $500 .3 $999.1 $1,529.3
Percent of Gross national product
9.1 10 .4 11.1 13 .4
o
LO
t—1
Per capita $1,055 $1,696 $1,987 $3,739 $5,551
17
Table 1-3. Cost escalation in National Health Care, 1980, projected through 2000.
Medicare is the largest single payer in the U.S.
medical care system. Medicare's growth makes it the
government's third largest and fastest-growing program.
Medicare purchased about 20 percent of all personal health
services in 1991. These expenditures are expected to more
than double by the end of the decade as reflected in Table
1-4 (Iglehart, 1992).
1993 1994 1995 1996 1997
Hosp. Ins. Expen. (billions) % Growth
$ 86.7 $ 96.2 10.9
$106.2 10 .4
$117 .8 10.9
$129.5 10.0
Supp. Medical Ins. (Part B) Expen. (billions) Growth Rate (%)
$ 59.4 $ 76.6 13 .6
$ 76.6 13 .6
$ 87.1 13 .7
$ 98.6 13 .2
Total Medicare Outlay Expen. (billions) Growth Rate (%)
$146.1 $163.6 12.0
$182 .8 11.7
$204.9 12 .1
$228.1 11.4
Table 1-4. Projected Annual Growth in Medicare Expenditures, 1993 to 1997.
Data are from the Health Care Financing Administration (Iglehart, 1992).
Current Health Care Reform
In 1992 Health Management Quarterly published an
article by Jerom Brazda which says that "most of the reason
for the failur of health care reform legislation in past
several decades has been the well-organized and well-
financed opposition of associations representing provider
groups that see threats to their independence in much of the
18
legislation." (p. 9) He is referring to the AMA, the AHA,
the Health Insurance Association of America, and various
other provider organizations who maintain offices in
Washington, D.C. (Brazda,1992).
Many consumers are now actively involved in choosing
their health care services by selecting a health plan or
hospital. One of the most quoted desires from consumers is
their requests to be able to select their primary care
physicians (Moloney & Paul, 1991) . This study explores this
area in depth.
Consumer Options
In the study of the decision process, knowledge of
choice criterion and an understanding of consumer choice
behavior is needed. Choice for the consumer assumes
importance because of the value consumers place on services
selected by themselves (Mechanic, 1991).
The Health Care Consumer
In the United States, the health care consumer falls
into one of the following four groups:
• employees and individuals with some form of health
insurance
• those whose care is subsidized by the state
(Medicaid recipients)
• those whose care is partially subsidized by the
federal government (elderly and disabled)
• those without health insurance (Klinkman, 1991).
19
Health Care As A Service
Inherent differences exist between tangible products
and intangible services (Barnes, 1985) . These differences
include the following:
• services are often less standardized than
goods (Berry, 1984). The producer of a
service has a difficult time producing
consistent performance and quality (Zeithaml,
1984).
• services are perishable and are consumed at
the same time they are purchased (Berry,
1984).
• services require the presence of the consumer;
products do not. Consumer-provider
interaction is mandatory in service
'consumption' (Barnes, 1985).
• health services are provided directly to the
consumer and are simultaneously produced and
consumed in one's presence (Barnes, 1985).
The consumer participates in some way in the
production of a service (Zeithaml, 1984) .
• service purchase includes expectations beyond the
service itself. The consumer expects to
obtain certain benefits beyond the best
technical quality from the product being
purchased. Among these benefits are the
20
consumer's desire or concern for physical
comfort, social and psychological support,
and considerably greater ease in purchasing
the primary health product (Flexner,
McLaughlin, & Littlefield, 1977). Consumers
rely on post purchase evaluation as essential
to assess their experience qualities with a
service (Zeithaml, 1984).
• usually more product alternatives are displayed
and are available in close proximity than
there are service alternatives (Barnes,
1985). The consumer may find it difficult to
obtain adequate prepurchase information about
services thus limiting the alternatives from
which to choose (Zeithaml, 1984).
• services are perceived to be riskier than goods.
The consumer possesses this perceived risk
because of the following:
• lack of knowledge of service attributes prior
to purchase
• non standardization of services
• lack of guarantees or warranties with services
• deficiency in consumer expertise or knowledge
about service
• lack of tangibility (Murray, 1991).
Decisions for Products and for Services
21
Because of these differences between tangible products
and intangible services, the processes of selection of
products and of services also differ. Barnes (1985) states
that the decision process for selecting and evaluating
service is distinct in order, content, and number of stages.
Prior evaluation of services is more difficult than for
goods or products. Personal sources or referrals are more
important than impersonal sources when consulted for
services rather than for goods (Murray, 1991) .
The role of the use of information, both external and
internal, and the choice decision process in the consumer
search for health care services differ from that of buying a
product.
Research studies on consumer decision making which use
demographics are often inconsistent and do not give
explanations. Because demographic research has not been the
best type of research on which to make policy decisions on
health care choices, there exists a need for behavioral
based models on health care decisions made by consumers
(Thompson & Rao, 1990).
This study used a Search Decision Process (SDP) Model
(Illustration 1). The model depicts the antecedents of
physician profile, environmental factors, economic factors,
socio-demographic factors, and self-efficacy plus the
perceptuals of satisfaction, results, quality, and benefits.
The heuristics (antecedents and perceptuals) acted upon the
22
decision process to influence the role of prior knowledge
and the attaining of more knowledge and information to
assist and intuitively persuade the consumer as the decision
i s made.
Characteristics of Health Services
Services are consumed but not possessed. The essence
of what is being purchased is a performance rendered by one
party for another (Berry, 1985). According to Bettman,
Johnson, and Payne (1991) the process itself is multifaceted
because:
• decisions may be difficult.
• often the alternatives are changing.
• a great deal of information exists.
• uncertainty as to service performance
exists.
• difficult value trade-offs occur.
Cartwright (1967), in an early study of the consumer
search process for a health care provider, revealed that
many consumers have the belief that they lack the competence
or knowledge to evaluate a physician's performance in terms
of the quality of medical care. Later studies (Kane, 1969;
Doyle & Ware, 1977) reported that consumers tend to evaluate
physicians on such aspects as personality, quality of
interaction, and "art-of-care," for which they believe they
can make accurate judgments (Stewart, Hickson, Pechmann,
Koslow, & Altemeier, 1989). With the proliferation of
23
changes in health care and the addition of alternatives for
health care provision, has the consumer become any more
knowledgeable or feel any more competent to make selections
for a health care provider?
Alternative Health Care Providers
The choice of a specific physician may not be possible
for many consumers. They have chosen one of the alternative
health care providers as follows:
• Health Maintenance Organization (HMO)
• Preferred Provider Organization (PPO)
• Health Center/Clinic
• Hospital/Emergency Room
• Complementary treatment providers
Health Maintenance Organizations (HMOs)
An HMO is a prepaid health-care plan under which
people enroll by paying a set annual fee. Consumers then
receive all their medical services through a group of
affiliated doctors and hospitals, often with no additional
co-payments or fees (Winslow, March 11, 1993). In 1973,
Congress enacted the Health Maintenance Organization Act
which enabled the federal government to establish a program
of financial assistance to promote federally qualified HMO
development. This act required all employers with 25 or more
employees to offer workers a chance to join a qualified HMO
if one existed within specified geographic boundaries
(Barrett, 1989) .
24
The history of HMOs can be traced to the 1920s. The
HMO features insurance for and delivery of health care
services within one organization. HMOs contract to provide
a stated, fairly comprehensive range of health care services
in return for fixed annual or monthly payment. They create
incentives to reduce demand for medical care services by
encouraging the use of less costly alternatives to
hospitalization and by emphasizing wellness and prevention
(Renn, 1987). By operating within a fixed budget, the HMO
has a financial incentive to provide early care and to
minimize use of expensive hospital facilities. Quality of
care has been found by some studies to be as good as that
offered at private hospitals and doctors' offices according
to the New England Journal of Medicine (Chase, 1985) .
In the last decade, the number of people using managed
care plans, also known as prepaid delivery systems or
alternative delivery systems, has skyrocketed. In 1980 in
the United States and Guam, 9.1 million people were enrolled
in HMOs. By 1990 the number had grown to 33.6 million
people, an increase of 376 percent. In June 1992 the total
number of people enrolled in HMOs in the United States
topped 37.2 million. Employees too have become enamored
with the managed care concept. More than 80 percent of
employers offer some type of managed care plan to their
employees (Iglehart, 1992).
25
HMOs are usually one of four types (Barrett, 1990).
These types are Independent Practice Associations (IPAs),
network HMOs, group HMOs, and staff HMOs.
Independent Practice Associations (IPA) made up 62% of
HMOs in 1987. Physician fees may be 10% to 15% below their
usual fees (Barrett, 1990). An IPA is a type of HMO that
contracts with individual physicians to provide services to
the HMOs enrollees. Doctors maintain their own private
practices and can contract with other HMOs or see regular
fee-for-service patients as well (Winslow, March 11, 1993).
Network HMOs contract with two or more independent
group practices to provide services to its members (Barrett,
1990) .
A group HMO contracts with a multi-specialty group
practice to provide health services to its members. A
capitation payment is made to the group for each HMO member
regardless of the number of visits made by that member
(Barrett, 1990).
A staff HMO consists of physicians employed directly
in a central office facility with administrative support.
Doctors receive salary and bonuses based on the HMOs
profits, costs, physician performance, and other factors
(Barrett, 1990) .
Preferred Provider Organizations (PPOs)
Another type of managed care plan is the preferred
provider organization. Preferred Provider Organizations
26
(PPOs) are the newest and fastest growing alternative to
traditional financing systems. Between 1983 and 1985 the
number of Americans enrolled in health insurance plans
offering PPO options tripled (Renn, 1987). A PPO is an
arrangement under which an insurance company or employer
negotiates discounted fees with networks of health-care
providers in return for guaranteeing a certain volume of
patients. Enrollees in a PPO can elect to receive treatment
outside the network but have to pay higher co-payments or
deductibles for it (Winslow, March 11, 1993). A generic PPO
is essentially a defined, limited, and sometimes organized,
set of providers that contract with employers or insurers to
provide a comprehensive set of health care services on a
fee-for-service basis, usually at a negotiated, discounted
rate. Seemingly this provides something for everyone (Renn,
1987). For consumers PPOs introduce a tradeoff between
freedom of choice and out-of-pocket payments. If the
provider of their choice is not a preferred provider, they
have to pay more (Allen, 1985).
The managed-care increase has just rearranged health
care costs. By 1990, 72 million people were enrolled in HMOs
or preferred provider organizations. Projections show that
as much as 80 percent of the insured population will be
enrolled in HMOs or PPOs by the early 1990s (Tokarski,
1990). With increased emphasis on cost containment,
providers within managed care networks will be evaluated
27
according to how they use facilities, acquire equipment and
technology, utilize specialized personnel, and consume
supplies and materials in the clinical treatment process.
Furthermore, adverse patient selection will have significant
financial repercussions on the economic stability of any
organization (West, 1993).
Medical Clinics and Hospital Emergency Rooms
Increased competition from alternative delivery
systems are causing the health care services to change in
order to compete. Proponents of walk-in clinics describe
them as a cost and time efficient alternative to private
physicians and hospital emergency rooms for routine medical
needs. Many people no longer think there is a difference
between private physicians and walk-in clinics. Further,
consumers are using hospital emergency rooms as sources for
nonurgent care (Gilbert, Lumpkin, & Dant, 1992).
Some health-care managers predict that within ten
years most health care services will be provided outside the
hospital and will include such as subacute, stepdown, and
recovery-care centers; medical malls; medical center inns
for outpatients and their families; and telephone and
electronic "house calls" promoting home care (McManis,
1990). Employers are working with providers to manage their
employees health care and outcomes by establishing employee
health goals, defining and documenting quality and providing
high-quality care with providers being compensated on the
28
basis of results (McManis, 1990). Stewart, Hickson,
Ratneshwar, Pechmann, and Altemeier mention in an 1985 study-
that a recent trend in the primary health care business is
the boom in walk-in or convenience clinics with well over a
thousand clinics operational and serving over 12 million
patients in 1983.
Complementary Treatment Providers
Perhaps the increase in the types of health care
providers that American consumers choose has been one of the
most startling changes in American health care. Although
exotic "New Age" thinking may have caused some Americans to
consult the use of crystals or bioenergetics therapists to
heal themselves, other Americans ask for help from
acupuncturists or shiatsu ("finger pressure") massagers both
of whose therapies have histories of over 1000 years
(Horowitz & Lafferty, 1991). A Time/Cable News Network (CNN)
poll found that 30% of people questioned had tried some form
of complementary medicine in 1990. Researchers reported in
the New England Journal of Medicine in 1993 that they could
estimate from their results that one in three Americans had
used complementary care providers in 1990 (Eisenberg,
Kessler, Foster, Norlock, Calkins, & Delbanco, 1993) . The
researchers found that 16 interventions could be called
representative of complementary care in the United States.
These included:
• relaxation techniques
29
• chiropractic
• massage
• imagery
4 spiritual healing
• commercial weight-loss programs
• lifestyle diets (e.g., macrobiotics)
• herbal medicine
• megavitamin therapy
• self-help groups
• energy healing
• biofeedback
• hypnosis
• homeopathy
• acupuncture
• folk remedies (Eisenberg, Kessler, Foster,
Norlock, Calkins, & Delbanco, 1993)
Claudia Wallis wrote an article for Time magazine in
which she grouped complementary care into four groups as
follows:
• Life-style
• macrobiotics - a dietary and health cultivation
which balances yin or passive energy and
yang or active energy
Ayurvedic medicine - a system of diet and
therapies based on a 4,000 year-old Indian
30
system of herbs and massage upon different
body types
• holistic medicine - a variation on conventional
medicine emphasizing life-style and
psychological factors - treating the whole
person
Botanical
• aromatherapy - inhalation or massage into skin
of essential plant and flower oils
• medicinal herbalism - promotion of health and
treatment of illness with plant-
derived potions
• homeopathy - treatment of disease with very
small doses of natural substances
that in larger amounts would cause
the same symptoms as the ailment
Manipulative/hands-on
• reflexology - the manipulation of areas on the
feet to affect the rest of the body
• rolfing - deep, sometimes painful massage to
realign the body
• shiatsu - Japanese therapeutic massage using
pressure points
• Alexander technique - training to improve poor
posture which alleviates pain
31
• chiropractic - manipulation of the spine to
relieve backache and other ailments
• acupressure - using fingers instead of needles
in a technique similar to acupuncture
• acupuncture - a 2,000-year-old Chinese method
of easing pain and maintaining health by
inserting fine needles at specific points that
relate to different parts of the body
Mind over matter
• color healing - illumination of colored light
on the body to alter its vibrations" or aura
• crystal healing - New Age therapy purporting to
derive healing energy from quartz and other
minerals
bioenergetics - exchange of energy between
patient and therapist
guided imagery - therapy in which patients are
encouraged to envision their own
immune systems battling disease
• hypnotherapy - making therapeutic suggestions
to patients who are in a semiconscious trance
to relieve pain or speed healing
biofeedback - use of machines to train people
to control such involuntary functions as jaw
tension, heart rate and circulation in the
hands (Wallis, 1993).
32
Many therapists pick up bits of different disciplines,
offering a combination of several different therapies
(Horowitz & Lafferty, 1991). Since funding for research is
provided primarily by drug companies, little research is
ongoing into the usefulness of complementary medicine. But
even when research finds no scientific basis for a
complementary therapy, it could effect improvement in
patients that use it because of their belief in its utility.
Because some physicians are beginning to see that care other
than conventional can help, these physicians are beginning
to look at the way that body, mind, and life-style interact
in holistic care (Horowitz & Lafferty, 1991).
The poll in Time found that 84% of those who had
consulted a complementary care provider would return to such
a provider for more help. Among those who have never
consulted a complementary care provider, they found that 62%
would consider seeking help from such a provider (Horowitz &
Lafferty, 1991). Major medical schools are introducing
programs in complementary medicine into their curriculums
(Gordon, 1993). Obviously, physicians are not the only
health care providers that Americans consult. Perhaps our
definition of primary care needs to be studied and redefined
to include alternative/complementary care providers.
Consumers are becoming more and more concerned with
preventive care. Because of this concern Americans have
altered their outlook with respect to health-related matters
33
(Bloch, 1984). This national health consciousness may be
driven by the aging of the baby-boomer generation in
addition to the amount of preventive health information
available in society today (Horowitz & Lafferty, 1991) . With
the buzz word of the '90s being "empowerment," more
consumers want as much information as possible about their
choices in health matters (Horowitz & Lafferty, 1991).
Conventional medicine has focused on crisis
intervention. Physicians have not been as successful in
informing the public how to stay healthy or how to contend
with chronic afflictions such as arthritis, osteoporosis,
lower-back pain, high blood pressure, coronary-artery
disease and ulcers (Horowitz & Lafferty, 1991) . The public
has not only aged but has become impatient with medical
miracles and dissatisfied with the existing health care
delivery and has lost some respect for physicians. These
factors have driven the development of the wellness movement
toward preventive care (Bloch, 1984) .
This increasing wellness orientation among American
consumers has implications for the health care industry.
With the health care system in America primarily positioned
to cure sick patients (medical care) rather than prevent
health problems in health clients (preventive care), one
needs to understand the consumer health beliefs (Bloch,
1984).
34
A group of social psychologists employed at the U.S.
Public Health Service constructed the Health Belief Model
(HBM) in the 1950s. These psychologists used the model to
understand why people failed to participate in programs to
prevent or to detect disease. Scientists later expanded this
model to apply to people's responses to symptoms and to
explain their behavior in response to diagnosed illness.
For the past thirty plus years, this model has influenced
psychosocial approaches to explaining health-related
behavior (Rosenstock, 1990). Simply, the Health Belief Model
explains that "individuals will take action to ward off, to
screen for, or to control ill-health conditions if they"
believe the following:
• that they are susceptible to the condition,
• that the condition has potentially serious
consequences,
• that there is a course of action that would be
beneficial in reducing either their susceptibility
to the condition or the severity of the
condition, and
• that the anticipated barriers or costs of taking
the course of action are less than its benefits
(Rosenstock, 1990).
35
The following table shows the key components of the
Health Belief Model of 1989 (p. 46, Rosenstock, 1990).
I. Threat A. Perceived susceptibility to an ill-health
condition (or acceptance of a diagnosis) B. Perceived seriousness of the condition
II. Outcome expectations A. Perceived benefits of specified action B. Perceived barriers to taking that action
III. Efficacy expectations: conviction about one's ability to carry out the recommended action (self-efficacy)
Table 1-5. Key Components of the Health Belief Model, 1989.
The scientists originally developed the Health Belief
Model to explain preventive health actions. The model may
also be used to explain compliance. Patient-physician
interaction may impact a patient's Health Belief Mode.
Patient satisfaction increases the likelihood of compliance
by a patient. A consumer whose satisfaction with physician
choice is positive helps that consumer's health by
increasing compliance with preventive health measures
(Becker & Maiman, 1980).
Primary Care Physician Choices
Behavior Choice Antecedents
In a 1989 study (Gallagher) of what influences North
Carolinians and their choices of doctors, 74% of the
respondents said that their doctors offices were less than a
20 minute drive from their homes. Fully 63% preferred seeing
their doctors before noontime. Proximity of the doctor's
office and time of day for appointments are just two factors
which comprise an environmental influence on the choice of a
36
doctor. Others include the ease of getting an appointment,
the courtesy, appearance, and hygiene of the office staff,
the appearance of cleanliness, and technology of the office
itself. Some considerations are not central to the decision-
making in influencing the choice of a provider by the
consumer, but these considerations such as convenience,
physical proximity to care, attractiveness of centralized
services, limited waiting time, perceived responsiveness of
nonprofessional personnel and attractiveness of premises of
the care provider occupy only secondary importance for the
preference for a provider at the margin (Mechanic, 1989).
Stewart, Hickson, Ratneshwar, Pechmann, and Altemeier
conducted a study of parents in Arkansas and their selection
of their pediatricians. In a study published in 1985 they
found that the most important factors, nearly equally
ranked, proved to be recommendation of a friend or neighbor,
personality of the provider, whether the provider explains
their illness in an understandable manner, and the
timelessness of getting an appointment. Of less importance
was recommendation of other family members, provider's
office hours, more than one physician in practice,
convenient location, age of provider, and whether the
provider recommends breast feeding. The study indicated the
following factors provided the most dissatisfaction with
their pediatrician:
• no interest by the doctor in child's behavior
37
• no concern shown for child
• no improvement in child's condition
• no competence shown by the doctor
Those using a general practitioner/family physician
were most often dissatisfied because of:
• distance to the office(clinic)
• convenience of another MD's location
• rudeness of staff
• lack of concern shown toward patient
(Stewart, Hickson, Ratneshwar, Pechmann, & Altemeier, 1985)
The variables that influence patients to feel
satisfaction/dissatisfaction with their physicians
include technical care and the conditions under which the
care is provided including the following:
• access/convenience of care,
• availability of resources,
• humaneness,
• finances, and
• quality of care.
Other variables include professional competence,
provider personal qualities, cost and convenience of care
(Koehler,Fottler, & Swan, 1992). Additionally, because
consumer/decision makers feel an increase in time
constraints they make efforts to simplify the
selection.(Bettman, Johnson, & Payne, 1991).
38
When one mentions the cost or price of medical care,
economic cost is meant. However, "cost" goes beyond "price"
to the consumer in that something of value is given up by
the consumer in exchange for health care services. Time and
opportunity are only two examples which may be more valuable
than money (Cooper, 1986). Others include effort, lifestyle,
and psyche. When effort leads to fatigue, the cost is that
fatigue (Fine, 1981). Thus, resources beyond money are given
up by consumers in the purchase of services. Most consumers
depend on insurance or on themselves to pay for health care
services.
For the consumer the description of a good physician
should include the following properties of being able to:
• show intelligence and medical/technical knowledge
• have a sympathetic and interested manner
• organize an office to run efficiently
• take a detail history of a patient including time
for the patient to discuss problems
• explain clearly diagnosis and treatment
• admit a lack of knowledge or diagnosis
• know self-limitations
• refer to specialists when indicated
• be conservative in recommending surgery
• not abandon a patient once treatment has begun
• consult with patient by telephone when needed
39
• provide a competent backup physician when
unavailable
• charge reasonable fees and discuss these fees with
patients
• possess staff privileges of an accredited hospital
• keep up-to-date by reading journals and attending
post-graduate and other educational meetings
(Barrett, 1989).
Other requirements which could be considered part of a
good physician profile would include the following:
• willingness to talk about specific illness with
patient
• access to a hospital desired by patient
• short lead time for appointment making
• reasonably adequate personality or appearance
• experience
• good office location
• weekend and evening office hours (Barrett, 1989).
Daley, Gertman, and Delbanco (1988) recommend
developing a desirable outline for a primary care physician
profile which could be a basis of information about primary
care physicians. This profile would include the following:
• Institute of Medicine criteria score for
accessibility, comprehensiveness, coordination,
continuity, and accountability
• process tracer score
40
• outcome tracer score
• physician credentials
• education and teaching profile
• patient satisfaction score
• psychosocial and bio-ethical profile (Daley,
Gertman, & Delbanco, 1988) .
Role of Consequences in Selection
Satisfaction and outcomes/results are consequences in
choosing a primary care physician. The consumer of a service
concurrently evaluates the available characteristics of the
service and the level of satisfaction achieved (Barnes,
1985, p.61). Consumer satisfaction may be connected to who
makes the choice, self or some other (Woodside, Sertich, &
Chakalas, 1987) . Marquis, Davie, and Ware (1985) found that
patient dissatisfaction can cause provider change (Marquis,
Davie, & Ware, 1985) . The importance of the task (choice)
(it can actually become a life or death choice) can cause
the consumer to expend a great amount of effort in making
the decision (Bettman, Johnson, & Payne, 1991).
Patient satisfaction is one ultimate outcome of the
delivery of personal medical care services (Marquis, Davies,
& Ware, 1985). Consumers desire satisfaction. Because of
this desire, client satisfaction has become a measure for
the quality assessment. Fincham & Wertheimer (1986) found
that patient-physician continuity, self assessed health,
appropriate physician-patient communication, and a positive
41
view of preventive health activities all combined to add to
the satisfaction consumers felt for their HMOs. According
to Dolinsky and Caputo (1990) consumer satisfaction is
probably the most important dimension of HMO performance.
John and Miaoulis (1992) suggest that one of the most
pervasive changes in American society over the past thirty
years has been the shift from medical care or cure-oriented
health care to preventive health care.
Quality of care is important to the consumer of health
care. Froebe, Balitsis, Beckman, Dolphin, Hayes, & Morrissey
(1982) found that the most important factor influencing
choice of a nursing home was quality of care with other
considerations being distance, cost, and appearance. These
researchers recommended that studies should determine what
ingredients make up quality of care. The lack of
standardization or quality control increases the perceived
risk of the service decision (Barnes, 1985). The consumer
cannot actually evaluate the quality of a health service
prior to actual consumption (Barnes, 1985).
Flexner, McLauglin, & Littlefield (1977) found in a
study of consumers and potential consumers of an abortion
service that the following factors in their choices of
services were ranked in order of importance with medical
care ranking first:
• technical medical proficiency
• convenience of location and timely appointment
42
• cleanliness and attractiveness of office
• reputation of the service
• follow-up for health future
• referrals from a physician or friend
A full description of the product in health care
services must include what the consumer expects to obtain
beyond technical expertise. The consumer's desire for
physical comfort, social and psychological support are just
some benefits the consumer hopes to gain (Flexner,
McLaughlin, & Littlefield, (1977). Gilbert, Lumpkin, and
Dant concluded in 1992 that physicians should not continue
to rely on their good reputations to help them maintain
their market shares but should spend more time with their
patients because consumers perceive that the amount of time
spent with them influenced their quality of care.
Role of Information
The elements that make up the choice decision task
influences the difficulty of the consumer's decision. The
consumer's decision becomes more difficult if the
information used in making the decision is not presented to
the consumer in a usable and processable format (Rudd &
Glanz, 1990). The mere availability of information does not
ensure that it is processable or, if it is processable, that
it makes sense and will be used in decision making (Bettman,
1979) .
43
Four qualities of information determine if that
information can be used in consumer behavior decisions. The
information must be:
• available;
• useful - the information should supply new
discernment about the characteristics of the
service which will help the consumer decide
these characteristics are desired or helpful;
• processable within the time, energy, and
comprehension level of the consumer; and
• "format friendly" - not only processable but
strategically placed for the decision-making
situation within the required time frame
without confusion (Rudd & Glanz, 1990) .
Health conscious consumers want an available
collection of standardized and thorough health service
delivery data covering a broad spectrum of relevant health
care information (Varner & Christy, 1986) . Consumers want
the information they use to have a relationship between that
information and themselves. Consumers would label this
relationship as relevance (Schamber, 1991) . Relevance could
be called a cognitive phenomenon about the knowledge state
of the individual. Relevance is the "overall concept of
relationships existing between information and information
needs in terms of some value(s) to information users" (p. 8,
Schamber, 1991) . Relevant data should permit consumers to
44
compare and contrast health care providers and plans. The
agency collecting and disseminating this information should
ensure that the data/information is analyzed and presented
in a meaningful and intelligible form to consumers (Varner &
Christy, 1986) . Consumers need quality of care information
which is readily and widely available. This information
needs to be presented in understandable form and be specific
for the hospital or physician the query is referencing.(Rudd
and Glanz, 1990). Researchers also recommend that
information be constructed according to principles based on
Consumer Information Processing (CIP) theory (Rudd & Glanz,
1990). CIP theory framework assumes a "continuous and
reciprocal interaction among elements, resulting in feedback
loops in the decision-making process." (p. 120, Rudd &
Glanz, 1990) . Because of the particular characteristics of a
service, the search for information is more confined
(Barnes, 1985) .
Internal Search
Pre-existing knowledge (prior knowledge/experience)
and memory combine to form the two components of internal
search (Bettman, 1979). Information search generally begins
with internal search. Internal search has two aspects -
direction and degree (Bettman, 1979) . Direction defines
which pieces of information are examined; degree tells how
much information is sought.
45
The direction of internal search is usually determined
by the goals of the consumer. Although what is in memory
may be under the control of current goals, the consumer's
initial search may be for what is not known to provide a
guide for external search (Bettman, 1979) .
The degree of internal search is determined by the
amount of information stored in memory, the suitability or
usefulness to the consumer for the current choice, and the
level of decision conflict (Bettman, 1979) .
Memory is used to refer to almost any way that current
behavior reflects sensitivity to past experience (Bettman,
197 9) . Experience causes knowledge which can be used in
subsequent internal search (Murray, 1991).
External Search
In theory, external search is postulated to follow
internal search. However, a brief internal search which
defines lack of knowledge or uncovers conflict may lead to
external search. Periods of internal search alternating with
external search are typical in the choice decision process.
Prior knowledge concentrates the immediate search and
information collection on a subset of the available
information (Bettman, 1979).
A consumer's ability to use information determines
whether that consumer will search for information to use
according to Stewart, Hickson, Pechmann, Koslow, and
Altemeier (1989). They also note the lack of information
46
readily available to potential users of health care services
and the barriers to access of this information.
Information search is an early influential stage in
the purchase decision process according to Murray (1991). If
the consumer finds that information examined in the internal
search is sufficient for the purpose, then no further search
may be undertaken. However, several pieces of information
gleaned from internal search may conflict or information may
be lacking. Consumers respond to insufficient or conflicting
information with external search (Bettman, 1979) . They
prefer subjective and experiential information (Murray,
1991) .
In a study in Arkansas, Stewart, Hickson, Pechmann,
Koslow, and Altemeier (1989) found that families tended to
rely primarily on information from just a few individuals.
They concluded that even when the consumer is highly
involved in his health care, he rarely uses high levels of
information search because information is not easily
obtained or evaluated.
According to Glassman and Glassman (1981) collecting
medically-related information can be very difficult.
Physician referral services appear very reluctant to divulge
any value-oriented information. Asking the physician's
receptionist can produce inaccurate information. Glassman
and Glassman found that 80% of receptionists surveyed know
almost nothing of their employers' medical backgrounds.
47
Even though consumers in an earlier Arkansas study-
appeared to probably be highly involved in the selection of
a doctor for their children, researchers found that they
carried out only a limited search for information in making
their choices (Stewart, Hickson, Ratneshwar, Pechmann, &
Altemeier, 1985) .
When the consumer perceives a lack of knowledge,
dependency upon referrals from friends, family, neighbors,
and co-workers increases (Beatty & Smith, 1987). As
consumers perceive the risk of a purchase decision to be
greater, they place greater importance upon personal
influence (Murray, 1991). Personal sources become the most
preferred external source of information, second in
importance to only direct observation or experience (Murray,
1991). Many researchers have confirmed the credibility of
the use of personal information sources in situations of
high personal risk (Barnes, 1985).
Past studies (Stewart, Stewart, Hickson, Ratneshwar,
Pechmann, & Altemeier, 1985; Glassman & Glassman, 1981;
Stewart, Hickson, Pechmann, Koslow, & Altemeier, 1989) show
that consumers consult few sources of information in
selecting a doctor and usually rely on the advice of a
friend, neighbor, or family. These findings suggest that
most consumers do little information acquisition when
selecting a physician. Even when selecting a health care
provider for their children, parents usually relied on the
48
advice of friends, relatives, or neighbors (Stewart,
Hickson, Ratneshwar, Pechmann, & Altemeier, 1985; Hickson,
Stewart, & Altemeier, 1988) . Stewart and his colleagues in
1985 also found that fully 82% of the respondents in the
study used only one information source...no respondent in
their study mentioned consulting more than three sources.
Glassman and Glassman found that over 46% of consumers in
their study chose doctors recommended by friends or
relatives. Consumers seem to engage in a pattern of using
relatively little information search when selecting a health
care provider.
The researchers in Arkansas in 1985 concluded that
little change has occurred in the consumer's choice process
over the last 30 years based on their comparisons with
earlier studies. They cited a study made by Talcott Parsons
in 1951 which said that "the majority of people choose their
physicians 'blind' on the basis of recommendations of
friends or neighbors and without any further inquiry!"(p.
255) They also concluded that high involvement alone does
not produce a great deal of search for information,
especially if the customer can not access the information,
lost his attention to the task, has time constraints, or has
made such a decision many times. They felt that the main
factor in influencing the decision process was the advice of
friends, relatives, or other health care providers. These
researchers also came to a judgment that "art of care" was
49
most important to all consumers in their choices of
providers (Stewart, Hickson, Ratneshwar, Pechmann,&
Altemeier, 1985).
Prior to 1980 the AMA's code of ethics banned
advertising and even regulated the size of the letters on
the doctor's office sign (Burton, 1991). In 1980, the AMA
changed its policy on advertising and solicitation as a
result of a Federal Trade Commission ruling on the
advertising ban as a possible violation of the Sherman
Antitrust Act by characterizing the ban as an unfair trade
practice (Allen, Wright, & Raho, 1985). Because of the ban
being lifted, a larger than normal supply of physicians
throughout the 1980s, and a surplus of doctors in many
cities, more physicians have decided to use advertising and
marketing research (Allen, Wright,& Raho). Doctors feel that
advertising does not make the consumer more aware of the
qualifications of the doctor or be of assistance in consumer
choice. Physician attitudes toward advertising have become
more favorable as years have passed (Allen, Wright, & Raho,
1985). In Allen, Wright, and Raho's study, 80% of the
responding physicians felt that consumers could not make
better decisions in selecting a physician through
advertising. The doctors in the study did feel (73%) that
consumers would be likely to select the least expensive
physicians (fee-wise) if fees were advertised.
50
Doctors do not believe that information made available
through the advertisement of medical services will benefit
consumers. Although consumers generally have a more positive
attitude toward advertising than doctors, Burton (1991)
found that consumers think that physician advertising has
the potential to increase the cost of physician services.
Allen, Wright, and Raho theorized in their study that
physicians view the public as unqualified to pass judgement
on professional credentials. The researchers noted that
consumers desire more information about doctors. Physicians
have great concern for the image of the profession and feel
that advertising would be applied in an unprofessional,
unethical manner.
Some physicians realizing the impetus of marketing and
the implications of competition have produced brochures to
advertize their competencies and availabilities.
Publishers of yellow pages do not verify the
information that physicians submit causing yellow pages to
be frequently inaccurate. Further, only eight states
prohibit the use of the term board-certified by physicians
without mentioning by which board they are certified
("Special certification," 1989).
J. M. Reade and R. M. Ratzan reported in the New
England Journal of Medicine in 1989 that they could not
verify the credentials of physicians who advertise in the
Yellow Pages. They also noted that the publishers of Yellow
51
Pages do not routinely corroborate the information about the
physicians listed.(Reade & Ratzan, 1989).
Since 1990, the American Board of Medical Specialties
(ABMS) haved placed advertisements in the yellow pages
listing the names of ABMS board-certified doctors ("Special
certification," 1989).
Doctor certification should "assure the public that a
physician has met certain standards of knowledge,
experience, and skills set by other medical professionals to
ensure high-quality care in the specialty ("Special
certification," 1989). Usually this means that a doctor has
studied beyond the requirements to earn an M.D. or a D.O.
degree. However, not every branch of medicine has a
specialty certification board. Prerequisites for
certification vary from board to board. Some boards certify
for a limited period of time (seven to ten years); others
certify for life or require no recertification.
The U. S. medical community has established the
American Board of Medical Specialties (ABMS) in Evanston,
Illinois, to oversee certification boards. The ABMS
recognizes 23 specialty boards. Not all specialty boards are
covered by the ABMS umbrella. The ABMS does not recognize an
additional 105 medical specialty boards. ("Special
certification," 1989) Some of these unrecognized boards are
perceived to be equal in quality to those certified by the
ABMS according to an article in the People's Medical Society
52
Newsletter (1989). However, the article hastens to point out
that any doctor can start/found a specialty board.
To compound the confusion, the word specialization
often misleads the consumer into thinking that if a
physician has an area of specialization that is the same
thing as the physician's area of board certification.
Throughout most areas of the United States a medical
practitioner can claim to have expertise in an area in which
he/she has no certification or training - otherwise known as
"self-designating." Consumers certainly may find it
difficult to verify the certification of a doctor because of
the confusion in the realm of certification. Confirming a
doctor's education, specialty training, certification, and
other background can be a herculean task according to an
informal study performed by Julia M. Reade, M.D., and
Richard M. Ratzan, M.D., and reported in the New England
Journal of Medicine (August 17, 1989) . The consumer cannot
access any single source of information regarding the
certification of a doctor.(People's Medical Society
Newsletter, 1989)
The consumer may, with persistence, find out about a
physician's credentials by going to the following sources of
information:
• county or state medical associations (The consumer
needs to ask if the information has been
independently verified.
53
• state licensing boards (Again, the consumer needs
to find out if the information has been
independently verified.)
• Marquis' Directory of Medical Specialists (Only-
physicians who are specialty board-certified
are listed.) (Reade & Ratzan, 1989)
• The AMA directory (This mainstream medical
directory contains both verified and unverified
information. A good portion of the information is
coded.)(People's Medical Society Newsletter, 1989)
• The American Board of Medical Specialties (ABMS)
is the governing body for the nation's 24
medical specialty boards, which certify
specialists in various disciplines. Health
care consumers can check out a specialist's
credentials by calling the ABMS toll-free
hotline at 1-800-776-2378, weekdays from 9
a.m. until 6 p.m. EST.
Other sources of information for the consumer include
guidelines released by the Agency for Health Care Policy and
Research (part of the U.S. Public Health Service) this year
(1993) . The agency prepared these guidelines for doctors but
consumers can get them, too. These guidelines will aid the
consumer to team with a doctor to make health decisions for
the patient. The Agency for Health Care policy has printed
simplified versions as consumer pamphlets. Although these
54
guidelines do not help the consumer make a provider choice
they are a source of information in health care choices.
(Findlay, 1993)
Patients all too often have no sources of information
available to give them information about a doctor's
performance (Daley, Gertman, & Delbanco, 1988) . The consumer
finds it difficult to obtain information on performance and
quality of care (Mechanic, 1989). Because of the lack of
information about quality of care and the belief that lay
opinion is adequate as a substitute, consumers have had to
rely on referrals of friends and relatives (Rudd and Glanz,
1990) .
Peer review processes should be re-examined to improve
the peer review process by including more objective
assessment procedures, multiple reviewers, higher standards
for reviewers, elimination of systematic reviewer bias, use
of outcome judgements, and adoption of practice guidelines.
Almost all quality assurance methods use peer judgements to
make the final determination of the quality of care. Doctors
feel that they can maintain control over the standards of
their profession by the effectiveness of peer review
activities. Because physicians agree that the quality of
care is only slightly better than the level expected by
chance, these physicians cast doubt on the standard practice
of peer assessment and whether its shortcomings will cause
further measures to be used as independent indexes of
55
quality. Perhaps peer review should be modified to make it
more reliable (Goldman, 1992).
Congress created a network of peer review
organizations for Medicare to protect against low-quality or
unnecessary care. The Health Care Financing Administration
(HCFA) has found that peer review leads to harsh
disagreements between doctors and that a case-by-case review
is an impossibility (Iglehart, 1992).
Independent peer review is often much too costly for
clients according to David Burda, writing in the January 15,
1992, issue of Modern Health care. Burda cites the
experiences of a Philadelphia-based not-for-profit
foundation created to perform independent peer reviews for
hospitals and physicians. Factors that complicate peer
reviews include lack of expertise to adequately review peer
performance, political motives, loyalty problems, and
personal bias (Burda, 1992).
Information processing technology has improved to the
point where information could be published easily to show
patients' ratings of competing health care providers(Moloney
and Paul, 1991) . Certainly the consumer should have access
to comparison information on costs, ease of getting
appointments, average waiting time for an appointment, and
other indicators of responsiveness (Mechanic, 1989).
Hypotheses
56
This study will delineate and discuss the findings of
a survey conducted to stratify and codify the primary
factors consumers consider important when deciding on a
primary care physician. Specifically the following
hypotheses will be tested:
1. Information plays a significant role in the
selection by consumers of a primary care
physician.
2. Demographics play a significant role in the
consumer selection of a primary care physician.
3. Economic factors play a significant role in the
consumer selection of a primary care physician.
4. Expected health outcomes, by consumers, plays a
significant role in the selection of a primary
care physician.
5. Checking the credentials of the physician plays a
significant role in the selection of a primary
care physician.
CHAPTER II
REVIEW OF THE LITERATURE
This chapter examines the literature relevant to this
study including medical licensing laws, health belief
models, information search, decision-making, anticipated
benefits/consequences, consumer choice and the role of
information, primary care/family practice, and physician
choice criteria such as location, skill, personality, cost,
courtesy, competence, sex, and interpersonal referrals.
Medical Licensing
The original intention of medical licensing laws and
the modern manifestation of such laws are quite different.
When first established during the seventeenth century, in
Massachusetts, New Jersey, and New York, medical practice
laws applied to anyone employed for the preservation of life
or health. The laws required anyone exercising an intrusive
procedure on a person's body obtain advice or consent from
those skillful in the same art, or from the wisest of laymen
who were present (Andrews, 1986).
From the Revolutionary War through the Civil War,
medical societies predominated and established the right to
license physicians and sue for fees. Non-physicians were
typically excluded from licensing, but not from practice
since their procedures, herbal prescription, for example,
57
58
were no less effective, and often less harmful, than the
"heroic efforts" of bloodletting and blistering used by
physicians (Andrews, 1986; Inlander, Levin, and Weiner,
1988) .
Following the discovery of the relationship between
bacteria and disease, by Pasteur and Koch, physicians
claimed superior knowledge over other practitioners. Medical
schools proliferated, and vaccinations and surgery replaced
"heroic efforts" as standard physician treatments.
Physicians, because of the new scientific basis of their
profession, successfully convinced legislators to grant
elusive rights to practice medicine. These factors set the
stage for the passage of the Medical Practice Acts in their
modern form (Parish, 1965; Lechevalier & Solotorovsky, 1965;
Starr, 1982; Andrews, 1986).
Enacted primarily in the late nineteenth century, the
modern medicine practice acts were state efforts to protect
the health, safety, and welfare of its citizens against
infectious diseases. Since physicians had specific training
and demonstrable success against these diseases, the states,
10 percent by 1877 and 50 percent by 1894, passed laws
forbidding all unlicensed individuals from practicing
medicine. The resulting system of health care for the
protection of the public, also created an economic monopoly
for physicians, banned competition, established monopolistic
prices, and denied innovations from non-physician
59
practitioners (Moore, 1965; Stigler, 1971; Begun, Crowe, &
Feldman, 1981; Andrews, 1986).
In 1991, Catherine Bidese (1993) estimated state
boards of medicine issued 45,249 licenses for Medical
Doctors (a physician may hold a license to practice in
multiple states) with New York, California, Ohio,
Pennsylvania, and Texas leading in total numbers. From 1974
to 1990 the overall license issuance increased 26.3 percent.
The official U.S. medical licensing exam, developed
with the aid of the National Board of Medical Examiners
(NBME), was the Federal Licensing Exam (FLEX). FLEX was
developed to replace the multiplicity of state examinations
with uniformity and to reflect advances in medicine and
physician licensing practices. In June 1992, The United
States Medical Licensing Exam (USMLE) replaced the national
boards and FLEX examinations (Bidese, 1993).
In addition to the USMLE, the Special Purpose
Examination (SPEX) is used to requalify physicians who have
taken no further training after their initial examination.
Graduates of foreign medical schools, in addition to meeting
the requirements of U.S. medical school graduates, must pass
the Educational Commission for Foreign Medical Graduates
examination (ECFMG) and complete one year of U.S. or
Canadian graduate medical education before licensure
(Bidese, 1993) .
60
Medical Licensing Monopoly
In the past century, both the number of medical
licensing laws and the average longevity of individuals have
increased dramatically. For example, a century ago only one-
half of the children born in the United States lived past
their fifth birthday (Carlson, 1975). From 1900 to 1991, the
average life span of Americans increased from 47 years to
74.5 years (Cockerham, 1982; U. S. Dept. of Commerce, 1992).
According to some studies the role of physicians and
technology in increasing life span has been overestimated by
physicians, politicians, and the public. Instead, the health
improvement and increased longevity was primarily due to
improved nutrition, better sanitation, and a higher standard
of living (McKeown, 1966, 1976; McKinlay & McKinlay, 1977;
Grossman, 1972).
Other studies have suggested that the increased use of
hospitals and physicians had no measurable health benefit
(Benham & Benham, 1976) and doctors were often credited with
helping people whose recovery was due to their own bodily
healing process (Preston, 1981) . Still other studies found
that new medical technologies introduced between 1950 and
1975 had little overall effect on the general health status
of the population (Thomas, 1977). Similarly, another study
found that morbidity and mortality in Israel and the United
States decreased when physicians went on strike. Finally, a
study by the National Bureau of Economic Research found that
61
one dollar spent for education reduced mortality as much as
one dollar spent on medical care (Carlson, 1975).
Despite America's pride in its medical system, out of
eighteen developed countries, the United States ranks last
in life expectancy and first in infant mortality (U. S.
Dept. of Commerce, 1992). The medical licensing laws,
designed to improve the quality and access to care for
individuals, has dramatically limited the type of
practitioners that an individual may use, the result of
which has been a health care monopoly (and escalating cost)
by physicians whose exclusive practice procedures and high
status are based on a disease-oriented intrusive approach
rather than a preventive approach (Diesendorf, 197 6). This
intrusive approach was developed in the nineteenth century
when the leading killers were infectious diseases
(influenza-pneumonia, tuberculosis, and gastroenteritis).
Twentieth century killers-heart disease, cancer, and
cerebrovascular diseases-are not infectious but rather long-
term onset, or chronic diseases, which require preventive
health care rather than invasive medicine that relies on
physiological precise treatment (Glazier, 1973; Fonaroff &
Levin, 1977; Inlander et. al, 1988).
Given the changing threat of disease and the connection
between lifestyle (e.g., profession, place of work, stress,
choice of diet) and health, U. S. physicians have been
criticized for their training and practice that concentrates
62
on curing rather than preventing diseases (Lemon & Walden,
1966; Wolinsky, 1980; Inlander et. al, 1988). Since
physicians have the exclusive right to deliver health care,
they have neither been forced to justify their approach or
required to provide outcome information. Studies have shown
that only 10 to 20 percent of physicians' techniques are
empirically proven; the error rate in laboratory testing is
between 25 to 50 percent, medical intervention is necessary
only in an estimated 10 percent of all cases, 11 to 30
percent of all surgery is unnecessary, and adverse
prescription drug reaction is responsible for 5 percent of
all hospitalization (Beatty & Peterdorf, 1966; Brooks &
Stevenson, 1970; Anderson & Shields, 1982; Martin, 1982;
Andrews, 1986; Inlander et. al, 1988).
As a result of misdiagnosis, over treatment, and
inappropriate treatment, the potential for patient harm
suggests reform is needed in physician training and
licensing, along with the development of health care
alternatives. Reaction to physicians' exclusive right to
control health care, the results of current health care
procedures, and the spiraling health care costs has taken
several alternative forms including self-care, health care
information providers, mutual aid groups, and the
proliferation of non-physician professional health care
providers (Andrews, 1986; Inlander et. al, 1988).
63
Self-care represents an increase of public confidence
in the ability to make health care decisions and increased
willingness of people to take health (prevention and cure)
into their own hands. This self-care movement is reflected
in the rise of self-care or fitness books from 3 percent of
the hardcover bestsellers to approximately 25 percent in the
early 1980s. These and other information providers offer
health care information typically not available from
physicians. Examples include Prevention magazine with a
readership exceeding 2.5 million readers, American Health
magazine, and the Cable Health Network. Additional sources
of information include health food shops, vitamin dealers,
and exercise instructors (Andrews, 1986; Levin, Katz, &
Hoist, 1979).
Because of the perceived deficiencies in physician
provided care and rising cost, non-physician professional
health care providers, including Acupuncturists,
Chiropractors, midwives, and nutritionists have steadily
increased since World War II. Often these practitioners
operate without any statutory recognition and, hence, in
violation of medical licensing laws. Not only do licensing
laws restrict alternative practitioners in conducting
independent practice but they also limit the uses that
health care institutions may make of non-physician
practitioners for fear of malpractice (Keisling, 1983 ;
Diers, 1982; Inlander et. al, 1988).
64
Without discussing the complicated issue of how to
license all non-physician health care providers, two
fundamental reforms would improve access to health care and
reduce medical costs. Licensing should apply only to those
individuals who practice invasive medicine and prescribe
medication for compensation. This would permit the practice
of health care within families and mutual aid groups, two
groups with the highest level of inter-group trust and
awareness of skill levels. Second, narrow the definition of
the practice of medicine so that it does not cover the
activities protected by the First Amendment guarantees of
freedom of speech and the press. This includes advising,
recommending, and suggesting, even if for compensation,
which would give consumers access to a greater range of
information to assist them in their search for and decisions
regarding health care services (Andrews, 1986).
Information Search and Choice
The hypothesis that individuals undertake an overt
external search for information prior to decision-making has
been popularized in conceptual models by a number of
researchers including Howard and Sheth (1969) and Engle,
Kollat and Blackwell (1968, 1973). Generally neglected,
however, has been research efforts on external search for
information on professional services including health care.
This section reviews the literature concerning the
consumer search process that occurs within the broader focus
65
of this study of decision-making. This includes relevant
external search indices and search determinants, along with
issues relating to the marketing of professional services
and consumer goods.
A number of studies have been devoted to understanding
the processes by which consumers arrive at some type of
decision (e.g., purchase, service selection). From the early
formations by Nicosia (1966) to models by Howard and Sheth
(1969), Engel, Kollat, and Blackwell (1968, 1973), and
others, theorists attempted to identify, examine, and
describe the major stages (e.g., problem recognition,
search, alternative evaluation, choice, and outcomes) of the
consumer behavior process. The empirical verification of the
researchers' models, however, proved difficult (Staelin &
Payne, 1975) and, as a result, a number of limited scope
models have been developed to explain consumer behavior.
These models include the hierarchy-of-effects model of
Lavidge and Steiner (1961), the stochastic model of brand
choice by Aaker (1971), and the extended model of attitudes
by Fishbein (1975). While these models are theoretical and
do not constitute mature theories in and of themselves,
neither are they isolated empirical findings. They are
properly characterized, instead, as middle range theories
that suggest explanations and predictions concerning
relatively circumscribed areas of inquiry (Robertson & Ward,
1973) .
66
Another segment of consumer decision-making research
has centered on two basic aspects. One is information
acquisition (Bettman & Park, 1980; Jacoby, 1977; Russo &
Rosen, 1975) and the other is information integration (Ryan
& Bonfield, 1975; Wilkie & Pessemier, 1973; Wright, 1975).
In spite of the research a large portion of the variance in
consumer choice is still unexplained.
Coinciding with the aforementioned research has been a
reaction to the over-dependency on the cognitive information
processing perspective, a paradigm based on the troublesome
assumption that individuals are information extractors
seeking the correct decision, brand, product, or service.
Olshavsky and Branbois (1979) argue, in fact, that a
substantial portion of purchases do not involve decision-
making at all. "When purchase behavior is preceded by a
choice process, cognition is likely to be very limited"
(Oshavsky & Granbois, 1979, p.99).
Consumer search is defined by Kelly (1968, p.273) as
"that set of information-seeking and information-processing
activities in which a consumer engages preliminary to a
decision on obtaining some goal-object presumed by that
consumer to be available in the market place." Because the
definition focuses exclusively on the pre-purchase search
activities, some researchers have criticized it and proposed
more comprehensive views of the search process. These
researchers include Bloch, Sherrell, and Ridgway (1986) who
67
suggested that ongoing research often occurred outside of a
purchasing situation. It is noteworthy to point out that
individuals have a scarcity of health care service
attributes with which to compare service provider quality
and have a very limited amount of information available in
the marketplace regarding performance criteria for competing
providers (Carmen & Langeard, 1980).
Howard (1977) said that an individual's pre-purchase
behavior was classified into three categories, extensive
problem solving, limited problem solving, and routinized
response behavior, and determined by the individuals
familiarity with the product, or service, and the available
alternatives. Similarly, Bettman (1979, 1980) argued that
consumers searched for information in pursuit of particular
goals, and that the search is a continual cycling between
internal (memory) and external (literature, recommendations,
etc.) searches.
There is a scarcity of empirical evidence on the
relationship between the amount of external search and the
amount of internal search. Stiegler (1961) postulated that
the more information obtained prior to an active search, the
less the need for an external search, and vice versa. While
this inverse relationship is hypothesized during a low level
of perceived conflict, internal and external search are
positively correlated during high levels of perceived
conflict. In addition, the relationship would also
68
presumably depend upon individual differences (Bettman,
1979) .
External search is the process whereby various sources
of information are used by the individual to learn of
alternative solutions to a perceived problem, the
characteristics and attributes of alternatives, and their
relative desirability (Engel, Kollat, & Blackwell, 1973) .
While few researchers tried to alter the essence of the
definition, studies including Duncan and Olshavsky (1982)
and Bennett and Mandell (1969) have attempted to measure the
intensity of the external search (Beatty & Smith, 1987).
Measures of external search have been formulated in
terms of single aspects such as number of stores visited
(Katona & Mueller, 1955; Dommermuth, 1965; Beatty & Smith,
1987), time spent at shopping centers (Kleimenhagen, 1967),
number of shopping trips prior to a purchase decision
(Bucklin, 1966), the number of visits to the store of
purchase (Udell, 1966; Duncan & Olshavsky, 1982), time spent
in purchase decision process (Newman & Staelin, 1971),
number of alternative brands examined (Dommeruth, 1965) and
the amount of information about brands sought by buyers
(Katona & Mueller, 1955). Given the paucity of research
efforts on external search for information on professional
services, the aforementioned research represents useful
trial hypotheses and comparative measures for search
behavior across categories of professional services.
69
Service marketing literature studies indicate a limited
number of sources used in the external search process.
Swartz and Stephens (1984) found in their study of services
(i.e., physicians, financial institutions, and barber/beauty
shops) that individuals used one source of information more
than two or more sources. Stewart (1985), similarly, found
an average of only 1.2 sources of information used among
individuals acquiring physician services. Webster (1988)
found an average usage of 1.8 sources across categories of
professional services including dentists, accountants, and
attorneys. Frienden and Goldsmith (1989), in another study
of professional services, found that 48 percent of the
individuals used only one information source.
Physician Selection
Although research on consumers' selection of physicians
and dentists has been limited (Kuehl & Ford, 1977; Sarker &
Saleh, 1974; Wotruba, Haas, & Oulhen, 1985) some
generalities are discernable. Consumers typically use
several kinds of cues to assess physicians including other
patients, the demographic characteristics of the
professional, the appearance of personnel and facilities,
the location, and personal referral (Bateson, 1979; Bessom &
Jackson, 1975; Lovelock, 1979; Shostack, 1977; Upah, 1983) .
Similarly, Crane and Lynch (1988) found that competence and
courtesy were the most important criteria for individuals
selecting a physician. While Glassman and Glassman (1981)
70
found that personal experience and peer recommendations
served as a major determinant in the initial selection of
physicians, especially with women.
Following the development of a strong physician-patient
relationship, the probability of an individual changing to a
new health care provider is substantially reduced (Klegon,
1981) . Similarly, Tessler and Mechanic (1975) found that an
ongoing relationship with a personal physician precluded
enrollment in a prepaid health care plan by individuals.
Behavior and Roles
Parsons (1959, 1964) argued that professional role
expectations determined the role of the physician. Szasz and
Hollender (1956) examined the role of both patient and
physician in their three tier model (Activity/Passivity,
Guidance/Cooperation, Mutual Participation). Their model
demonstrated a broad range of physician and patient
behaviors. Of particular note was their condition of "mutual
participation" which approaches the current ideal of
patient/physician interaction. The three conditions
compliment the work of Parsons in that they analyze the
patient/physician relationship in functional terms. As noted
previously, Friedson disagrees with this approach, but
several researchers, including Bloom and Wilson (1979),
suggest that Friedson's arguments relating to the fee for
service aspect of medical care is weakly suggested.
71
Numerous researchers tried to describe medical care
behavior and roles from a social and social-psychological
perspective. Navarro, Parker and White (1970) argued that
the medical care system was the result of the class
relationships (roles) in the modern capitalistic society and
that the conflict in the medical care system is an extension
of the broader conflict in the social system. In other
words, the conflict is not between the patients (consumer)
and the physicians but between the dominant corporate and
upper-middle class who control the health institutions, and
the lower-middle and working class who have no control
(Navarro, Parker & White, 1970).
If the relationship between the physician and patient
is controlled by social and economic forces rather than the
individuals themselves then a discussion of those forces is
appropriate. Adam Smith (177 6) provides the starting point
for the development of free market economic theory and for
the analysis of the shortcomings of allocation systems. For
Smith health care should be analyzed in economic terms,
which "could not but color thinking about all aspects of
human relationship in communities" (Bernard, 1973, p.18).
Smith's economic theory of human behavior is also supported
by Friedman (1980), who argues that the key to the free
market is the free exchange of goods and services.
Individuals will not participate in a transaction of their
own free will unless both (patient and physician) are
72
convinced that they have something to gain. To be a perfect
marketplace, meeting the needs of both parties, several
conditions must be met. Both parties must be accountable and
responsible for the consequences, which is to say both
patient and physician must be at risk financially, both
parties must have access to complete information about the
product, price, and the ability to use it in support of the
decision-making process. Further, the marketplace must
encompass a sufficient number of patients and physicians,
who compete, patients for the physicians and the physicians
for the patients, and finally the groups must be large
enough that the parties can enter and leave the field at
will. In sum, there must be both the freedom to succeed and
the freedom to fail (Smith, 1976; Milton Friedman, 1979;
Institute for Health Planning, 1980; Samuelson, 1958).
In the United States, society has been encouraged to
believe that because of the fee-for-service system a free
market medical care system exists. This fee-for-service
payment suggests that the health care system (including
medical procedures) has a real commodity value rather "than
a social service guaranteed by the government, as is more
typical in European countries" (Stevens, 1981).
Mechanic (1978) points out that the current medical
care system has not succeeded in controlling costs or
providing the desired level of services to society. Mechanic
concludes that the medical market has functioned as an
73
allocative mechanism for the delivery of medical service and
there remains considerable problems with distribution and
poor organization despite efforts toward redistribution of
medical care. Given the extraordinary complexity of medical
politics, Mechanic (197 9) concludes that fundamental change
is impossible without political action that will provide
incentive systems for individual patients and physicians.
This corresponds to Knavery's (1976) position that the
health care system is structured by the same social and
political forces that impact the broader structures of
society.
Most contemporary health care providers feel that
managed care networks, that pull together the customer,
provider and insurer into a new alliance, will emerge as one
of the major building blocks to the new health care system.
Quality patient outcomes with negotiated financial terms
will drive an entirely new process in the relationship
between customers and providers (West, 19 93).
Health Maintenance Organizations (HMOs)
HMOs, the results of efforts to provide better service
for individuals and contain health care costs, are prepaid
plans patterned after the Kaiser-Permenete health care plans
developed in California during the 1940s. HMO enrollment has
risen from approximately 6 million in 1976 to 34.1 million
in 1991, while the workforce enrollment in companies' HMO
plans increased from 26 percent in 1980 to 45 percent in
74
1984. HMOs have also been popular with federal employees,
whose membership increased from 8 percent to 16 percent
between 1975 and 1985 (Francis, 1986; U.S. Dept. of
Commerce, 1992) .
Numerous studies examined the factors influencing the
decision to join a HMO (Arthur D. Little, Inc., 1983; Berki
& Ashcroft, 1980,; Juba, Lave, & Shaddy, 1980; Klegon, 1981;
Laird & Herd, 1987; McQuire, 1981; Morrisey & Ashby 1982;
Roghmann, Gavett, Sorenson, Wells, & Wersinger, 1975;
Tessler & Mechanic, 1975; Venkatesan, Moriarty, & Sicher,
1980; Welch & Frank 1986). The research was primarily
descriptive, focusing on who selected HMOs rather than why.
Why consumers select or do not select health care protection
plans has only been recently explored (Berki & Ashcraft,
1980; Thompson & Rao, 1990).
Despite their popularity, or inevitability because of
escalating health care costs, HMOs do not always compete
successfully (MacStravic, 1982). Berki and Ashcraft (1980)
found that both delivery characteristics (e.g., quality,
continuity, comprehensiveness, accessibility) and insurance
characteristics (e.g., price, benefit package) contribute to
enrollment decision. Furthermore, the cost,
comprehensiveness, and accessibility contribute most to
enrollment, while the barriers to enrollment include lack of
familiarity with the HMO model and limitations on provider
choice. Scotti, Bonner, and Wiman (1986), in a similar
75
study, found that the quality of care factors were more
important than cost/benefits factors in explaining the re-
enrollment decision.
Shimshak, DeFuria, and DiGiorgio (1988) examined client
satisfaction and the factors associated with disenrollment,
and found that overall dissatisfaction and dissatisfaction
with specific health care attributes were important
predictors of disenrollment. These factors contributed more
than either the age of the subscriber or the presence of a
non-plan family member. Specific dissatisfactions included
cost of care, quality of care, and inaccessibility of
services.
HMO Disenrollment
Disenrollment is a major problem for HMOs. Travis,
Russell, and Cronin (1989) found that approximately 30
percent of HMO members disenroll each year. Scotti, Bonner,
and Wiman (1986) concluded that for the people planning on
disenrolling that the quality of care was the most important
factor and cost was the second most important factor. Berki
and Ashcraft (1980) found this the reverse for initial
enrollees; cost was more important, followed by quality of
care. Travis, Russell, and Cronin (1989) stated that four
factors accounted for virtually all voluntary disenrollment:
cost (too expensive, prices escalated), choice (limited
choice of doctors and hospitals), quality (physicians'
attitude, lack of responsiveness of plan/staff), and
76
ease/convenience (e.g. distance from home). Of these
factors, Travis et al. found that the leading factor for
disenrollment was cost followed by quality, choice, and
ease/convenience factors at the same approximate value.
Cunningham and Williamson (1980) argued that
maintaining quality of care delivered along with enhancing
patient satisfaction with services provided was vital to HMO
success. Donabedian (1983) found that client satisfaction is
a legitimate component of the quality assessment for a HMO.
Similarly, Zapka and Dorfman (1982) found in a study of a
HMO in a college setting that consumer satisfaction becomes
more important as the consumer becomes more flexible in
their alternatives to seek other means of care.
While accumulated findings of the cited studies are
consistent in their findings that consumer satisfaction is
fundamental to HMO enrollment and re-enrollment (Zapka,
1979), Dolinsky & Caputo (1990) pointed out that most
studies were confined to one HMO and lacked comparability to
traditional fee-for-service populations. In addition,
several authors (Lebow, 1974; Rivkin & Bush, 1974; Ware,
Wright & Snyder, 1975) pointed out that there is a lack of a
conceptual framework in consumer satisfaction studies.
Other factors have been shown to be related to patient
satisfaction. Pope (1978) found that consumer satisfaction
was significantly related to the length of the relationship
between physician and patient, age of the HMO member, and
77
the higher perceived status of the physician. Scitovsky and
Benham (1979) also found physician-patient communication
appropriateness and physician-patient continuity (length of
relationship) to be a factor in the retention of HMO
enrollees. MacStravic (1977) also found the physician-
patient relationship to be instrumental in patient
satisfaction. Similarly, Luft (1981b) suggested that access
and continuity of care are related to consumer satisfaction.
Still other factors have been shown to be related to
consumer satisfaction. Berki and Ashcroft noted that beliefs
about the efficacy and appropriateness of health care
positively influenced consumer satisfaction. Also a Harris
poll (1980) found that 24 hour coverage, convenience, one-
stop shopping for services, physician-patient continuity,
and preventive services contributed to consumer
satisfaction. Fincham and Wertheimer (1986) in their study
of consumer satisfaction found that physician-patient
continuity, self-assessed health, preventive health
practices, and appropriateness of communication from the
physician explained more than 21 percent of the variance in
consumer satisfaction. Finally, Mullen and Zapka (1981)
found that one of the benefits of HMO preventive programs
was an increase in consumer satisfaction.
Hospital Choice
Hospital choice is another major health care choice.
There are allopathic hospitals staffed by Medical Doctors
78
(MDs) and osteopathic hospitals staffed primarily by Doctors
of Osteopathy (DOs). Although all but twelve states have the
same licensing examinations for both DOs and MDs, only about
4 percent of physicians (Statistical Abstract of the United
States 1986) are DOs. Consumer perceptions of the
differences between DOs and MDs, both across time and
geographic regions, were studied by Hoverstad, Lancaster,
and Lamb (1988). There are two basic difference between DOs
and MDs; DOs are disproportionately general practitioners
and they advocate a more "holistic" approach to medicine,
emphasizing body unity, capacity for the body to self-
regulate, and an interdependence of structure and function
(Lane & Lindquist, 1988; Sprafka, Ward & Neff, 1981) .
Because few studies have been done on osteopathic
choice - hospital choice (Margoles, Territo, & Lamberti,
1986) and osteopathic physician choice (Lindquist, 1988;
Riley, 1980; Hoverstad, Wade & Ramb, 1988) - the consumer
choice factors have been primarily determined by studies
relating to allopathic hospitals (Lane & Lindquist, 1988).
An increased competition among hospitals was noted by
Goldsmith (1980). Robinson and Cooper (1980-81) found that
consumers were becoming more active participants in
decisions affecting their health, including hospital choice.
This was related to a significance of proactive individuals
becoming more health-conscious and better informed about
79
health care which was, unfortunately, slowly recognized by
hospital administrators (Bloc, 1984; Hick, 1986).
After it was discovered that consumers could choose
different hospitals (Berkowitz & Flexner, 1981) research
determined that consumers focused on four factors in their
selection: quality of care, cleanliness of the facility,
attitude of hospital staff, and reputation of the hospital
(Berkowitz & Flexner, 1981) . The number of factors was
increased in subsequent research on allopathic hospital
selection, this research included Berkowitz and Flexner
(1981), Boscarino and Steiber (1982), Malhotra (1983), Kurz
and Wolinsky (1984), National Research Corporation (1984,
1985, 1986) and Friedman (1986) . Research on osteopathic
hospital selection included Margoles, Territo, and Lamberti
(1986), Linquist (1986), and five proprietary studies for
the American Osteopathic Hospital Association, two in 1980
and three in 1985, all cited in Lane and Linquist, (1988) .
Lane and Linquist found substantial consistency across the
studies in the choice factors being considered by customers
to select hospitals. For example hospitals "located near
home/convenient" was the primary attribute in Boscarin and
Steiber (1982), and Javalgi, Rao, and Thomas (1991). This
pattern of consistency included the following attributes:
hospital has specialist doctors, reputation, modern
equipment/technology, courteous employees, cost of care,
doctors' recommendations, friend's/relative's
80
recommendation, and type of hospital (Javalgi, Rao, &
Thomas, 1991) .
Woodside, Sertich, and Chakalas (1987) found that
female patient satisfaction, compared to male, with hospital
choice (and stay) was influenced by their perception of
personal participation in the choice decision and their
evaluation of physician attendant during the hospital stay.
Marketing of Health Care Services
The marketing of health care services is a central
concern of health care professionals since it relates
directly to consumer satisfaction (e.g., selection of
physicians, hospitals and health care services) which Luft
(1981a, p251) argued is "perhaps the most important
dimension of HMO performance." Kotler (1986) suggested that
the satisfaction of consumer wants and needs is the backbone
of the marketing-oriented organization. MacStravic (1977)
described the basic marketing principles in a health care
context. Griest (1974) studied the justification of the use
of marketing techniques in health care services and Burger
(1974) examined the marketing models of patient behavior,
while Katz and Soigir (1967) examined the design and
implementation of a marketing program. From the consumer's
perspective on health care marketing the works of Hulka
(1975), Ware (1975), Stratman (1975), Ware and Snyder
(1975), and Kelman (1976) should be examined.
81
Decision Making
Research on decision-making, closely related to
perceptuals, began in the economic and administrative
sciences which developed two major paradigms of decision
making: economic man and administrative man. The economic
man model assumed that the individual would deal with all
alternatives and their consequences, and would know the
probabilities of the occurrence of each consequence. Simon
(1957) said the model of economic man was unrealistic
because of the infinite number of alternatives in complex
decisions, lack of knowledge on the existences of
alternative paths, and the inability to estimate the
infinite number of consequences.
The model of the administrative man was less
problematic because it viewed man as having a limited
knowledge of alternatives and consequences. Within this
model there was three types of decision making strategies:
optimizing, satisficing, and mixed scanning. A plan
describing the type of search, deliberation, and selection
procedure an individual utilizes in the process of making a
decision is known as a decision-making strategy. (Janis &
Mann, 1977) .
Optimizing is a strategy by the decision-maker
expecting the greatest possible reward. Miller and Star
(1967) argued that this strategy was idealistic and
unattainable because of the transient nature of realities.
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Given its unrealistic nature, optimizing was replaced with
the more realistic sub-optimization process. Sub-
optimization is when the decision-maker maximizes selected
benefits at the expense of losing other benefits (Janis &
Mann, 1977). The problem with this strategy is that it
emphasizes the losses, moreover, something is gained at the
expense of losses. Another strategy, satisficing, is closely
related to sub-optimization.
Simon (1957) said that satisficing is a strategy that
strives to meet a minimal set of standards; it doesn't try
to maximize, rather it tries to satisfice. This strategy,
Simon argued, is more appropriate to the limited rationality
of humans.
Moral decision making, elimination by aspects, and
incrementalism are three variants of the satisficing
strategy. Moral decision-making is when an individual
chooses an alternative based on anticipated self and/or
social disapproval (Schwartz, 1970) . The elimination by
aspects occurs when the decision maker methodically
eliminates alternatives that do not contain the selected
(desired) aspects. Similarly, incrementalism is when an
individual makes incremental decisions toward a perceived
goal (Janis & Mann, 1977) .
The last of the decision-making strategies is mixed-
scanning. This strategy is a synthesis of optimizing and the
incrementalism type of satisficing, and involves fundamental
83
policy-making procedures which set basic directions and
incremental processes which prepare for the fundamental
decisions (Etzioni, 1967) .
Models
At least five major theoretical models have been
developed to illustrate the decision making strategies of
individuals. These are Achievement-Motivation, Attribution,
Expectancy, Consistency, and Conflict Models. The
Achievement-Motivation model explains what motivates an
individual to act in a specific way to achieve a particular
goal. Based on the work of Pavlov and Thorndike in the
1890s, the modern Achievement-Motivation model explains how
the personality and environment interact to motivate
behavior (Atkinson & Birch, 1978) .
Attribution Models
The purpose of attribution models is to organize
knowledge regarding "why" behavior occurs and to provide
direction for individuals to control their behaviors. In
other words, attribution models were designed to answer the
question: To what is the behavior attributed? Fritz Heider
(1958), who first proposed theoretical notions about
attribution, concluded that individuals interpret events as
having external (outside self) and internal (within self)
attributions. Of particular importance to medical decisions
is the Attribution Model of Learned Helplessness in Humans
(Abramson, Seligman, & Teasdale, 1978; Garber & Seligman,
84
1980), which refers to the debilitating consequences of
experience with uncontrollable events. Abramson, Seligman,
and Teasdale (1978) hypothesized that learning outcomes are
uncontrollable results in motivational, cognitive, and
emotional deficiencies. The researchers, however, concluded
that helplessness could be reversed and prevented by the
exclusion of defective information processing. Moreover, if
the individual gets the information they feel is right, they
do not feel helpless.
Expectancy Models
To understand the individual's expectation of the
consequences of their behavior is the purpose of the
Expectancy Models. The thesis of the model is that
expectations determines satisfaction which, in turn, affect
the individual's experience. In addition, individual and
peer group attainments influence expectations as does values
and norms in society (Beau, 1964). Lewin (1946) developed an
expectancy model, the Lewin's Force Field Analysis, which
hypothesized that an individual chooses an alternative that
results in expected gains and avoids unexpected gains.
Consistency Models
Types of Consistency Models, all of which are premised
on the notion that individuals aspire to consistency in
their knowing, feelings, and acting, include balance,
congruity, symmetry, and dissonance models (McGuire, 1966).
The dissonance model by Festinger (1964) had a profound
85
effect on the concepts concerning decision making and
included three fundamental assertions: individuals strive
for an internal consistency of cognition or perception of
the world, efforts are made to rationalize any
inconsistencies, and if inconsistencies can not be
rationalized, then individuals feel a psychological
discomfort which Festinger calls dissonance. According to
Festinger and Aronson (1968), this dissonance model predicts
that after a decision, an individual will try to convince
him/herself that the chosen alternative is better than
previously thought. This exaggeration is a means that
individuals often use to deal with the conflict of choosing
one alternative over another.
Conflict Models
Conflict Models theorize that individuals experience
conflict with every decision regarding their own vital
interests. This conflict is the result of having to choose
one alternative over another (Festinger, 1964; Janis & Mann,
1977; Lewin, 1935 & 1948). Based on the existing knowledge,
about the role of psychological stress generated by Lewin
(1935 & 1948) and Festinger (1964), Janis and Mann (1977)
developed a theoretical model call the Conflict Model of
Decision-making. This model explained and predicted the
behavior of individuals in terms of "when, how, and why
psychological stress generated by decisional conflict
impose[d] limitations on human rationality" (Janis & Mann,
86
1977, p. 3) and specified the antecedent variables of risk,
hope, and time that create a level of stress which, in turn,
results in either defective or vigilant decision-making.
Defective decision-making at its most uncommon level is
panic (Quarantelli, 1954) but the more typical response is
defensive avoidance, which manifests itself in three ways:
procrastination, exalting the least objectional alternative,
and individuals deferring decisions to someone else (Janis,
1968) .
Several studies indicate that "hope" contributes to
positive decision-making outcomes (Coulton, Dunkle, Goods, &
Macintosh, 1982; Dufault, 1981; Frank, 1968; Schulz, 1976)
not only with hospitalized individuals, but all individuals,
in the sense of freedom of choice, which is the ability of
individuals to exercise personal control in decision-making,
particularly the chose of alternatives (Janis & Mann, 1977;
Lefcourt, 1973; Averill, 1973).
Behavior Models
One of the earliest researchers to develop a general
theory and model of the behavior of persons in need of
medical care services was Talcott Parsons. In 1951 Parsons
recognized the connection between social systems and culture
within which the patient and provider functioned, and the
individual behavior. His research concluded that a
theoretical understanding of individual medical care
behavior is dependent upon a broad and integrated view of
87
social and behavioral science (Parsons, 1959 & 1964) . As an
example of general theory of social interaction, Parson's
research with the physician-patient relationship was the
foundation for additional research by subsequent
researchers.
Sick-Role Model
Central to Parson's research was the "sick-role" model
(for review of sick role research see Alexander Segall,
1976) which establishes three patient obligations:
motivation to get well, desire to seek technically competent
help, and trust the professional by accepting advice. Of
particular importance is the second which is the decision-
making threshold for the consumer (Parsons, 1951) .
Other research included Mechanic (1962), who concluded
that patients react differently depending upon the way they
comprehend their illness. Which is to say that if the
patient understands that the medical condition is common and
low risk, they will seek treatment in a routine way. If the
condition is understood to represent a considerable risk of
loss, the level of concern will increase and the patient
will be more aggressive in pursuit of treatment (1962) . This
conclusion was based on several assumptions including the
frequency of illness in the population, patient familiarity
with signs of the illness, predictability of the illness's
results, and the potential risk of loss that could result
(Mechanic 1959, 1960, 1961, 1962). While Mechanic's research
88
is focused on the individual decision-making process and
suggests that patient's decisions are based on information,
the research does not describe how extensively the
information is used, or how it is used by the patient (Zola,
1964) .
Friedson Model
Contrary to Parson's optimistic patient-physician model
is the Friedson model, which shows that the patient-
physician relationship is a "tension ridden, unstable
phenomenon" (Friedson, 1961, p 189) and that the Parson
model is a limited perspective, ignoring the necessity of
conflict in human relationships, and best used as an ideal.
In the same study Friedson also developed the concept of the
"lay referral system." This portion of the study showed that
the attitude and behavior of patients who received medical
services from three different types of medical care
organizations moved through definable stages. This was in
contrast to Parson's description of patients behaving in a
standardized pattern in a given societal structure
(Friedson, 1961) .
In a later study, Friedson observed that physicians act
in their own self interest and encourage the patient's
perception of physicians in exalted roles as a means to
control the medical market and the patients. His study also
suggests that market price of medical services plays a role
89
in the decision-making process of new patients (Friedson,
1970-a, 1970-b).
Suchman's Care Seeking Model
Suchman (1965) also examined care-seeking behavior and
in his decision-making model (Coe, 1978, p.116) incorporated
social, cultural, and psychological factors to describe the
behavioral alternatives for the patient. Suchmann's care
seeking model included five major outcome options: Symptom
Experience-denial, delay, or acceptance; Assumption of Sick
Role-denial, acceptance; Medical Care Contact-denial,
shopping, confirmation; Dependent-Patient Role-rejection,
secondary gain, acceptance; Recovery and Rehabilitation-
refusal, malingerer, acceptance.
Suchman's model laid the ground work for a decision
making model and similarly, except in an expanded fashion,
Mechanic (197 8) tried to demonstrate the decision-making
process in a ten step model. Kaduskin (1958) also tried to
delineate the different types of decisions and the various
guidelines within each decision type.
Health Belief Models
A parallel development, and major contributor to the
study of decision-making, are Health Belief Models (HBMs). A
group of social psychologists at the U.S. Public Health
Service developed HBMs during the 1950s in an effort to
determine why people did not participate in programs to
prevent or detect disease (Hockbaum, 1958; Rosenstock 1960,
90
1966, 1974, 1990). The model was subsequently extended to
apply to individual's responses to symptoms (Kirscht, 1974)
and to individuals' behavior in response to diagnosed
illness (Becker, 1974). These HBMs developed by the social
psychologists were based in psychological theory on a
confluence of learning theories derived from two major
sources: Stimulus Response Theory, or S-R (Thorndike, 1898;
Watson, 1925; Hull, 1943), and Cognitive Theory (Kohler,
1925; Tolman, 1932; Lewin, 1935, 1936, 1951; Lewin, Dembo,
Festinger, & Sears, 1944). Furthermore, S-R was itself a
confluence of classical conditioning theory (Pavlov, 1927)
and instrumental conditioning theory (Thorndike, 1898) . To
summarize S-R, theorists argued that learning resulted from
events (reinforcements) that reduced physiological drives
that activated behavior and cognitive theory emphasized the
role of expectations held by the individuals (Lewin, Dembo,
Festinger, & Sears, 1944) . Cognitive theory argues that
behavior is a function of the subjective value of an outcome
and of the subjective probability or expectation that a
particular action will achieve that outcome.
The work of S. V. Kasl and S. Cobb (1966), which can be
grouped with the work of Rosenstock, identified three
groupings of health related behavior. First, is the behavior
of persons who think they are healthy. Their behavior could
include preventive measures such a regular checkups. Second,
91
is the behavior of people who feel ill. Third, is the sick
role behavior, which is behavior for remedy or cure.
Rosenstock based his health-belief-model on the
individual's willingness to act because of susceptibility to
a particular illness and its probable severity. In order to
act the individual must see the potential benefits of the
recommended health behavior contrasted against the costs
(financial, death, disability, etc.) and there must be a
specific stimulant to action, either internal or external,
that causes the patient to pursue the health behavior.
Rosenstock's health-belief-model can be summarized by saying
that preventive service will not be sought by an individual
unless s/he has the necessary health related motivation and
knowledge. Furthermore, the individual must perceive a risk
that can be avoided by medical intervention.
Other contributions to the HBMs included Bandura who
introduced the concept of self-efficacy, or efficacy
expectation (the conviction that one can execute the
behavior required to produce the outcome), as distinct from
outcome expectations (Bandura, 1977a, 1977b, 1986).
Leventhal (1970) concluded that fear, through threatening
messages changed individual's cognition about health
matters. Rogers (1975), similarly, argued that the most
persuasive communications about health matters are the ones
that arouse fear while enhancing perceptions of the severity
of an event.
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Health-belief-models do not provide a complete view of
the individual health behavior variables. Enough research on
the models has been done to describe the limitations and
determine the capabilities of the HBMs as predictors.
Researchers generally agree now that individuals will take
action to prevent, to screen for, or to control ill-health
conditions if they believe: they are susceptible to the
conditions; conditions have potentially dangerous
consequences; if action would be beneficial in reducing
susceptibility or severity of the conditions; that
anticipated barriers to, or cost of, taking action are
outweighed by its benefits (Rosenstock, 1990) .
Criticisms of Health Belief Models
There are five criticisms of HBMs. One, and perhaps the
most fundamental problem is that an individual's belief and
behavior may or may not relate, which is significant if an
attempt is made to develop a policy for the delivery of
medical services based on the predictive reality of the
models (McKinlay, 1972 & Kirscht, 1974) . A second related
criticism is that direct attempts to modify beliefs are
often unsuccessful and that some alternative is needed
(Rosenstock & Kirscht, 1974).
The third criticism follows the second and argues that
both individual and socio-environmental factors should be
targets for health intervention (Rosenstock, 1990; Janz &
Becker, 1984; HBM studies 1974-1984) . A fourth criticism of
93
HBMs is focused on its lack of quantification. A successful
HBM, moreover, would provide numerical coefficients to the
susceptibility, severity, benefits, and self-efficacy, as
well as mathematical relationships between them. With only a
few exceptions (Becker et al, 1977; Maiman et al, 1977;
Cummins, Jette, & Rosenstock, 1978) research has generally
focused on substance rather than on method.
A fifth criticism of HBMs is that by focusing on the
individual determinants of health behavior, there is a
danger that victim-blaming will be encouraged. On the other
hand, Rosenstock (1988) argued that it is possible to assign
blame for health problems to factors outside the individual
while placing responsibility on the individual for problem
solutions. The individual is thus not blamed for having the
problem but is expected to assume responsibility for solving
the problem (Brinkman, et al, 1982) . This model appears to
be appropriate for the prevention of relapse to unhealthful
behavior (Marlatt & Gordon, 1985) .
While HBMs have its roots in the threat avoidance logic
of preventing or detecting serious illness, the model does
have applicability to health promotion such as diet and
exercise regimes whose purpose is to prevent or delay the
onset of illness or disease. In these cases, developing
awareness and specific situations in which efficacy may be
low and rehearsing the desired behavior appears to enhance
self-efficacy (Gilchrist & Schinke, 1983) . Other methods of
94
enhancing efficacy includes relation training to reduce
anxiety during the behavior change process (Gilchrist &
Schinke, 1983; Kaplan, Atkins, & Reinsch, 1984) and verbal
reinforcement to enhance self-efficacy (Nicki, Remington, &
MacDonald, 1985; Chambliss & Murray, 1979a, 1979b; Blittner,
Goldberg, & Merbaum, 1978). The research of Ewart, Taylor,
Reese, and Debusk (1984) suggests that counseling from a
credible source may be effectively used to generalize
specific task-related efficacy expectations to other
behavior.
Summary
The purpose of the preceding review was to provide
insight into research relating to individuals/patients'
decision making process as it relates to health care
decisions and physician selection. While the research has
been both extensive and inconclusive, several
generalizations are evident. Physician profile, health care
enviroment, cost, socio-demographic profile of individual,
and belief systems all effect health care decisions. In
addition, the consumers/patient perceptuals such as
satisfaction, results, quality of care, and
benefit/consequences are pivotal to health care decisions.
The influence of these perceptuals cannot be
underestimated and also demonstrate the lack of factual and
insightful information available to individuals. Because of
the paucity of information, along with service complexity
95
and lack of objective standards to evaluate health care
choices, interpersonal sources (friends, neighbors,
relatives, and co-workers) of health care information is the
most prevalent source of information in health care
selection decisions (Robertson, 1971; Swartz & Stephens,
1984; Frieden & Goldsmith, 1989) .
It is imperative to increase our understanding of
health care decisions and apply the cumulative research to
the fundamental goal of health care which is to provide the
highest quality health care at the most affordable cost to
the most individuals. This study will contribute to that
goal.
CHAPTER III
METHODOLOGY
The purpose of this study is to determine the factors
that influence the consumer's choice of a primary care
physician; to identify what those factors are, and to
determine the significance of each factor and of
combinations of the factors in the selection process.
The Search Decision Process Model
There are several factors influencing the decision in
the selection of a primary care physician. These factors
have been integrated to build a model and is referred in
this study as the Search Decision Process (SDP) model
(Illustration 1). The model is based on how users perceive
the value of information. It includes factors that may be
either antecedents or consequences, both of which serve as
interacting factors in the search decision process. Factors
such as cost, insurance, location and physician profile are
antecedents, or factors that precede the actual decision.
Factors like results and benefit expectations are considered
consequences and also precede the final decision
(Illustration 2). The two types of variables, antecedents,
Xi# and perceptuals (consequences), Yi=f(Xi), interact with
the knowledge base of the consumer, thus creating persuasion
and culminating with the consumer making the decision,
96
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depicted as Zi=g(Xi, ffXj). The process itself is a function
of information that enhances the current state of knowledge
and helps direct the consumer to an informed decision
(Illustration 3). The search and decision process thus forms
the model consumers follow in their selection.
Description of the Population
The population consisted of patients from selected
clinics. The process of selecting the family practice
clinics for the administering of this survey began on
February 15, 1993. To facilitate the distribution of the
questionnaire and control of the survey, the designated
areas for selection purposes were in the Dallas/Fort Worth
area and the Denton/Lewisville area. The directories used to
locate the clinics were the GTE Telephone Directory and
BlueCross BlueShield of Texas Health Select Directory. The
BlueCross BlueShield of Texas Health Select Directory lists
primary care physicians, specialists, mental health and
chemical dependency providers, hospitals and other
facilities in the network. This directory is provided to the
University of North Texas employees who are covered under
this health care plan. When an employee enrolls for
insurance coverage under this plan they are required to
choose a primary care physician from this directory to
receive the maximum benefits allowed. These physicians have
agreed to participate and to offer special price incentives
to the insurance company and therefore to the participants.
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101
Employees have the freedom of choice to seek csrs from 9.
non-participating professional or facility, however; their
benefits will be significantly less. This is because the
rates charged by non-participating physicians will most
likely be higher, therefore, both the insurer and the
insured will be required to pay more to offset the price
increase.
A total of sixteen family practice clinics were
contacted by telephone in the Denton, Grapevine, Highland
Village, Lake Dallas, Lewisville and Fort Worth areas. A
total of ten family practice clinics declined to participate
in the study, giving six clinics to be surveyed.
The population responding to the survey was from the
patients presenting themselves at one of the facilities for
health/medical care prior to seeing their physician. Each
patient had the opportunity to complete the survey. The
attitude and training of the individual handing out the
survey was critical to encourage patients to spend time
completing the survey.
The six family practice clinics that participated in
the administering of the survey were located in Denton, Lake
Dallas, Lewisville, and Fort Worth, Texas. A brief
description of each of the clinics/medical practices is
given below. The specific names of the clinics are not used
to maintain confidentially. For the purpose of this study
102
the facilities will be referred to as clinics A, B, C, D, E,
and F (Appendix D-2).
Clinic A is a large modern facility located in Denton,
Texas with a population of approximately 50,000. This
facility is located within a medical complex that provides a
variety of medical services as well as a drive through
pharmacy. It is within walking distance of the University of
North Texas and located in a rather densely populated
neighborhood. This community also encompasses the Texas
Woman's University with an enrollment of approximately
10,000 students and the University of North Texas with an
enrollment of approximately 26,500 students in 1993. A large
portion of Denton's population are students and faculty
members affiliated with one or both universities.
Clinic A has seventeen staff members which include an
office manager, office supervisor, receptionist, and four
full time staff physicians. Two of the four are Board
Certified by the American Board of Family Practice. The
other two physicians, are family practitioners but haven't
obtained Board Certification by the American Board of Family
Practice. This family practice clinic sees approximately one
hundred and twenty (12 0) patients per day. The receptionist
would offer the survey to each patient as they were signing
in for their appointment (Table 3-1).
The second family practice clinic, Clinic B, is also
located in Denton, Texas. This is a smaller clinic located
103
in an older section of Denton and is again within walking
distance of the University of North Texas. It is encompassed
within a medical complex and with a drive through pharmacy.
Clinic B is a small practice staffed by one primary
care physician who is board certified by the American Board
of Family Practice. It has four staff members which includes
one full time receptionist, two part time receptionists and
a nurse. All three of the receptionists were responsible for
administering the survey. This clinic sees approximately
thirty patients per day (Table 3-1).
The third family practice clinic, administering the
survey, Clinic C, is located in Denton, Texas. This family
practice clinic is a modern facility, with pleasing decorum
located in a small shopping center next door to a day care
center. It is close to the interstate for easy access.
This clinic is a small group practice of two
physicians, who are board certified by the American Board of
Family Practice. The clinic has a total of eight staff
members including two physicians, an office manager, nurse,
and receptionist. This clinic sees approximately 60 to 80
patients a day. The receptionist was the primary person
responsible for administering the survey (Table 3-1).
The fourth clinic participating in the survey, Clinic
D, is located in Lewisville, Texas approximately 18 miles
south of Denton, Texas. This clinic is a large modern
facility that provides a variety of medical services. It is
104
located convenient to the HCA Lewisville Hospital and
approximately a quarter of a mile from the interstate, which
makes it accessible. The population of Lewisville, Texas is
approximately 48,000.
The clinic itself has an open and inviting atmosphere.
There are approximately 20 staff members, including five
receptionists with rotating duties and three physicians who
are board certified by the American Board of Family
Practice. The front office and reception area accommodates
approximately five employees. Clinic D sees approximately
sixty to sixty-five patients per day (Table 3-1).
Clinic E was the fifth clinic to participate in the
administering of the survey. Clinic E is a large modern
facility located within a teaching institution in Fort
Worth, Texas. The population of Fort Worth, Texas is
approximately 447,619.
This clinic has approximately twenty-one staff
members: a clinic supervisor, six receptionists, five
nurses, three physicians, and six medical students. The
director of the clinic is a D.O., and supervises the six
medical students who are on staff full time. The clinic sees
approximately sixty to sixty-five patients per day. The
receptionist had the primary responsibility for
administering the survey. This particular family practice
clinic had the greatest number of surveys returned and the
fastest response in the participation of filling out the
105
survey than any of the other clinics. The enthusiasm of the
staff members and patients at this clinic surpassed all the
other family practice clinics who participated in this
research (Table 3-1).
Clinic F was the sixth and final family practice
clinic participating in this study. This clinic is located
on the north end of Lake Dallas, Texas with a population of
approximately 37,250. This clinic has five staff members.
They are an office manager, nurse, receptionist and two
physicians who are Board Certified by the American
Osteopathic Board of General Practice. The clinic provides a
variety of medical services and treats between thirty to
thirty-five patients per day. The receptionist had the
primary responsibility for administering the survey (Table
3-1) .
Clinics A B C D E F
Number on staff 13 4 6 17 18 3
Number of physicians 4 1 2 3 3 2
Avg. patients/day 120 30 70 65 65 35
Table 3-1. Clinic staffing and average no. patients/day
Data Collection Procedures
This researcher actually started, placing surveys in
selected clinics, on February 17, 1993 and concluded on May
17, 1993. The surveys were collected three days a week on
Monday, Wednesday, and Friday from four clinics: Clinic A,
Clinic B, Clinic C, and Clinic D. The surveys were collected
106
once a week on Monday from Clinic E and Clinic F. Both of
these clinics would be called during the week to answer any
questions regarding the survey. The other clinics were
visited often enough to answer questions as they occurred.
During the collection process the receptionist, from
each clinic, was offered additional support and training in
administering the survey and the opportunity to comment on
their experience in administering the survey. The
receptionist was encouraged to share their opinion in regard
to the patient's reaction to the survey to improve future
efforts of this nature.
In conducting this kind of study it became apparent
one must gain the support and good will of the receptionists
who were being asked to assume additional responsibilities
of administering the survey. The attitude of the individual
handing out the survey and their willingness to answer
questions is important to the respondents who were willing
to take the time to complete the survey. The two clinics
that experienced difficulty in administering the survey from
the beginning of this phase of the study, may have been
influenced by the attitude of the receptionist at these
particular clinics. Once this was brought to the attention
of the physician-in-charge or the office manager the
receptionist was given additional administrative support and
instruction and the flow of completed surveys was increased
two fold.
107
Description of the Survey Instrument
The survey was developed using questions from
recognized instruments which have demonstrated validity and
reliability. Some modification and inclusion of questions
was done so that some questions could be grouped to provide
multiple responses about an issue (grouping questions helps
increase reliability and presents a more valid picture of
the responses). The questionnaire was reviewed by Dr. Bert
Hayslip, University of North Texas Psychology Department and
Karen Bembry, University of North Texas Educational Research
Laboratory. In January 1993 the survey was pilot tested on
24 individuals and the physicians at each of the selected
clinics for content, form and readability.
Patients visiting the participating clinics were asked
to complete the survey consisting of three categories of
questions (Appendix A-l). One category of questions
considered the antecedent factors that affect the choice of
physicians such as, environmental, economic, physician
profile, sociodemographic and self-efficacy (Illustration
2). The second category of questions dealt with the
characteristics that consumers "perceive" as necessary in a
physician and also questions relating to results and
benefits expectations of the consumers (Illustration 2). The
third category of questions addressed the demographic and
socioeconomic data of the sample population.
108
The format of the questions are closed ended. This
format was selected for the following reasons. First, it
provides uniform reference for the respondents and reduces
ambiguity. Second, it is economical to analyze the closed
ended format. Third, analysis of the data is facilitated.
The questions are short and direct to save respondent's time
and to assist in maintaining one's attention span.
Description of the Variables
Based upon earlier studies there are various factors
that affect the decision process in selecting physicians
(Crane & Lynch, 1988; Sarker & Saleh, 1974; Wotruba & Hass,
1985), and hospitals (Javalgi, Rao & Thomas, 1991; Boscarino
& Steiber, 1982). There are certain critical factors that
most consumers depend upon in making their decisions. Not
only are the choice factors important but the process of
internalizing the information gathered and the use of this
information to make decisions are the objective of this
study.
The hypotheses for this study are:
1. Information plays a significant role in the
consumer selection of a primary care physician.
2. Demographics play a significant role in the
consumer selection of a primary care physician.
3. Economic factors play a significant role in the
consumer selection of a primary care physician.
109
4. Expected health outcomes, by consumers, plays a
significant role in the selection of a primary
care physician.
5. Checking the credentials of the physician plays a
significant role in the selection of a primary
care physician.
The independent variables studied comprise factors
that were derived from a factor analysis on all scaled
questions and responses using the Statistical Package for
the Social Sciences (SPSS) release 4.1 for IBM VM/CMS
(Appendix B). There were twelve (12) factors isolated by
SPSS. Of the 12 factors, the ten (10) most significant
factors were used for this study (Appendix C-l). Two factors
were eliminated because they were either duplicated in one
of the other 10 factors or their significance would not have
provided additional insight for the study. The order of
their ranking are as follows:
o Physician reputation (Fl)
o Physician socio-demographic (F2)
o Economic (F3)
o Environmental (location and appointments) (F4)
o Perceptuals (F5)
o Self-efficacy (patient's self awareness) (F6)
o Insurance (F7)
o Communication (doctor-patient communication) (F8)
O Technology (technology and staff) (F9)
110
o Opportunity (time) (F10)
After deriving the factors and ranking the factors by
their relative order of significance, a one way analysis of
variance was done on each factor for each independent
variable representing the characteristics of the patient
population (Appendix B-2);
o Gender
o Age
o Marital status
o Education
o Ethnic origin
o income
o Occupation
o Residence
o Length of time at current address
Data Analysis Methodology
The survey consisted of 21 numbered questions,
although several of the questions were grouped into sub-
questions (Appendix A-l). There were some bivariant
questions of the "yes" or "no" type, others were
multivariant in which the scale range was from 1 to 7 and
others were closed ended questions such as the questions
concerning demographics. The surveys for each clinic were
color coded and serially numbered. This facilitated control
and made it easy to distinguish between clinics.
Ill
The data was analyzed to detect choice factors using
SPSS factor analysis. This factored out the critical
factors. These factors were ranked according the their mean
and then further analyzed using Analysis of Variance. The
results of this analysis are discussed in chapter 4.
Limitations of the Study
The scope of the study was limited by several
restrictions. The first was the limitation of time which did
not allow for a longitudinal study of health consumer
decision making behavior. A follow up study over time and in
different areas of the country would possibly add to the
information base collected and analyzed in this study. Both
time restrictions and access to the clinics were a limiting
factor because there was not free access to the clinics'
patients for an indefinite time frame. Access to the clinics
was at the pleasure of the clinic administrators and the
resident physicians. The research was limited to those
individuals who chose to come to the clinics under study.
Another limitation was the differences in the policies and
administration of each of the family practice clinics.
Although the clinics are very similar in many ways, they did
operate under different policies limiting the ability to
draw useful comparisons in all areas.
The majority of the data were collected using a survey
questionnaire completed by patients as they presented
themselves for their appointment with their doctor. As a
112
written instrument, it potentially suffers from ambiguity.
Respondents to the survey were self selecting, which
also is a limitation of the study. All patients arriving
during the data collection period at the family practice
clinics were asked to complete the survey. However,
compliance was completely voluntary. The time the patient(s)
were asked to complete the survey, prior to their being seen
by their physician, was selected to facilitate data
collection and limit the biasing influence of the quality of
service, also serves as a limitation. This becomes even more
apparent in the next chapter when doctor/patient
communications are discussed.
The results of the analysis are discussed in the
following chapter.
CHAPTER IV
DATA ANALYSIS
This chapter analyzes the data collected at the six
(6) family practice clinics. First the data analysis methods
will be described; second a description of the respondents
to the survey are compared to the general population and
third the data was analyzed in relation to the hypotheses.
Specifically, the model was tested to evaluate the degree of
influence that each factor had on the decision process.
Respondent Characteristics
Data collected from the survey was analyzed using the
Statistical Package for the Social Sciences (SPSS) version
4.1. The first part of the analysis examined the frequencies
of the responses to each question. This was accomplished
using SPSS for statistical analysis, Draw Perfect and Plan
Perfect to construct graphs and charts of the responses
(Appendix D).
In total 3 00 patients responded to the survey. The
data was collected at six family practice clinics between
February 17 and May 17, 1993. The survey instrument was
presented at each clinic to patients who appeared for an
appointment during the survey period. It should be noted
that some clinics required more attention than others.
Frequent visits to each clinic and interest shown in the
113
114
survey enhanced the overall questionnaire completion rate.
Patients were free to choose not to respond. Due to
administrative workload, a specific count of individuals not
responding was not maintained.
In addition to the written survey instruments, 58
telephone interviews were conducted with patients who
completed the survey (Appendix A-2). The individuals
contacted had indicated on the survey their willingness to
participate in a follow-up to the written questionnaire. A
time limit of two weeks was placed on contacting as many of
the of the 13 0 respondents who gave permission to call as
possible. Fifty-eight (58) people were contacted. These
interviews were used to validate some of the questions asked
on the survey and provide anecdotal data and opinions
regarding the research questions. Of the 300 respondents,
130 (44%) indicated that they could be called.
Not all of the 300 respondents answered all the
questions in the survey. Therefore, some questions had
missing cases that were not included in the statistical
analysis. Table 4-1 shows the frequency of responses by
clinic (Appendix D-l).
Clinics
A B C D E F Total Frequency 25 34 56 74 95 16 300 Percent 8.3 11.3 18.7 24.7 31.7 5.3 100
Table 4-1. Number and percent of respondents by data collection sites.
115
Respondents were asked to indicate some specific
demographic data on the questionnaire as follows: gender,
age (by age range category), marital status, education (by
category), ethnic origin, annual income (by income range
category), occupation, place of residence and length of time
at present address. The specific responses to these
questions, by clinic, are shown in Appendix D-l.
Out of a total of 300 respondents, age is divided into
the following groups and percentages: 9 (3%) were under 20
years of age; 71 (23.7%) were in the 20 to 29 age group; 90
(30%) were in the 30 to 39 age group, this was the largest
grouping; 78 (26%) were in the 40 to 49 age group; 33 (11%)
were in the 50 to 59 age group; 13 (4.3%) were in the 60 to
69 age group; only 4 (1.3%) were over 70 and 2 (0.7%) did
not respond. Table 4-2 depicts this breakout in tabular form
(Appendix D-l).
Age of Respondents
<20 20-29 30-39 40-49 50-59 60-69 >70 Missing Tot
N 9 71 90 78 33 13 4 2 300 % 3 23.7 30 26 11 4.3 1.3 .7 100
Table 4-2 Age of Respondents
Of the 3 00 respondents 2 98 answered the question about
their gender. There were 234 (78%) females and 64 (21.3%)
males with 2 (0.7%) not responding to the question (Appendix
D-2). This is consistent with the findings of studies which
have shown that from two-thirds to seven-tenths of the
116
consumers of health care are female (Kuperberg, 1982). Table
4-3 shows the gender and ethnic background.
Gender and Ethnic Background
Variable Respondents Census% n= 300
Gender Female 234 (78%) 50.7 Male 64 (21.3%) 49.3 Missing 2 (0.7%)
Ethnic Background Caucasian 220 (73.3%) 67.1 African-American 33 (11%) 15.5 Hispanic 22 (7.3%) 14.2 Asian/Pacific Islander 8 (2.7%) 2.7 American Indian 6 (2%) .4 Other 8 (2.7%) .1 No Response 3 (1%)
Table 4-3 Gender and Ethnic Background
The predominant ethnic background of the respondents
is caucasian. Two hundred ninety seven (297) respondents
replied to the question on ethnic background. Of those
replying, 220 (73.3%) are Caucasian, 33 (11%) are African-
American, 22 (7.3%) Hispanic, 8 (2.7%) Asian/Pacific
Islander, 6 (2%) American Indian, 8 (2.7%) Other and 3 (1%)
did not respond (Appendix D-2). This data is similar to the
Dallas Standard Metropolitan Statistical Area 1990 Census of
Population which shows 67.1% Caucasian, 15.5% African
American, 14.2% Hispanic, 0.4% American Indian, 2.7%
Asian/Pacific Islander, and 0.1% other.
Respondents were asked to indicate their marital
status by responding to one of five categories. The largest
group indicated they were married, 181 (60.3%); divorced or
separated 49 (16.3%); never married 58 (19.3%); widowed 9
117
(3%); and 3 (1%) did not respond to the question. As
indicted by Table 4-4 over 50% of the respondents to this
survey were married. The 1990 census demographics for the
North Texas area shows 45.8% married, 32.7% never married,
15.1% divorced/separated, and 6.4% widowed. (Appendix D-2)
Marital Status
n=300 Percent Census Married 181 60.3 45.8 Widowed 9 3.0 6.4 Divorced/separated 49 16.3 15.1 Never married 58 19.3 32 .7 No response 3 1.0
Table 4-4 Marital Status of Respondents
Two hundred ninety eight respondents indicated their
educational background. One hundred (33.3%) indicated that
they had some college education. This was the largest group
of respondents. The remainder was as follows: completed
Baccalaureate, 57 (19%); completed post Baccalaureate
degree, 46 (15.3%); some post Baccalaureate work, 29 (9.7%);
completed high school, 34 (11.3%); some high school, 17
(5.7%); completed grade school, 15 (5%); did not respond, 2
(.7%) (Appendix D-2). The level of education overall was
very high as indicated in Table 4-5. A partial explanation
is the proximity of a large part of the population studied
to universities.
118
Educational Background
n=300 Percent Completed grade school 15 5.0 Some high school 17 5.7 Completed high school 34 11.3 Some college 100 33 .3 Completed Baccalaureate 57 19.0 Some post Baccalaureate work 29 9.7 Completed post Baccalaureate 46 15.3 No Response 2 0.7
Table 4-5 Educational Background of Respondents
Respondents were asked about "Total yearly household
income, before taxes, from all sources". Only five (5)
individuals did not respond to the question. The largest
number of respondents 68 (22.7%) indicated income in the
highest category, over $50,000. Only 24 (8%) indicated less
than $5,000. The remainder are as follows: $5,000 to $10,000
23 (7.7%); $10,000 to $15,000 24 (8%); $15,000 to $20,000 24
(8%); $20,000 to $30,000 41 (13.7%); $30,000 to $40,000 50
(16.7%); $40,000 to $50,000 41 (13.7%); and 5 (1.7%) did not
respond to the question (Table 4-6). The total percent is
100.2% due to rounding (Appendix D-2).
Yearly Household Income
n=300 Percent* less than $5,000 24 8.0 $5,000 to $10,000 23 7.7 $10,000 to $15,000 24 8.0 $15,000 to $20,000 24 8.0 $20,000 to $30,000 41 13 .7 $30,000 to $40,000 50 16 .7 $40,000 to $50,000 41 13 .7 over $50,000 68 22 .7 No Response 5 1.7
* Total percent greater than 100 due to rounding, Table 4-6 Yearly Household Income
119
To evaluate the role occupation may contribute to the
primary care physician selection decision patients were
asked to indicate their occupation. This area was divided
into ten categories. The results and percentages are given
below in Table 4-7 (Appendix D-2).
Occupation
n=300 Percent unskilled worker 11 3.7 skilled worker 21 7.0 office/clerical/sales 48 16.0 professional 99 33 .0 management 21 7.0 self-employed 15 5.0 homemaker 35 11.7 student 19 6.3 unemployed 7 2.3 other 19 6.3 No Response 5 1.7
Table 4-7 Occupation by Number and Percent
To ascertain the general geographic location in which
the respondents lived, place of residence was included in
the questionnaire. Table 4-8 depict these results (Appendix
D-2) .
Place of Residence
n=3 00 Percent City of Denton 86 28 .7 Outside city, but in Denton County 54 18 .0 Lewisville 35 11 .7 Dallas/Ft Worth 92 30 .7 Other 31 10 .3 No Response 2 0 .7
* Percent greater than 100 due to rounding Table 4-8 Place of Residence
To evaluate if length of time at a place of residence
had an impact on selection criteria, a question was included
120
in the survey. By far, most people, 186 (62%) to be
specific, had lived at their current residence longer than
two (2) years. The next longest was 1 to 2 years which was
48 people or 16%. After that was 6 to 12 months at 27 people
or 9%; less than 6 months, 38 people or 12.7% with 1 (0.3%)
person not responding. Table 4-9 summarizes these results
(Appendix D-2).
Length of Residence
n=300 Percent < 6 Months 38 12 .7 6 to 12 Months 27 9.0 1 to 2 Years 48 16.0 Over 2 Years 186 62.0 No Response 1 0.3
* Percent greater than 100 due to rounding Table 4-9 Length of Residence
Factors and Components Ranked by Mean (Items scaled 1 to 7)
The survey included items which were scaled 1 through
7. Items marked 7 were considered to be most important when
selecting a primary care physician and items ranked 1 were
considered least important in the selection process. A
factor analysis was done on all scaled items using SPSS. A
total of 12 factors were isolated of which 10 were
considered significant. The factors were physician
reputation, physician socio-demographic, economic,
environmental,perceptuals, self-efficacy,insurance,
communication,technology, and opportunity. The factors were
labeled per the SPSS results. The factors and the components
121
which make up the factor are listed below ranked by mean
(Appendix C-l).
Factor 8 (6.74)
( 6 ( 6
64 18
Factor 7 (6.08 (5.88
Factor 9 ( 6 . 2 0 (5 .87 (5.30
Factor 5 (6.40 ( 6 (5 (5 (5 (4
,34 .87 .81
.39
.25
Factor 4 (5.98 (5.30 (5.30 (4.78
Factor 1 (6.17 ( 6 ( 6 ( 6 (5 (4 (4
15 06 00 56 66 23
Factor 6 (5.95 (5.54 (4 .84 (4 (3
34 57
Factor 3 (5.59 (5.00
(6.52) Communication (doctor/patient communication) Physician spends adequate time discussing condition. Physician explains illness/issues. Physician values patient's opinion.
(6.02) Insurance Insurance coverage. Physician belongs to insurance network.
(5.79) Technology (support) Support staff. Current technology and equipment. Hospital which the physician uses.
(5.68) Perceptuals Physician's personality and manner. Physician's reputation. Access to preferred hospital. Physician's credentials. Physician is recommended by other physicians. Physician participates in research.
(5.34) Environmental (location and appointments) Ease of getting an appointment. Appearance of office. Convenient office location. Office close to residence.
(5.20) Physician Reputation Record of penalties and disbarments. Physician's criminal record. Physician's malpractice record. Tests for HIV or other communicable diseases. Moral standing on medical issues. Number of years in practice. Physician's bankruptcy record.
(4.79) Self Efficacy (patient's self awareness) Selecting a physician is important. Worth extra time to choose physician. Could help a friend select physician. Felt knowledgeable about selecting a physician. Professional qualifications are readily available.
(3.90) Economic Factors Consultation fees and charges. Economic consequences of making a poor choice.
122
(4.46) Extra time required to find the best fees. (3.87) Selecting physician difficult due to complex
services offered. (3.54) Wide difference in fees charged by physicians. (2.85) Selection is difficult because of lack of
knowledge about medicine.
Factor 10 (3.50) Opportunity (time) (5.19) Differences in performance among physicians. (3.81) Little time to search for information. (2.91) Concern for health left little time to search for
physician. (2.10) Pressured by family to act quickly.
Factor 2 (3.47) Physician Socio-Demographic (3.86) Physician has specialty. (3.64) Medical school attended. (3.18) Physician's age.
(2.77) Physician's gender.
Factors by Demographics
Each of the factors are discussed below based upon the
results of a One Way Analysis of Variance using SPSS. If the
probability of the F statistic is less than .05 the finding
is significant, if the probability is greater than .05 the
finding is considered not significant for this analysis
(Table 4-10) .
Gender
Education
Fx
.054
.025
.059
001
362
.001
.008
.001
111
003
001
.557
.104
.167
007
205
.016
. 0 0 2
123
.325
.001
Ethnic .001 .001 .001 .001 178 734 . 6 6 2 .078 001 018
Income .557 009 .001 .007 035 .766 .209 .375 037 009
LengthRes .044 .855 .461 886 .551 .626 .413 .778 .932 .590
DistTrav ,780 .974 .063 808 .772 .120 .788 .685 .571 .723
Occupation .053 .004 001 ,210 .332 .114 .729 .298 .099 .410
MaritalSta .511 153 055 .516 .693 .253 .926 .133 ,480 506
Residence 325 .001 .001 001 019 144 046 216 .001 .045
Table 4-10. Significance by Demographics and Factors
A multiple regression correlational analysis was also
run using SPSS. Since it is difficult to definitively state
what magnitude of correlation coefficient (r) indicates a
noteworthy relationship for this study the following
heuristics listed at Table 4-11 was used.
Size of Correlation Interpretation
.90 to 1.0 (-.90 to -1.0)
.70 to .9 (-.70 to - .9)
.50 to .7 (-.50 to - .7)
.30 to .5 (-.30 to - .5)
.00 to .3 (-.00 to - .3)
Very high positive (negative) High positive (negative) Moderate positive (negative) Low positive (negative) Little if any correlation
Table 4-11 Correlation Values
Factor 1 - Physician's Reputation (Appendix E-l)
Females in the survey thought the reputation of the
physician was more important than did males. The £ statistic
was .0541. Males had a mean of 4.99 for factor 1 as opposed
to the female mean of 5.26.
124
Education appears to have a significant effect (F,
statistic .0250) on a patient's view of the doctor's
reputation. The less educated seem to put more credence in
this factor. There is a significant difference between the
least and most educated at the .05 level. The means of the
groups were; completed high school or less was 5.44, some
college or baccalaureate was 5.21 and some post-
baccalaureate study or graduate degree was 4.98.
Ethnicity appears to have a significant role in the
respondent's view of the doctor's reputation with an £
statistic of .0016. Interestingly, no two groups are
significantly different at the .05 level.
The length of time individual respondents had lived at
the same address appears to be significant (£ statistic
.0445) when related to doctor's reputation. The means by
group was 5.05, less than two years at present address, and
5.29, more than two years at current address.
Occupations has a slight effect on the patient's
perception of the doctor's background. There was a
significant difference at the .05 level between all groups.
Means ranged from 4.92 for students to 6.19 for the self
employed.
The physician's reputation (factor 1) has a low
correlation (between .3 and .5) with the following factors
in rank order: .494 perceptuals (factor 5), .487 physician's
socio-demographic (factor 2), .474 technology (factor 9),
125
.419 environment (factor 4), and .373 economic
considerations (factor 3). The other factors were of little
or no significance when correlated with the physician's
reputation.
Factor 2 Physician Socio-Demographic (Appendix E-2)
Gender appears to have a slight effect on the
respondent's view of the doctor's background with an F_
statistic of .0592. The means were 3.21 for the males and
3.54 for the females. These are averages on a 7 point scale.
Education appears to have a significant effect, F
statistic less than .0001, on the patient's view of the
doctor's background. There is a significant difference at
the .05 level between all groups. The means for this
grouping are; 4.04 completed high school or less, 3.45, some
college or baccalaureate, and 3.03 some post-baccalaureate
or more.
Ethnic background appears to play a significant role
(F Statistic less than .0001) in respondent's perception of
the doctor's background. Caucasians are significantly less
concerned at the .05 level than most other groups. The means
are 3.23 Caucasian, 3.53 Asian/Pacific Islander, 4.37
African American, 4.31 Hispanic and 5.00 American Indian .
Higher income groups show a significantly lower
ranking of concern about the physician's background. The
lowest and the highest income groups are significantly
different at the .05 level. The means for this group are;
126
(3.82) under $15,000, (3.49) $15,001 to $30,000, (3.47)
$30,001 to $50,000 and (3.11) over $50,000.
Occupation has a significant effect (F. statistic
.0047) on the respondent's view of the doctor's background.
There was a significant difference shown between the two
groups, students and the unemployed. The means ranged from
2.77 for self employed to 4.83 for unemployed.
Place of residence had a significant effect (JF
statistic .0002) on the patient's view of the physician's
demographics. The most significant differences between pairs
occurred between Dallas/Fort Worth and all other areas
surveyed and between Denton and Denton County. The means
were 3.94 for Dallas/Fort Worth, 3.45 for Denton, 3.34 for
Lewisville, and 2.94 for Denton County.
The physician socio-demographic information (factor 2)
has a moderate correlation (between .5 and .7) with factor 5
perceptuals (.543) and factor 9 technology and support
(.523). Factor 5 speaks to how people view the physician and
factor 9 how people view the physician's support staff.
Factor 3 Economic Concerns (Appendix E-3)
Educational background seems to have a significant
effect at the .05 level with an F statistic less than .0001
on respondent's economic concerns. The largest difference
occurs between those who have completed only high school and
the respondents who have some higher level of education. The
means of these groups were; 4.43 completed high school or
127
less, 3.86 some college or baccalaureate, 3.56 some post
baccalaureate or more.
Ethnic background appears to significantly effect the
respondent's view of economic factors with an £ statistic of
less than .0001. Means of the responses categorized under
economic factors range from 3.41 (Asian/Pacific Islander) to
4.63 (African American). The only significant difference at
the .05 level was between Caucasians and African Americans.
As income increases concern about the economic factors
seems to decrease. The £ statistic at the .05 level was less
than .0001. The highest income group, over $50,000, is
significantly different, again at the .05 level, from all
the other groups.
Occupation seems to play a significant role, F
statistic .0015, in the respondent's economic concerns.
There are significant differences at the .05 level between
skilled workers and professionals and between skilled
workers and homemakers. The means ranged from 3.88 (self
employed) to 5.24 (unemployed).
Concern for economic factors was significantly
effected (F. statistic .0002) by place of residence. The
significant differences occur between Dallas/Fort Worth and
all other areas surveyed. The overall mean rating was 4.23.
The means by category are; Denton (4.02), Denton County
(3.87), Lewisville (4.03), and Dallas/Fort Worth (4.73).
Closely associated with residence variable was the variable
128
distance traveled. This variable also seems to have an
effect on the economic factor.
Economic considerations, factor 3, did not have a
moderate or high correlation with any other factor. This
factor had a low correlation (between .3 and .5) with the
following factors in rank order: environment, factor 4
(.385), physician's reputation, factor 1 (.373), technology,
factor 9 (.356), opportunity, factor 10 (.341), perceptuals,
factor 5 (.332) and physician socio-demographic, factor 2
(.312) .
Factor 4 Environmental(Appearance & Location)(Appendix E-4)
Gender was significant in this factor with an _F
statistic of .0082. Females were more concerned with the
surroundings and convenience than males. The means were 5.43
for females and 4.99 for males.
Educational level significantly (F. statistic .0003)
appears to effect a respondent's perception of the
environment of the doctor's office. Post baccalaureate work
seems to have the most significant impact. The means for
this category were; 5.66 completed high school or less, 5.41
some college or baccalaureate, and 4.91 some post
baccalaureate or more.
Environmental factors are significantly effected by
ethnic background with an F statistic less than .0001 at the
.05 level. The means ranged from 5.15 for Caucasian to 6.23
129
for African American. The only significant difference in
groups was between Caucasians and African American.
Income level seems to significantly (F statistic
.0078) effect a respondent's view of the environmental
conditions. The only significant difference between groups
was between the highest income group ($50,000 or more) and
the lowest income group (under $5,000).
Insurance coverage was not significant (F. statistic
.0773) in environmental factors when the three forms of
insurance (private, medicaid, and medicare) are combined.
The means for this grouping are; 5.11 self pay and 5.40
insurance.
Lastly, in this area, the concern for environmental
factors (appearance and location of office) seems effected
by place of residence (F statistic less than .0001) . The
significant differences grouped Dallas/Fort Worth and
Lewisville against Denton and Denton County. The means for
the groups are; Denton (4.96), Denton County (5.11),
Lewisville (5.62), and Dallas/Fort Worth (5.73).
Environment, factor 4 has a moderate correlation
(between .5 and .7) with technology, factor 9 (.630).
Subcategories of the environmental factor deals with
location and ease of appointments while subcategories of
technology relates to people and equipment in the office.
Factor 5 Perceptuals (Appendix E-5)
130
Educational background seem to play a significant (F.
statistic .0035) part in the way a patient perceives the
physician especially post graduate education. The means for
the groups are; 5.90 completed high school, 5.74 some
college or baccalaureate, and 5.38 some post baccalaureate
or more.
Insurance coverage had a significant affect, F
statistic .0322, on how the patient's perceived the doctor.
Likewise income level significantly (F. statistic .0355)
fected the perceptual factor. However, no two groups are
significantly different at the .05 level.
How one perceives the doctor seems to be affected by
their most recent visit to the doctor (F. statistic .0353) .
The means for the two groups are; 5.76 most recent visit
within 6 months and 5.49 most recent visit more than 6
months ago.
Place of residence was significant at the .05 level
with an F statistic of .0197. The primary difference exist
between the Denton area and the Dallas/Fort Worth area.
Perceptuals, factor 5, have a moderate correlation
(between .5 and .7) with technology, factor 9 (r=.621) and
physician socio-demographic, factor 2 (r=.543).
Factor 6 Self Efficacy (Appendix E-6)
Females have significantly (£ statistic .0004) higher
ratings of self efficacy. They appear to be more concerned
regarding their selection of physicians than do males.
131
Occupation did not seem to have a large effect
although it is significant at the .05 level, F statistic
.0467, on respondent's rating of need for self efficacy.
However, there was a significant difference between the
groups of homemakers and office/clerical/sales workers and
between homemakers and professionals.
Patient self-efficacy, factor 6, had no significant
correlation with any of the other factors.
Factor 7 Insurance (Appendix E-7)
Insurance coverage was grouped into two sections,
private insurance, medicare, and medicaid versus self pay.
Without question, this factor was significant at the .05
level with an F statistic of less than .0001.
The highest correlation with the insurance factor was
with environmental, factor 4, and this was low at r=.334.
Factor 8 Communications (Appendix E-8)
Gender plays a significant role (F statistic .0076) in
how the respondent's view of the importance of doctor -
patient communication. Females tend to value the attribute
more than males.
The doctor-patient communications seems to effect the
length of time between visits (F statistic .0052).
Interestingly, as we have observed over the past few years,
the intensity of feeling about doctor-patient communications
appears to be a trend although the F statistic (.0782) was
not significant. No two ethnic groups show a significant
132
difference. This factor did not show any significant
correlation with the other factors.
Factor 9 Technology (Appendix E-9)
There was a significant difference (F. statistic .0167)
in how gender viewed the role of technology and support
staff. Females appear to be more interested in this aspect
of health care than do males.
Educational background seems to significantly (F.
statistic .0023) effect the patient's view of the technology
and support staff the doctor has with a slight decrease of
importance as educational level increases.
Concern about technology and the support staff
networks appears to be significantly (F statistic .0183)
affected by race. Caucasians ranked the questions slightly
lower than most other ethnic groups and significantly less
than African Americans at the .05 level. The means by group
are: 5.61 Caucasian, 6.47 African American, 6.21 Hispanic,
6.11 American Indian, and 5.96 Asian/Pacific Islander.
Income level seems to significantly affect (F.
statistic .037 6) the respondent's view of this factor. There
was no significant difference between any two groups at the
.05 level.
Where respondents live seems to have a significant
effect (F. statistic .0001) when they answer questions about
the doctor's support system such as technology, staff, and
hospital. As stated before, the significant differences
133
grouped Dallas/Fort Worth and Lewisville against Denton and
Denton County. The dichotomy of big city versus small city
is an interesting phenomenon and has recurred in these
statistics. This area may be of interest to pursue further.
Technology and support staff, factor 9, has a moderate
correlation (between .5 and .7) with the environmental
factor (r=.630), perceptuals (r=.621), and the physician
socio-demographic background (r=.523).
Factor 10 Opportunity (Time) (Appendix E-10)
Educational level seems to significantly effect (F,
statistic .0002) the opportunity factor. The difference
between high school education and any level of college work
is significant at the .05 level.
As may be expected there is a significant difference
(F statistic .0095) between the lowest and the highest
income groups. As income increases, concern about the
opportunity costs steadily decreases.
Racial background (F statistic .0183) and the place of
residence to a lesser extent (F statistic .0454) seems to
effect the respondent's view of opportunity costs (time,
effort). There was no significant difference between any two
ethnic groups, however, there was significant differences
between the Dallas/Fort Worth area and Denton.
Opportunity, factor 10, did not have a significant
correlation with any of the other factors.
134
Demographics by Factor
Gender
Gender appears to influence the way one chooses a
primary care physician. Females tended to mark higher or
more important in all categories except factor 3, (economic
concerns) and factor 10, (opportunity). The statistics on
gender had a low standard deviation of 0.407. Part of the
explanation for this phenomenon is the high number of female
respondents. As the homogeneity of a group increases, the
variance decreases. As the group under study becomes
increasingly homogeneous, the correlation coefficeient
decreases. Specifically the gender of the patient seems to
be related to the following factors:
Factor 1 - females value a physician's reputation
more than males.
•Factor 4 - females were more concerned with
environmental issues such as appearance of the office and
the ease of getting an appointment significantly more than
males.
Factor 6 - females have a significantly higher
rating of self efficacy - they care more about their ability
to decide than males.
Factor 8 - females appear to be significantly more
concerned with the importance of doctor-patient
communication.
135
Factor 9 - females seem to be more interested in
the technology, facilities, and staff than males.
Age
Age was not significantly related to any factor.
Marital Status
Marital status does not seem to effect any category in
this study.
Educational Level
Educational level is significantly related to factor 1
(physician reputation), factor 2 (physician ethnographies),
factor 3 (economic concerns), factor 4 (environmental),
factor 5 (perceptuals), and factor 10 (opportunity costs).
On average the less educated, completed high school or less,
marked as more important each of the factors listed above.
Some college or baccalaureate degree group marked the next
in importance and some post baccalaureate work or more
marked each of the factors as being less important to them .
Ethnic Background
People in different ethnic groups perceived the
following factors differently: factor 1 (doctor's
reputation), factor 2 (physician's ethnographies), factor 3
(economic factors), factor 4 (environmental concerns),
factor 9 (technical and support) and factor 10 (opportunity
costs).
Ethnicity appears to have a significant role in the
patient's view of the doctor's reputation and background,
136
however, Caucasians seem to be less concerned than the other
groups. Ethnic background had a significant effect on how
the respondent's viewed economic factors, environmental
factors such as location, technology and support available
and opportunity.
Income Level
Income level is significantly related to factor 3
(economic concerns), factor 4 (environmental concerns and
factor 10 (opportunity costs). Overall it appears the higher
the income the less concerned one tends to be concerning
economic factors. Income also tends to play a role in how
one perceives the location and support factors.
Occupation
Occupation seems to effect the patient's view of the
physicians socio-demographics with self employed, unemployed
and students causing the largest deviations. Overall,
students and the self employed tended to mark low levels of
concern, while the unemployed seems to be more concerned
than other groups.
Place of Residence
Place of residence has a significant effect on the
respondent's view of the physician's demographics (factor
2). As stated before, the most significant difference was in
the Dallas/Fort Worth area and all other areas surveyed
between Denton and Denton County.
137
Length of Residence
Length of residence at ones present address seems to
make little difference in the factors under study. When
related to doctor's reputation the length of residence
indicated a trend that the longer one lives in a particular
area the less likely they are to change doctors.
Related Non-Demographic Factors
Insurance Coverage
When all forms of insurance (private insurance, HMO's,
Medicare and Medicaid) are grouped, factor 7 (Insurance) is
significant. Respondents seem to feel having some form of
insurance is important.
Travel
Distance traveled to the doctor's office was not
significantly associated with any factor although a trend
was apparent with factor 3 (economic). This trend appears to
indicate respondents would rather not travel over 3 0 miles
to visit their primary care physician.
Last Time Visited Doctor
The length of time between visits appears to be
significantly related to doctor-patient communication
(factor 8) and perceptuals (factor 5). The stronger the
communications and feeling toward the doctor the more recent
was the last visit to the doctor's office.
Stepwise Regression
138
In order to see if the social statistics had an impact
on the selected factors and to confirm other observations a
multiple regression was done (stepwise entering of data)
using the 10 factors as dependent variables and the ordinal
demographic variables of age, education and income and the
dicotomous variable of gender as independent variables.
These results by factor are listed below:
Physician Reputation-Factor 1: None of the tested
predictor variables showed a significant impact on the
patient's perception of physician reputation at the .05
level of significance.
Physician Socio-Demographic-Factor 2: Of the four
independent variables tested only educational level made a
significant impact on the patient's view of the physician's
socio-demographic background. The correlation between
education and doctor's background shows that the higher
education brackets are less concerned with the physician's
background. This confirms earlier findings that as education
increases concern about the physician's background
decreases.
Economic-Factor 3: Both education and income make an
impact on economic issues in health care selection. Both
show a negative correlation. As income and education levels
increase concern about the economic impact lessens.
Environmental-Factor 4: Education and gender make a
significant impact on patient's perception of the
139
environment of a physician's office (convenience of location
and ease of getting an appointment). Education again showed
a negative correlation. As education increases concern over
convenience lessens. Females also seem more concerned with
this factor.
Perceptuals-Factor 5: Only education showed a
significant impact on perceptuals. Again the correlation is
negative or as education increases the perceptual rating
decreases.
Self-Efficacy-Factor 6: Gender showed a significant
impact on the measure of patient's self-efficacy. Females
seem to feel that they are better able to select a doctor
themselves.
Insurance-Factor 7: Only age showed a significant
impact on people's perception of insurance needs. Most
(78.4%) of the patient's surveyed were covered by some type
of insurance.
Communication-Factor 8: Gender showed a significant
impact on the communication factor. Females seem to need to
know more information about their health.
Technology-Factor 9: Education had a negative
correlation on this factor. The higher the education level
the less concerned patients seem to be about the technology
and support staff.
Opportunity-Factor 10: Education again showed a
negative correlation on opportunity and time enough to make
140
an intelligent decision. The more education the less
concerned patients were about the time and selection.
In summary education affected the most factors,
factors 2,3,4,5,9, and 10. All of the factors affected have
a negative correlation. In other words, persons with low
levels of formal education were more concerned about
physician socio-demographic, economic, environmental,
perceptuals, technology, and opportunity than were people
with higher levels of education. Income only affected factor
3, economics. Age had a negative correlation with insurance.
As people age, they seem to be less concerned with
insurance. This may be related to the particular population
I studied. Most (78.4%) of them had insurance, therefore; it
was not a factor for them to be concerned with. Lastly,
gender affected several factors, factors 4,6 and 8. It seems
females like to be informed and have a pleasant environment.
Significance of the Findings
The objective of the study was to ascertain the
critical factors that most consumers depend upon in making
their selection of a primary care physician. Not only are
the choice factors important, but the process of
internalizing the information gathered and the use of this
information to arrive at a decision were objectives of this
study.
The hypotheses stated were:
141
1. Information plays a significant role in
consumers selection of a primary care physician.
2. Demographics play a significant role in the
consumer selection of a primary care physician.
3. Economic factors play a significant role in the
consumer selection of a primary care physician.
4. Expected health outcome, by consumers, plays a
significant role in the selection of a primary care
physician.
5. Checking the credentials of the physicians
plays a significant role in the selection of a primary care
physician.
The majority of the survey addresses hypothesis one
(1) concerning the role of information in health care
decision making. All ten (10) factors were significant in
various aspects of the population under study as outlined in
the preceding analysis.
Hypothesis two (2) stated demographics play a
significant role in how consumers select their primary care
physician. Table 4-10 summarizes this hypothesis. All
demographic measures except marital status was significant
within one or more of the factors considered.
Hypothesis three (3) concerning economic factors was
particularly interesting. When one considers economic
factors, educational background, ethnic background, income,
occupation, and place of residence all were significant,
142
along with a trend toward distance traveled. Gender, age or
marital status did not appear as significant areas of
concern within economics or money issues.
Hypothesis four (4) addressed the issue of
consequences and expectations, or what is called perceptuals
for this study. In this factor, educational background was
significant with individuals with less education being more
concerned. Insurance coverage was significant as was income
level, most recent visit to physician and place of
residence.
Hypothesis five (5) put forth a statement that
consumers did not check or verify the credentials of a
physician prior to making the decision to select them as
their primary care physician. In the primary survey two
factors addressed these issues, factor one (1) and factor
six (6).
Based upon the preceding data analysis hypotheses one
(1) through four (4) was accepted and hypothesis five (5)
was rejected.
Factor one inquires into the physician's reputation
and factor six makes inquiries concerning how the patient
feels about their decision or choice. The physician
reputation factor was influenced by gender, females being
more interested in this factor; education, the less educated
more interested; ethnicity was significant across the
groups; length of time at present address and occupation
143
were a trend very close to being significant at the .05
level.
Factor six, self efficacy, again was significant by
gender, with females tending to care more about their
ability to decide than males. Occupation was the only other
significant variable in this factor with significant
differences occurring between homemakers and
office/clerical/sales workers and between homemakers and
professionals.
In a follow-up telephone inquiry the question was
asked: "Did you inquire into the credentials of your current
physician before selecting him/her?" Of the 58 questioned 3 6
(62.1%) stated they did not inquire into the physician's
credentials. To follow up on this question if the respondent
answered yes, they were asked, "Where and how did you check
their credentials?" The largest response to this question
was family and friends (33%) which validates other studies
discussed in Chapters I and II of this study. An additional
question that complements the direct questions regarding did
you ask about the physician credentials was, "Did you check
to see if your physician has any malpractice claims or
convictions"? Of the 58 respondents 56 (96.6%) did not
inquire into this issue.
A final question was asked: "Would you like to have a
central place you could call for unbiased information
concerning physician credentials, fees, recommendations or
144
complaints from other consumers like yourself?" The response
to this question was 50 people (86.2%) said they would like
a service of this nature.
Supplemental Questionnaire Responses
Additional information was gathered from a series of
follow up telephone interviews with some of the patients who
indicated a willingness to be called. A total of 58
telephone interviews were completed. Additional interviews
were not conducted for several reasons. First, the
interviews were not intended to provide a statistically
valid sample of the population, as discussed earlier.
Second, time and resources were limited and finally the
calls accomplished their purpose as the information obtained
from the calls consistently validated the written survey.
Results and comments on the follow up interviews are given
below.
When asked if they felt physician fees are fair and
equitable for the service received, 43 (74.1%) felt they
received adequate service for the price paid. The reponses
were not divided into whether or not respondents had
insurance, which would have been an interesting follow-up to
this question. Most people, 47 (81%) did not discuss the
fees/charges prior to deciding on their physician. The
insurance and economic factors would be interesting to
pursue in this regard. By a significant margin, (94.8%)
respondents felt that their physician spent adequate time
145
answering their questions and discussing their illness. When
asked the question, "During your last visit how much time
did your physician actually spend with you", 45 (77.6%) of
respondents stated their physician spent between 10 to 15
minutes with them.
Of the remaining questions, 56 (96.6%) of respondents
felt the receptionist was courteous, 36 (62.1%) did not ask
about their physician's credentials, 57 (98.3%) did not ask
whether their physician had been tested for HIV, 41 (70.7%)
of respondents knew which hospital their physician has staff
privileges in, 56 (96.6%) did not asked about malpractice
suits and lastly 50 (86.2%) of respondents would like to
have a centralized place to call to inquire concerning
qualifications of physicians such as credentials,
specialties, complaints and fees.
CHAPTER V
CONCLUSIONS
This chapter presents conclusions from the data
concerning the selection of a primary care physician using
fuzzy information within a chaotic environmental. There are
hundreds or thousands of individual unconnected fiefdoms:
independent physicians, insurance companies, medical
colleges and universities, specialty hospitals, community
hospitals, military hospitals, clinics, preferred provider
organizations, health maintenance organizations and the
government, from the local to the federal, and this is just
the beginning. There is no entity that ties them all
together and no assurance of quality. It's nearly impossible
for the consumer to differentiate between good and bad
health care until it's too late (Arnot, 1993).
The major conclusions of this study were:
o Patients who evidenced interest in the physician's
reputation had less formal education.
o The lack of a patient's knowledge concerning
medicine was not a significant factor in selecting
a primary care physician.
o Insurance factors are more significant than other
economic factors.
146
147
o people that have insurance are not concerned with
the various factors that tend to increase health
care costs.
o Gender influences the way one chooses a primary
care physician.
o Females value a physician's reputation more than
males, are more concerned with environmental
issues, had a higher rating of self-efficacy,
value communications more, and had more interest
in the technology, facilities and staff than did
males.
o Ethnicity was significant in the doctor
reputation factor, physician socio-demographics,
economics, environmental, opportunity and
technology and support factors.
o Occupation (ie. do you have a job) as a factor in
the selection process was more significant among
the unemployed, students and self-employed.
o The more effective the communication between the
physician and patient the more frequent the
patient visited the doctor.
0 The results of the study indicate the SDP model is
a valid indication of consumer health care
decision making.
This study clearly indicates people want to be
informed, however; there is a problem with locating and
148
verifying information when it pertains to the health care
system, be it information on hospitals or physicians. The
following discussion, based upon the results of this study,
addresses some of the more significant factors.
Communications
The highest overall mean and ranked number one (1) by
the respondents to this study was the factor entitled
communication. This entails the time the doctor spends with
a patient both discussing the reason for the visit as well
as listening to the patient. As one study demonstrated,
"Because patients obviously cannot follow directions they do
not understand, effective communication becomes an essential
factor in promoting their compliance with medical regimens"
(DiMatteo & Hays, 1988). Equally important is personal
manner. Many people tend to weave together their personal
feelings about a doctor and their belief in the doctor's
technical ability. If they like the doctors manners, they
are skilled doctors; if they don't like their behavior they
are incompetent. Evidence suggests that these judgements
influence the patients subsequent health behavior, such as
keeping follow up appointments. Because of this most
important link between patients' perceptions of socio-
emotional aspects of the physician-patient relationship and
their reported satisfaction with the medical care they
receive, that first domino, poor communication and
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interpersonal skills, starts the chain reaction that
determines, to a considerable extent, ultimate outcome.
It's a paradox. This study clearly indicates the
importance of communications, however; patients are often
denied access to specialists by the gatekeeper (primary care
physician), or some even denied access to their doctor by a
secretary or nurse. Doctors who's purpose should be doing
the best within their ability and knowledge for their
patients, have been enlisted as gatekeepers whose primary
purpose is to hold down costs, which sometimes means
delaying or refusing treatment to some patients. (Arnot,
1993). This trait was evident at several of the clinics
observed during this survey.
Time is another confounding element in the
communications factor. "Because of the time consuming nature
of the discussion in the doctor's office," writes David
Hilfiker, M.D., in Healing the Wounds, "we physicians often
are tempted to leave out the description of the process when
talking with patients..." (Inlander et al, 1988). The
patients in this study indicated their physician spent an
average of 10 to 15 minutes with them, whereas; the national
average is around seven (7) minutes. The real difficulties
and danger this inability to communicate may produce is lack
of compliance with the treatment regimen. This in turn
leaves the patient unhappy when the treatment outcome is not
satisfactory as well as feeling betrayed, sure that the
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doctor is guilty of gross negligence. This in turn makes the
doctor impatient and frustrated with the patient's
expectations and somewhat guilty for not having fulfilled
them.
The patient/physician communications issue is a
confusing business, especially when dispensing the news of a
dire prognosis. In the days of the Greek empire, the
messengers of bad tidings were slain. This happens somewhat
figuratively to physicians having to discuss serious
illnesses with their patients. However, a study at UCLA's
Cancer Rehabilitation Project showed that doctors not only
communicate less with cancer patients, but may actually go
out of their way to avoid them. When patients need the most
guidance and information about available treatment
possibilities and alternatives, the physician is not
available or avoids the important points of discussion and
keeps the conversation at the small talk level.
Interestingly, the study found that those doctors who
approached their patients with care, concern, and
sensitivity had experienced serious illness themselves or
had it occur within their own families (Inlander et al,
1988) .
Insofar as communicating and spending quality time
with patients are concerned, doctors could make no better
investment of their time. This study and other studies
referenced in this study, as well as articles read while
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doing research for this study, indicate physicians must
spend the necessary time with their patients if they hope to
be effective healers and practitioners.
Insurance
Insurance factors were second only to communications
to the respondents of this survey. Insurance appears to be a
necessity, however; consumers seem to separate insurance
from health care costs. It is evident that for the most
part, the cost of health care is not perceived by consumers
to be a direct cost to them. It is also evident that health
care costs for society overall have been increasing much
faster than the general rate of inflation. If price is of
concern to consumers at any level, it appears to be at the
insurance level. Because of the insurance safety net
consumers seem not to concern themselves with costs at the
primary care physician level. However, as health care
delivery moves into a different political and social
environment the issues of how much should a procedure cost,
who should pay, should all fees be standard, and how do we
pay must be addressed and based upon the results of this
study the information and criteria with which to based a
decision is just not readily available.
Technology and Support
Factor nine (9) addressed the issue of consumer
concern with technology and support. Based upon this study
the factor of technology placed number three (3) out of ten
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(10) clearly indicating a level of significance. A broad
cross section of variables were significant to include
gender, educational background, ethnicity, income level and
where one resides.
With the ubiquitous computer playing a major role,
technology has driven the major advances in medicine over
the last generation. There has been no parallel drive to
improve the quality of medicine, nor has the quality of
medicine improved according to Robert Arnot, M.D.. The Joint
Commission for the Accreditation of Health Care
Organizations has not been able to maintain the same pace as
technology and they are trying to revise their procedures to
accommodate this trend. The same can be said regarding
physicians and hospitals. Patients still have parts of their
medical record dispersed among competing health care
delivery organizations when technology would allow
consolidation of the record to be accomplished in a very
efficient and effective manner. This issue goes back to the
discussion regarding the lack of a health care system.
Part of the technology factor is concerned with the
hospital the physician uses. Robert Arnot, M.D., in his
book, The Best Medicine, recommends that one search out an
outstanding hospital prior to selecting the surgeon or
physician who will perform the procedure. When you are
discharged, 80% of the success of the procedure is
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determined by the care you receive in the hospital (Arnot,
1993) .
Hospitals do not release infection rates, mortality
rates by given procedures, or names of practitioners who
have lost privileges, been suspended or provide you with the
number of like procedures that a particular doctor has
performed in that specific hospital and the outcome of those
procedures. Further, they do not divulge publicly the rate
of medication error, the rate of adverse medication
reaction, nosocomial infections, or descriptions of clinical
trials and clinical experiments proposed or conducted in the
facility. The hospital used is part of the technology factor
and is critical to the overall outcome of procedures
performed in that facility.
While these items may seem technical to the decision
maker, the reality is that they and many others provide the
basis upon which decisions about care must be made.
Individuals can only make informed decisions about the
treatments and providers of care with information that
addresses quality and competence. Disclosure of health data
must be all encompassing. It must not be limited to just the
information the medical community deems appropriate. It must
be all the data and it must be reported in understandable
terms.
Perceptuals
This factor ranked number four (4) and is closely
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related to the communication factor and criteria. The study
indicated consumers are very interested in their physicians
personality and manner. They tended to ask friends and
assosciates who they would recommend and about how they felt
about the physician, vis-a-vis their reputation. Consumers
tend to put a great deal of reliability and credence in the
opinion of friends and associates as was verified by this
study.
Environmental
Price and product knowledge did not appear to be as
significant a part in the choice behavior of the respondents
as was location and ease of getting an appointment. This
variable, environmental, was examined by asking respondents
about the ease of getting an appointment, appearance of the
office, and the convenience of the office location.
Responses indicated this was indeed an important factor. It
ranked number five (5) out of ten (10), ahead of physician
reputation, self-efficacy, economic factors, opportunity,
and physician socio-demographics. These data indicate that
it can be said with some confidence that the perceived
convenience of the health care provider is important in the
initial decision making process. Again, this result cannot
be generalized with confidence beyond the population
studied.
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Physician Reputation
One of the more confounding of the factors is the
issue of physician reputation, which ranked number six (6)
out of ten (10). This factor includes information concerning
penalties and disbarments, criminal record, malpractice
record, moral standing on medical issues, personal and
business financial records and others items which may
contribute to ones knowledge prior to making a selection of
a physician. This one decision, concerning the selection of
a primary care physician, may indeed be the most important
decision an individual will make in their life. The
population in this study did not seem to possess any
specific knowledge about the provider they chose. The public
likes the idea that "doctors" will cure them or even keep
them from death (Smith, 1993) .
This study shows that those patients who evidenced an
interest in physician reputation tended to have less
education, females tended to place more credence on this
factor than did males, ethnicity appeared to play a role,
and to a slight extent length of time at present address and
occupation indicated a trend. Respondents seemed to think
reputation was important, but not enough so to spend the
considerable effort necessary to verify their feelings. This
issue refers to an earlier statement regarding verifying
information on hospitals and physicians such as mortality
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and morbidity rates and relates very strongly to factor
five, perceptuals..
The lack of knowledge is partially explained by the
complexity of health care which arises because of biological
variability, the probabilistic nature of most outcomes, the
variability with which interventions are applied, the rapid
rate of change in health care, the sheer number and range of
interventions, and the difficulty of conducting experiments
with human subjects. Indeed, the chaos theory suggests that
the complexity of health care may make it intrinsically
unpredictable: We may never be able to know what we would
like to know (Smith, 1993). Interestingly, the respondents
in this survey indicated they did not consider their lack of
knowledge concerning medicine, to be a significant factor in
their selection of a primary care physician. Rightly or
wrongly, the consumer places an tremendous amount of faith
and confidence in their physician to know what to do and to
do it right.
This factor of physician reputation, is a significant
area of concern and difficult to measure, however; it must
be addressed in a meaningful and responsible manner.
Self-Efficacy
Another area addressed in the study was self-efficacy
or the self awareness of the individual. Some of the
components of this factor are: selecting a physician is
important, worth extra time to choose a physician, felt
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knowledgeable about selecting a physician and the
professional qualifications of physicians are readily
available. This factor ranked number seven (7) out of the
ten (10) factors evaluated. The only highly significant
finding was that females were more concerned regarding their
selection of physicians than were males.
Of particular interest in this factor is at present,
others; employers, insurers, insurance claims adjusters, the
government, or a doctor being paid by your company, choose
the care for most insured consumers. Dr. Stanley Reiser
stated in the Journal of the American Medical Association
that creating consumer competence and responsibility in
health care choices is the key to health care reform in the
United States. The concept of placing authority and
responsibility in the hands of individuals has been
important in the shaping of American history, but not in
American health care. Health care, the "experts" explain,
needs judgements made by more competent individuals than the
average consumer (Arnot, 1993).
However, consumers do need to make a choice and
hopefully, an informed correct choice. One is not likely to
luck into great health care. If you select a physician or
hospital that delivers second rate care, no amount of
questioning, badgering, and checking is going to make the
care you receive first rate (Arnot, 1993). If you take your
car to an incompetent mechanic, it may only fail to start or
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run. If you make the wrong health care decision you may not
have a second opportunity to correct the first bad decision.
Economic
Economic factors placed number eight (8) out of ten
(10) factors considered. The interesting aspect to this is
insurance placed number two in importance and the very
factors that drive insurance rates, the economic factors
placed number eight on the rating scale. What appears to
occur is once people have insurance they ceased to be
concerned with the various factors that drive health care
costs such as physician fees, laboratory costs and other
services rendered. Different approaches are being discussed
regarding the economics of health care delivery, one of the
approaches being economic credentialing.
The term economic credentialing is new to the health
care literature and has historically been related to
exclusive contracts that are executed with hospital based
physicians. Economic factors have rarely been utilized in
the credentialing process for physicians. The current
process relies extensively on the use of clinical data,
professional competency and professional conduct. There has
been little written on the criterion to be established and
utilized in an economic credentialing process. Health care
providers have been concerned with structuring fair hearings
and due process into their medical staff by-laws, but new
efforts to contain costs will force managed care networks to
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look closely at efficient and effective use of resources in
the treatment of patients. New forms of active economic
credentialing will entail a close examination of under and
over utilization of health care resources (West, 1993).
With increased emphasis on cost containment, providers
within managed care networks will be evaluated according to
how they use facilities, acquire equipment and technology,
utilize specialized personnel, and consume supplies and
materials in the patient treatment process. Furthermore,
adverse patient selection will have significant financial
repercussions on the economic stability of any organization.
The types of financial data that most readily lend
themselves to economic credentialing include the costs
associated with malpractice claims, previous patient
profiles, admissions generating capacity, average length of
stay, charges per admission, and resource utilization in the
area of capital, personnel and supplies. Most organized
medical groups are opposed to using economic credentialing
although there has been general acceptance in the use of
exclusive contracts for hospital based medical services.
Some physicians argue that using financial data for economic
credentialing purposes would interfere with the quality of
medical services provided to patients and present ethical
dilemmas (West, 1993).
The real concern is not whether economic factors will
be utilized in the credentialing process, but rather what
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procedures will be utilized to facilitate the appropriate
usage of economic criterion along with quality clinical data
to assess providers of health care services. Once again, how
do we measure outcomes and pay for results?
Based upon this study, the lack of concern about cost,
by the population studied, is not surprising. One reason for
this lack of concern may be by having insurance one does not
realize the costs until one loses ones insurance coverage,
by policy cancellation, loss of employment or some other
reason. Another reason may be that people feel health care
is a right. The Clinton administration is in the throws of
this conundrum as this study is being written.
Health Care Reform
This study has addressed three of the most debated
issues in health care reform; physician selection,
insurance, and costs. Health care reform, the domestic
program that is suppose to change Americans' lives more than
any legislation since the Social Security Act of 1935 is
under intense public and political scrutiny. It is estimated
to cost somewhere between $30 and $150 billion a year,
depending upon the estimate you choose to quote and the
point one is defending at the moment.
There seems to be two primary alternative public
policy courses under serious consideration. The first often
discussed, is for one payer universal national health
insurance coverage, patterned to some extent after the
161
Canadian model. Various options have been put forth
concerning this model, discussed, and died in the arena of
political reality. The second alternative, and the one that
appears to be gaining favor, is alliances of consumers and
employers that will negotiate with groups of insurers for
health care services at the "lowest" cost. The Federal
Government will define a standard package of benefits that
must be made available to everybody. States will have the
responsibility of setting up alliances of consumers and
employers that will negotiate with pools of insurers to make
certain the package is actually delivered (Church, 1993).
As presently envisioned the basic benefits package
guaranteed to all Americans will be more generous than most
people's current coverage. It will probably cover mental
health, dental benefits, hospitalization, outpatient care,
checkups, prescription drugs, prenatal care, preventive
medicine such as mammograms and more. While the details are
still vague, most patients are likely to pay a low fee for
each service, while the health plan covers the balance. This
approach is what the respondents in this study indicated is
important to them. They don't want to be concerned by what
health care costs, the insurance should take care of this.
They are interested in their ability to receive appropriate
health care and the ultimate outcome.
If health care is removed from the private insurance
market, and placed in the public sector, several advantages
162
and benefits will become immediately available. Since
convenience is important to the consumer, primary care, and
the potential for cost saving that early intervention
represents, should be universally available and
geographically distributed to maximize consumer convenience.
Those presently uninsured would have access to health care
and particularly preventive care such as pre-natal.
The issue of consumer choice is of primary importance
and was indicated as such in this study. Consumer choice is
conceptually based upon the assumption of consumer
knowledge. This study as well as others indicate this
knowledge just does not exist. One area that should be
encouraged is knowledge of the alternative types of primary
care available to the consumer. Consumers should be allowed
to make choices at the level where differentiation is
important, between the allopathic primary care provider and
alternative types of primary care, including, but not
limited to, those alternatives which require an increase in
knowledge and consumer participation in the decision making
process. For example, consumers should be given the
opportunity to choose physical therapy or nutritional
therapy as opposed to other types of intervention by a
medical doctor. The present insurance system mandates that
you only seek alternative treatment if your physician
approves. This method of treatment is self serving to the
medical community and not to the consumer seeking care.
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This study clearly indicated consumers are concerned
with who they choose and how they are treated once they make
that choice. The debate ought to be about safety and choice,
about who should and should not be permitted to provide
health care and why. It should not be about one belief
system versus another, for the belief that a sick person
should be cared for and assisted to get well, by whatever
means, ought to be at the heart of any system concerning
health care. No one school of thought ought to ostracize
another, if together they can provide the building blocks of
diagnosis and treatment. Uwe Reinhardt, Princeton University
political economist, warns of the risks that exist in
pursuing the care of non-physician practitioners instead of
that of M.D.s or D.O.s. "It could be dangerous, but then you
have to go by the principle that I thought organized
medicine always went by, and that is we should have a free
market in health care, and a free market is dictated by the
principle of caveat emptor, let the buyer beware." Patients
ultimately bear the cost of malpractice, and therefore
should have the right to decide the degree of risk they are
willing to accept.
This study has evaluated the consumers attitude and
feelings toward the selection of a primary care provider.
There are no tricks or shortcuts involved in improving the
physician-patient relationship. A failure on the part of
either party increases the likelihood of mistakes, and of
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other situations in which there are no winners, only
victims.
The most important factor in this study,
communications, depends upon an interrelationship based on
trust. Patients must take responsibility for their own
health care. To do this they must become more knowledgeable,
with realistic expectations concerning what medical science
can do. Physicians, for their part, must recognize and
accept their limitations vis-a-vis the biomedical model and
the role of medical care. Physicians must reevaluate their
place and power in the health care process and share their
knowledge and uncertainty with their patients. Likewise,
patients must take more responsibility for their health and
challenge the physicians to do a better job and to
communicate more effectively. Physician and patient must
strive to understand each other and build a supportive
relationship that aids the healing process. We must not let
economics and greed rule.
The momentum, for the first time in history, is in the
consumer's favor. Consumerism in health care will mandate
more of a partnership between the provider and the patient.
Control of medicine has been in the hands of physicians and
politicians for the past 100 plus years, and the results
speak for themselves. According to the National Center for
Health Statistics the United States spends more money on
165
health care ($838 billion in 1992) yet ranks lower in life
expectancy than 16 other industrial nations.
Future Research Needs
As our society moves toward a different paradigm of
delivering health care, the changes that will be required by
all the members of the health care delivery system must be
analyzed and studied for future direction. Studies
concerning the role that physicians, insurers, alternative
care providers, government and others will play in a dynamic
health care environment must be addressed. What will be the
role of informational technology and how will it change the
way health care is delivered presently?
With local area networks for alliances of physicians
and individual hospitals, wide area networks for regional
kinds of support needs and the super highway nets such as
the internet providing a medium for connecting the varied
aspects of health care, studies as to how to manage this
network of information is a must. As this study discussed
the role of divergent sources of patient information and the
need to synthesize multiple patient records into a cohesive
whole, how this is to be done using technology must be
explored. What are the emerging trends in the health care
industry: 1) concerning computing; 2) what is the impact of
health care reforms on information systems needs; 3) how are
current health care organizations meeting the information
needs of both the physicians and the patients; 4) how can we
166
measure better results/outcomes from current and future
health care systems; 5) how do we connect the systems of
networks with different hardware and software and maintain
comprehensibility; and 6) how do specific factors of culture
and language affect the selection process of a primary care
physician.
Medical Informatics is entering a new era in health
care. The issues of image information systems and how to
manage and retrieve them must be studied along with how to
train both the technical and support personnel concerning
how to manage this potpourri of technology. With the advent
of networks, palmtop computing, and medical records on a
card the size of a credit card; health care is becoming
truly international with a need to understand through
research the multi-faceted social and political realities
being encountered. Maybe salient aspects of this conundrum
can be resolved through research.
APPENDIX A
SURVEY INSTRUMENT
167
168
INFORMED CONSENT PHYSICIAN SELECTION STUDY UNIVERSITY OF NORTH TEXAS
Dear Research Volunteer:
The purpose of this study is to determine the information people consider when they choose a primary care physician. In order to gain a clear understanding of the various factors you, the consumer consider important, we are asking that you take a few minutes to complete the attached survey. Your answers will be completely confidential and you may remain anonymous if you wish.
Your time and participation is greatly appreciated.
Thank you,
E. Sonny Butler University of North Texas
169
ID # SURVEY
When in need of medical attention whom would you first refer your problem to?
(1) Primary care physician (2) Health Maintenance Organization
Organization (PPO). (3) Health Center/Clinic (4) Hospital/Emergency Room (5) Other
(HMO) or Preferred Provider
How many different physicians did you consider before selecting your current one (including the one you chose)?
Number of physicians considered .
The following is a list of sources which you may have used in locating your doctor. Please check those sources you used (check all that apply). Next, for those sources actually used, please rate the importance of each in your final selection decision using the 7 point scale below.
Source of Information
Did Use Not Source Important
Very Important
Advertising, brochures 1 2 3 4 5 6 7 Referrals (other doctors) 1 2 3 4 5 6 7 Physician referral service 1 2 3 4 5 6 7 Friends, Relatives, Neighbors, Co-Workers 1 2 3 4 5 6 7
Noticed at Random 1 2 3 4 5 6 7 Local Medical Association 1 2 3 4 5 6 7 Yellow Pages 1 2 3 4 5 6 7 Contacted Doctor's Office Directly 1 2 3 4 5 6 7
Others 1 2 3 4 5 6 7
Is the cost of treatment paid by:
(1) Self (2) Insurance (primary payor) (3) Medicaid
(4) Medicare (5) Not sure (6) Other
How far do you travel to get to your physician's clinic!
(1) 1 to 10 miles (2) 10 to 30 miles (3) more than 3 0 miles
Do you think that it is important to have a family physician?
(1) ( 2 )
Yes No
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How long have you been going to your current physician?
(1) Less than 1 year (2) 1 to 3 years (3) 3 to 5 years (4) more than 5 years
When was the last time you visited a primary care physician?
(1) One week to a month (2) A month to six (6) months (3) Six (6) months to a year (4) More than a year
How important are the following factors in your selection of your primary care physician. Rate your factors on a scale of 1 to 7, 1 being not important and 7 being very important.
Not Important
1 2
Very Important
4 5 6 7
Physician discusses illness/issues in a language I can understand.
Physician is recommended by other doctors.
Physician has access to a preferred hospital.
Physician has a good personality or "bedside" manner.
Reputation of physician.
Number of years of service.
Physician participates in research.
Sex of the physician.
Physician has a speciality.
Medical school attended.
Age of physician.
Physician values my opinion.
Physician spends adequate time discussing illness and answering my questions.
Physician makes house calls and other weekend and emergency policies.
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10. How important are the following factors in making your choice of a primary health care physician? (Ranks range from 1 to 7, not important to very important).
Not Very Important Important
1 2 3 4 5 6 7
Convenient office location.
Ease of getting an appointment.
Appearance of office or clinic.
Technology and most up to date equipment.
Quality of support staff.
Close to your residence.
Hospital physician uses.
Consultation fees and charges.
Insurance coverage.
Physician belongs to your insurance network of physicians.
11. How important might the following credibility factors be in your choice process for a primary health care physician? (ranging from 1 - not important to 7 - very important)
Not Very Important Important
1 2 3 4 5 6 7
Credentials of a physician.
Moral standing on medical issues.
Physician's criminal record.
Physician's bankruptcy record.
Record of any penalties or disbarments from a professional association.
Record of any charges of medical malpractice against a physician.
Medical record, particularly of tests regarding AIDS and other communicable diseases.
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12. Rate your choice factors that you might have considered while selecting your primary care physician on a scale of 1 to 7 ranging from 1 strongly disagree to 7 strongly agree.
Strongly Disagree
1 2
Strongly Agree
5 6 7
When I chose my doctor, I had little time to search for information.
I feel there are wide differences in performance between the available choices of doctors.
The process of selecting a doctor is important to me.
I felt quite knowledgeable about selecting a doctor before I began searching for one.
Being a smart consumer is worth the extra time it takes when choosing a doctor.
I believe I could be quite helpful to friends who are having difficulty choosing a doctor.
I am willing to spend extra time searching in order to get the best possible fee for doctors of similar quality.
When selecting a doctor, I am concerned about the economic consequences of making a poor or incorrect choice.
Choosing a doctor was difficult because the services rendered are very complex.
I received considerable pressure from other family members to select a doctor quickly.
I spent more time deciding on a doctor because of my lack of knowledge and expertise about medicine.
There were wide differences in the fees charged by the doctors I considered.
I find professional qualifications about physicians are readily available.
Because I was concerned about my health getting worse, I had little time to search for a doctor.
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This section of the questionnaire contains a series of questions about your demographic characteristics such as age and income. We are asking these questions to determine if various groups have different opinions and attitudes about selecting a primary care physician. Therefore, we hope you will answer these personal questions. The responses you provide will not be associated with your name for the study.
13. Gender
14. Age
(1) Male (2) Female
(1) Below 2 0 years (2) 20 to 29 years (3) 30 to 39 years (4) 40 to 49 years
(5) 50 to 59 years (6) 60 to 69 years (7) over 70 years
15. Marital Status
(1) Have never been married (2) Married
(3) Widower (4) Divorced or Separated
16. Educational Background
(1) Completed grade school (5) (2) Some high school (6) (3) Completed high school (4) Some college (7)
Completed Baccalaureate Some post Baccalaureate work Completed Post Baccalaureate
17. Ethnic Origin
18,
(1) Caucasian (2) African-American (3) Hispanic
(4) American-Indian (5) Asian/Pacific Islander (6) Other
Total yearly household income, before taxes, from all sources,
(1) Under $5,000 (2) $5,000 to $10,000 (3) $10,000 to $15,000 (4) $15,000 to $20,000
(5) $20,000 to $30,000 (6) $30,000 to $40,000 (7) $40,000 to $50,000 (8) Over $50,000
19. Occupation
20.
(1) Unskilled Worker (6) Self-Employed (2) Skilled Worker (7) Homemaker (3) Office/Clerical/Sales (8) Student (4) Professional (9) Unemployed (5) Management (10) Other
Place of residence
(1) City of Denton (4) Dallas/Fort Worth (2) Outside city, but in (5) Other
Denton County (3) Lewisville
21. How long have you lived at your current address?
(1) Less than 6 months (2) Between 6 and 12 months (3) 1 to 2 years (4) Over 2 years
174
ID #
May we call you to clarify or validate sections of this questionnaire if necessary? This page will be separated from the survey.
If yes please print your name and telephone number in the space below. Thank you very much for taking the time to complete this survey.
Nam*
Phone
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SUPPLEMENTAL SURVEY QUESTIONS
1. Do you feel physician fees are fair and equitable for the service you received? Y N
2. Did you discuss fees/charges with your physician prior to deciding to use him/her as your primary care physician? Y N
3. Does your physician spend adequate time with you answering your questions and explaining your illness?
Y N
4. During your last visit to your physician how much time did the physician actually spend with you? A. Less that 5 minutes B. 5 to 10 minutes C. 10 to 15 minutes D. over 15 minutes
5. Were the receptionist(s) courteous to you on your last visit? Y N
6. Did you inquire into the credentials of your current physician before selecting him/her?
Y N IF YES ASK Where or how did you check their credentials?
7. Did'you ask if your physician had been tested for HIV? Y N
8. Do you know which hospital(s) your physician has staff privileges in? Y N
9. Did you check to see if your physician has any malpractice claims or convictions?
Y N IF YES ASK Where did you get the information regarding malpractice?
10. Would you like to have a central place you could call for unbiased information concerning physicians credentials, fees, recommendations or complaints from other consumers like yourself. Y N
APPENDIX B
SPSS LISTINGS
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FACTOR ANALYSIS LISTING
177
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ANOVA LISTING
196
197
ANOVA <=.05 Significant
Between .05 & 1.0 is a trend > 1.0 Not Significant
_ _ _ _ _ _ _ - O N E W A Y Variable Fl (Reputation) TRBND By Variable GENDER (Grp l=Male;Grp 2=Female) Gender of respondent
ANALYSIS OF VARIANCE
SUM OF MEAN F F SOURCE D.F, SQUARES SQUARES RATIO PROB.
BETWEEN GROUPS 1 3. .5379 3.5379 3.7395 .0541 WITHIN GROUPS 288 272, .4737 .9461 TOTAL 289 276. .0116
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 (M) 63 4.9921 .9108 .1148 2.1250 6.6250 4.7627 TO 5. 2214 Grp 2 (F) 227 5.2599 * .9890 .0656 2.1250 7.0000 5.1306 TO 5. 3893 TOTAL 290 5.2017 .9773 .0574 2.1250 7.0000 5.0888 TO 5. 3147
FIXED EFFECTS MODEL .9727 .0571 5.0893 TO 5. 3141 RANDOM EFFECTS MODEL .1435 3.3779 TO 7. 0256
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0263 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5411, P = .324 (Approx.) Bartlett-Box F = .635 , P = .426 Maximum Variance / Minimum Variance 1.179
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS.
O N E W A Y
Variable F2 (Physician Socio-Demographic) TRBND By Variable GENDER gender of respondent
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 279 280
SUM OF SQUARES
5.0020 388.8183 393.8203
MEAN SQUARES
5.0020 1.3936
F RATIO
F PROB.
3.5892 .0592
GROUP COUNT STANDARD STANDARD
MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 (M) 60 3.2146 1.0334 .1334 1.1250 Grp 2 (F) 221 3.5402 * 1.2170 .0819 1.2500 TOTAL 281 3.4706 1.1860 .0707 1.1250
FIXED EFFECTS MODEL 1.1805 .0704 RANDOM EFFECTS MODEL .1742
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5810, P = .054 (Approx.) Bartlett-Box F = 2.319 , P = .128 Maximum Variance / Minimum Variance 1.387
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS.
5.3750 6.5000 6.5000
0.0382
2.9476 TO 3.3788 TO 3.3314 TO 3.3320 TO 1.2570 TO
3.4815 3.7015 3.6099 3.6093 5.6843
O N E W A Y
Variable F3 (Economic) NOT SIGNIFICANT By Variable GENDER gender of respondent
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 279 280
SUM OF SQUARES
1.0351 346.9720 348.0071
MEAN SQUARES
1.0351 1.2436
RATIO PROB.
.8323 .3624
Grp 1(M) Grp 2(F) TOTAL
COUNT
59 222 281
MEAN
4.0145 3.8655 3.8968
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.1620 1.1026 1.1148 1.1152
STANDARD ERROR
.1513
.0740
.0665
.0665
.0665
MINIMUM
1.0000 1.1429 1.0000
MAXIMUM
5.8571 6.8571 6.8571
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0022 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5262, P = .535 (Approx.) Bartlett-Box F = .257 , P = .612 Maximum Variance / Minimum Variance 1.111
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS.
95 PCT CONF INT FOR MEAN
3.7117 TO 3.7197 TO 3.7659 TO 3.7658 TO 3.0515 TO
4.3173 4.0113 4.0277 4.0278 4.7421
198
O N E W A Y
Variable F4 (Environmental) SIGNIFICANT By Variable GENDER gender of respondent
ANALYSIS OF VARIANCE
SOURCE D.F. SUM OF SQUARES
MEAN SQUARES
F F RATIO PROB.
BETWEEN GROUPS 1 9.5222 9.5222 7. 0865 .0082 WITHIN GROUPS 294 395.0502 1.3437 TOTAL 295 404.5724
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 (M) 63 4.9921 1.1323 .1427 2.2500 7.0000 4.7069 TO 5.2772 Grp 2 (F) 233 5.4303 * 1.1663 .0764 1.0000 7.0000 5.2797 TO 5.5808 TOTAL 296 5.3370 1.1711 .0681 1.0000 7.0000 5.2030 TO 5.4710
FIXED EFFECTS MODEL 1.1592 .0674 5.2044 TO 5.4696 RANDOM EFFECTS MODEL .2437 2.2410 TO 8.4329
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0825 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5148, P = .721 (Approx.) Bartlett-Box F = .084 , P = .772 Maximum Variance / Minimum Variance 1.061
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS.
O N E W A Y
Variable F5 (Perceptuals) NOT SIGNIFICANT By Variable GENDER gender of respondent
ANALYSIS OF VARIANCE
SUM OF MEAN F F SOURCE D.F. SQUARES SQUARES RATIO PROB.
BETWEEN GROUPS 1 2.3433 2.3433 2. ,5483 .1115 WITHIN GROUPS 285 262.0696 .9195 TOTAL 286 264.41292
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 (M) 60 5.5083 .9974 .1288 3.0000 7.0000 5.2507 TO 5. 7660 Grp 2 (F) 227 5.7305 .9486 .0630 2.3333 7.0000 5.6065 TO 5. 8546 TOTAL 287 5.6841 .9615 .0568 2.3333 7.0000 5.5724 TO 5. 7958
FIXED EFFECTS MODEL .9589 .0566 5.5727 TO 5. 7955 RANDOM EFFECTS MODEL .1151 4.2218 TO 7. ,1463
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0150 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5250, P = .550 (Approx.) Bartlett-Box F = .238 , P = .626 Maximum Variance / Minimum Variance 1.105
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS.
O N E W A Y
Variable F6 (Self-Efficacy) SIGNIFICANT By Variable GENDER gender of respondent
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 287 288
SUM OF SQUARES
12.6360 286.5866 299.2226
MEAN SQUARES
12.6360 .9986
F RATIO
F PROB.
12.6542 .0004
GROUP COUNT STANDARD STANDARD
MEAN DEVIATION ERROR MINIMUM MAXIMUM
Grp 1 (M) 61 4.3852 1.0504 .1345 1.8333 Grp 2 (F) 228 4.8977 * .9853 .0653 2.6667 TOTAL 289 4.7895 1.0193 .0600 1.8333
FIXED EFFECTS MODEL .9993 .0588 RANDOM EFFECTS MODEL .2900
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5319, P = .444 (Approx.) Bartlett-Box F = .3 95 , P = .530 Maximum Variance / Minimum Variance 1.136
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - - - - -
6.6667 7.0000 7.0000
0.1209
95 PCT CONF INT FOR MEAN
4.1162 TO 4.7691 TO 4.6715 TO
4.6738 TO 1.1048 TO
4.6543 5.0262 4.9075 4.9052 8.4742
Variable F7 (Insurance) NOT SIGNIFICANT By Variable GENDER gender of respondent
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 287 288
SUM OF SQUARES
5.4982 596.3773 601.8754
MEAN SQUARES
5.4982 2.0780
RATIO PROB.
2.6459 .1049
199
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 (M) 61 5.7541 1.7263 .2210 1.0000 7.0000 5.3120 TO 6.1962 Grp 2 (F) 228 6.0921 1.3563 .0898 1.0000 7.0000 5.9151 TO 6.2691 TOTAL 289 6.0208 1.4456 .0850 1.0000 7.0000 5.8534 TO 6.1881
FIXED EFFECTS MODEL 1.4415 .0848 5.8539 TO 6.1877 RANDOM EFFECTS MODEL .1758 3.7876 TO 8.2540
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0355 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .6183, P = .004 (Approx.) Bartlett-Box F = 6.001 , P = .014 Maximum Variance / Minimum Variance 1.620
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS.
O N E W A Y
Variable F8 (Communication) SIGNIFICANT By Variable GENDER gender of respondent
ANALYSIS OF VARIANCE
SUM OF SQUARES
MEAN SQUARES RATIO PROB.
BETWEEN GROUPS 1 3.2167 3.2167 7. .2264 .0076 WITHIN GROUPS 294 130.8700 .4451 TOTAL 295 134.0867
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 (M) 64 6.3229 .7441 .0930 4.0000 7.0000 6.1370 TO 6.5088 Grp 2 (F) 232 6.5761 * .6446 .0423 3.6667 7.0000 6.4928 TO 6.6595 TOTAL 296 6.5214 .6742 .0392 3.6667 7.0000 6.4443 TO 6.5985
FIXED EFFECTS MODEL .6672 .0388 6.4451 TO 6.5977 RANDOM EFFECTS MODEL .1406 4.7350 TO 8.3078
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0276 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5713, P = .083 (Approx.) Bartlett-Box F = 2.138 , P = .144 Maximum Variance / Minimum Variance 1.332
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. O N E W A Y
Variable F9 (Technology) SIGNIFICANT By Variable GENDER gender of respondent
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 294 295
SUM OF SQUARES
6.4914 329.5442 336.0357
MEAN SQUARES
6.4914 1.1209
F RATIO
F PROB.
5.7913 .0167
GROUP COUNT STANDARD STANDARD
MEAN DEVIATION ERROR MINIMUM 95 PCT CONF INT FOR MEAN
Grp 1 (M) 64 5.5052 Grp 2 (F) 232 5.8649 * TOTAL 296 5.7872
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0535 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5130, P = .752 (Approx.) Bartlett-Box F = .068 , P = .7 95 Maximum Variance / Minimum Variance 1.054
1. .0805 .1351 2, .3333 7, .0000 5.2353 TO 5. .7751 1. ,0527 .0691 2. .0000 7, .0000 5.7288 TO 6, .0011 1. .0673 .0620 2. .0000 7. .0000 5.6651 TO 5, .9092 1. .0587 .0615 5.6661 TO 5. .9083
.1979 3.2723 TO 8. .3021
Variable F10 By Variable GENDER
Minimum Variance - - - - - - - - - - O N E W A Y (Opportunity) NOT SIGNIFICANT
gender of respondent ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 285 286
SUM OF SQUARES
1.2560 368.7889 370.0449
MEAN SQUARES
1.2560 1.2940
RATIO PROB.
.9706 .3254
Grp 1 Grp 2
3.6243
(M) (F)
COUNT
60 227
TOTAL
STANDARD STANDARD MEAN DEVIATION ERROR
3.6208 3.4581 287
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
1.0858 1.1507
3.4922
1.1375
.1402
.0764 1.1375
.0671
.0671
MINIMUM
1.2500 1.0000
.0671
MAXIMUM
6.2500 7.0000
.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0004 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5290, P = .489 (Approx.) Bartlett-Box F = .306 , P = .580 Maximum Variance / Minimum Variance 1.123
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS.
95 PCT CONF INT FOR MEAN
7.0000
3.3403 TO 3.3077 TO
3.9013 3.6086
3.3600 TO
3.3600 TO 2.6390 TO
3.6243 4.3453
200
_ _ O N E W A Y Variable F1 (Reputation) SIGNIFICANT By Variable EDUC2 (Grpl <=12 yrs; Grp 2 <=Baccalaureate; Grp3 > Baccalaureate)
ANALYSIS OF VARIANCE
SUM OF MEAN F F SOURCE D.F. SQUARES SQUARES RATIO PROB.
BETWEEN GROUPS 2 6.9958 3.4979 3. ,7347 .0250 WITHIN GROUPS 287 268.8040 .9366 TOTAL 289 275.7998
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAi
Grp 1(1,2,3) 60 5.4375 * .9463 .1222 3. .0000 7.0000 5.1931 TO 5. 6819 Grp 2(4,5) 155 5.2153 .9287 .0746 2. .5000 6.8750 5.0680 TO 5. ,3627 Grp 3 (6,7) 75 4.9817 1.0600 .1224 2, .1250 6.7500 4.7378 TO 5. 2256 TOTAL 290 5.2009 .9769 .0574 2. .1250 7.0000 5.0880 TO 5. .3138
FIXED EFFECTS MODEL .9678 .0568 5.0890 TO 5. ,3127 RANDOM EFFECTS MODEL .1216 4.6778 TO 5. 7240
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0292 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .3899, P = .232 (Approx.) Bartlett-Box F = Maximum Variance /
.931 1.303
.395 Minimum Variance
- O N E W A Y Variable F1 (Reputation) By Variable EDUC2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.48 3.48 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I)
0.6843 * RANGE * DSQRT(1/N(I) + 1/N(J)) (*) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
IS. .
Mean Group 3 2 1 4.9817 Grp 3 5.2153 Grp 2 5.4375 Grp 1 •
_ _ _ _ _ _ O N E W A Y Variable F2 (Physician Socio-Demographic) SIGNIFICANT By Variable EDUC2
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
2 277 279
SUM OF SQUARES
33.9113 358.5717 392.4830
MEAN SQUARES
16.9556 1.2945
F RATIO
F PROB.
13.0984 .0000
GROUP COUNT STANDARD
DEVIATION STANDARD
ERROR MINIMUM 95 PCT CONF INT FOR MEAN
Grp 1(1,2, 3) 61 4.0389 * 1. .1980 .1534 1. ,8750 6, .5000 3.7321 TO 4, .3458 Grp 2(4,5) 146 3.4452 1. ,1551 .0956 1. ,2500 6. .3750 3.2563 TO 3. .6341 Grp 3(6,7) 73 3.0308 1. .0474 .1226 1. .1250 5, .0000 2.7864 TO 3, .2752 TOTAL 280 3.4665 1. .1861 .0709 1. .1250 6, .5000 3.3270 TO 3, .6060
FIXED EFFECTS MODEL 1. ,1378 .0680 3.3327 TO 3, .6004 RANDOM EFFECTS : MODEL .2745 2.2855 TO 4, .6475
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .3712, P = Bartlett-Box F = Maximum Variance
.662 1.308
.517
.516
0.1826
(Approx.)
/ Minimum Variance _ _ _ _ _ O N E W A Y -Variable F2 (Physician Socio-Demographic) By Variable EDUC2 (Education) MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.48 3.48 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I)
0.8045 * RANGE * DSQRT(1/N(I) + 1/N(J)) (*) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
IS. .
Mean 3.0308 3.4452 4.0389
Variable F3 By Variable
Group Grp 3 Grp 2 Grp 1
(Economic) EDUC2
3 2 1
SIGNIFICANT O N E W A Y
ANALYSIS OF VARIANCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
2 279 281
SUM OF SQUARES
24.8507 324.7036 349.5543
MEAN SQUARES
12.4253 1.1638
RATIO PROB.
10.6764 .0000
201
GROUP C
Grp 1(1,2,3) Grp 2(4,5) Grp 3 (6,7) TOTAL
59 152 71 282
MEAN
4.4262 3.8571 3.5594 3.9012
STANDARD DEVIATION
STANDARD ERROR 95 PCT CONF INT FOR MEAN
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrane C = Max. Variance/Siim(Variances) = .3594, P =
1. .0626 .1383 2, .0000 6. .8571 4.1492 TO 4. .7031 1. .0627 .0862 1. .0000 6. .2857 3.6868 TO 4, .0275 1. .1256 .1336 1. .1429 5. .8571 3.2929 TO 3, .8258 1. .1153 .0664 1. .0000 6. .8571 3.7705 TO 4, .0320 1. .0788 .0642 3.7748 TO 4, .0277
.2385 2.8752 TO 4, .9272
Bartlett-Box F = Maximum Variance
.176 1.122
P =
0.1326
.7 61 (Approx.)
.839 Minimum Variance
_ _ _ _ _ _ _ - O N E W A Y - - - - - - - - - - - - -Variable F3 (economic) By Variable EDUC2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.48 3.48 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS..
0.7628 * RANGE * DSQRT(1/N(I) + 1/N(J)) (*) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
Mean 3.5594 3.8571 4.4262
Group Grp 3 Grp 2 Grp 1
3 2 1
Variable F4 (Environmental) By Variable EDUC2
O N E W A Y SIGNIFICANT
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
GROUP COUNT
D.F.
2 293 295
MEAN
SUM OF SQUARES
21.6644 382.9632 404.6275
STANDARD DEVIATION
MEAN SQUARES
10.8322 1.3070
RATIO PROB.
8.2876 .0003
STANDARD ERROR MINIMUM MAXIMUM
Grp 1(1,2,3) Grp 2(4,5) Grp 3 (6,7) TOTAL
64 157 75 296
1.2873 1.0867 1.1291 1.1712 1.1433
.1609
.0867
.1304
.0681
.0665
.2144
1.0000 2.7500 1.7500 1.0000
5.6641 5.4140 4.9067 5.3395
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE O N E W A Y
Variable F4 (Environmental) By Variable EDUC2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.48 3.48 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.8084 * RANGE * DSQRT(1/N(I) + 1/N(J)) (*) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
Mean Group 3 2 1 4.9067 Grp 3 5.4140 Grp 2 • 5.6641 Grp 1 *
O N E W A Y - - - - - - - - - - -Variable F5 (Perceptuals) SIGNIFICANT By Variable EDUC2
ANALYSIS OF VARIANCE
7.0000 7.0000 7.0000 7.0000
0.1059
95 PCT CONF INT FOR MEAN
5.3425 TO 5.2427 TO 4.6469 TO 5.2056 TO
5.2087 TO 4.4171 TO
5.9856 5.5853 5.1665 5.4735 5.4703 6.2619
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
2 283 285
GROUP C
Grp 1(1,2,3) Grp 2(4,5) Grp 3 (6,7) TOTAL
SUM OF SQUARES
10.3154 253.6745 263.9899
STANDARD DEVIATION
MEAN SQUARES
5.1577 .8964
RATIO PROB.
5.7539 .0036
STANDARD ERROR MINIMUM XJNT MEAN
64 5.8984 148 5.7399 74 5.3784 286 5.6818
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0484 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .4000, P = .148 (Approx.) Bartlett-Box F = 2.879 , P = .056 Maximum Variance / Minimum Variance 1.592
95 PCT CONF INT FOR MEAN
1. .0763 .1345 2. .3333 7. .0000 5.6296 TO 6. .1673 .8530 .0701 3. .0000 7, .0000 5.6013 TO 5, .8784
1. .0050 .1168 2. .6667 7. .0000 5.1455 TO 5. .6112 .9624 .0569 2. .3333 7. .0000 5.5698 TO 5, .7938 .9468 .0560 5.5716 TO 5, .7920
.1476 5.0469 TO 6, .3167
202
Variable F5 (Perceptuals) By Variable EDUC2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.48 3.48 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEIAN (J) -MEAN (I) IS..
0.6695 * RANGE * DSQRT(1/N(I) + 1/N(J)) (*) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
Mean Group 3 2 1 5.3784 Grp 3 5.7399 Grp 2 * 5.8984 Grp 1 *
- O N E W A Y Variable F6 (Self-Efficacy) NOT SIGNIFICANT By Variable EDUC2
ANALYSIS OF VARIANCE
SOURCE D.F. SUM OF
SQUARES MEAN
SQUARES F
RATIO F
PROB.
BETWEEN GROUPS WITHIN GROUPS TOTAL
2 287 289
1.2155 298.1488 299.3644
.6078
.0388 .5850 .5577
STANDARD DEVIATION
STANDARD ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1(1, ,2,3) 62 4.8925 1. ,1039 .1402 2. .1667 7, .0000 4.6121 TO 5. .1728 Grp 2(4, ,5) 154 4.7922 1. .0087 .0813 1. .8333 7. .0000 4.6316 TO 4. .9528 Grp 3(6, ,7) 74 4.7027 .9660 .1123 2. .6667 6. .6667 4.4789 TO 4. .9265 TOTAL 290 4.7908 1. ,0178 .0598 1. ,8333 7, .0000 4.6732 TO 4. .9084
FIXED EFFECTS MODEL 1. ,0192 .0599 4.6730 TO 4. .9086 RANDOM EFFECTS ! MODEL .0599 4.5333 TO 5. .0483
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0049 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .3845, P = .295 (Approx.) Bartlett-Box F = .626 , P = .535 Maximum Variance / Minimum Variance 1.306
- - _ _ - _ _ - - _ _ - O N E W A Y _ _ _ _ _ _ _ _ _ _ _ Variable F6 (Self-Efficacy) By Variable EDUC2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.48 3.48 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS..
0.7207 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
- - - - - - - - - - O N E W A Y - _ _ _ _ _ _ _ _ Variable F7 (Insurance) NOT SIGNIFICANT By Variable EDUC2
ANALYSIS OF VARIANCE
SUM OF D.F. SQUARES
MEAN SQUARES
F F RATIO PROB.
BETWEEN GROUPS 2 7 .4708 3.7354 1. 8002 .1671 WITHIN GROUPS 286 593.4427 2.0750 TOTAL 288 600.9135
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1(1,2,3) 62 6.3226 1.1842 .1504 1.0000 7.0000 6.0218 TO 6.6233 Grp 2(4,5) 153 5.9183 1.4650 .1184 1.0000 7.0000 5.6843 TO 6.1523 Grp 3(6,7) 74 5.9662 1.5775 .1834 1.0000 7.0000 5.6007 TO 6.3317 TOTAL 289 6.0173 1.4445 .0850 1.0000 7.0000 5.8501 TO 6.1845
FIXED EFFECTS MODEL 1.4405 .0847 5.8505 TO 6.1841 RANDOM EFFECTS MODEL .1208 5.4977 TO 6.5369
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0189 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum (Variances) = .4122, P = .076 (Approx.) Bartlett-Box F = 2.732 , P = .065
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ o N E W A Y - - - - - - - - - - - -Variable F7 (Insurance) By Variable EDUC2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.48 3.48 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS..
1.0186 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
203
O N E W A Y Variable F8 (Communication) NOT SIGNIFICANT By Variable EDUC2
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
2 293 295
SUM OF SQUARES
1.4450 133.1373 134.5822
MEAN SQUARES
.7225
.4544
RATIO PROB.
1.5900 .2057
GROUP
Grp 1(1,2,3) Grp 2(4,5) Grp 3 (6,7) TOTAL
COUNT
66 156 74 296
STANDARD STANDARD MEAN DEVIATION ERROR
6.3889 6.5641 6.5315 6.5169
95 PCT CONF INT FOR MEAN
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrane C = Max. Variance/Sum(Variances) = .4947, P =
8525 .1049 3. .6667 7, .0000 6.1793 TO 6. .5985 6217 .0498 4. .0000 7, .0000 6.4658 TO 6, .6624 5966 .0694 4. .6667 7, .0000 6.3933 TO 6, .6697 6754 .0393 3, .6667 7, .0000 6.4396 TO 6, .5942 6741 .0392 6.4398 TO 6, .5940
.0519 6.2936 TO 6, .7402
Bartlett-Box F = Maximum Variance
6.152 2.042 / Minimum Variance
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ o N E W A Y - - - - - - - - -Variable F8 (Communication) By Variable EDUC2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.48 3.48 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.4767 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL _ _ _ _ _ _ _ - O N E W A Y - - - - - - -Variable F9 (Technology) SIGNIFICANT By Variable EDUC2
ANALYSIS OF VARIANCE
0.0030
.000 (Approx.)
. 002
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
2 293 295
SUM OF SQUARES
13.6444 321.8136 335.4580
MEAN SQUARES
6 . 8 2 2 2 1.0983
RATIO PROB.
6.2114 .0023
GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1(1, ,2,3) 64 6.0156 * 1.0034 .1254 3.3333 7.0000 5.7650 TO 6.2663 Grp 2(4, ,5) 157 5.8684 1.0390 .0829 3.0000 7.0000 5.7046 TO 6.0322 Grp 3(6, ,7) 75 5.4356 1.1028 .1273 2.0000 7.0000 5.1818 TO 5.6893 TOTAL 296 5.7905 1.0664 .0620 2.0000 7.0000 5.6686 TO 5.9125
FIXED EFFECTS : MODEL 1.0480 .0609 5.6707 TO 5.9104 RANDOM EFFECTS ! MODEL .1693 5.0619 TO 6.5191
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .3683, P = Bartlett-Box F = Maximum Variance
.325 1.208
.550 (Approx.)
.723 Minimum Variance
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ o N E W A Y - - - - - - - - - - - - -Variable F9 (Technology) By Variable EDUC2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.48 3.48 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.7411 * RANGE * DSQRT(1/N(I) + 1/N(J)) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL (*)
Mean 5.4356 5.8684 6.0156
Group Grp 3 Grp 2 Grp 1
3 2 1
Variable F10 (Opportunity) By Variable EDUC2
- - - O N E W A Y SIGNIFICANT
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
2 285 287
SUM OF SQUARES
22.3656 351.6967 374.0623
MEAN SQUARES
11.1828 1.2340
RATIO PROB.
9.0620 .0002
204
GROUP C
Grp 1(1,2,3) Grp 2(4,5) Grp 3 (6,7) TOTAL
62 154 72 288
MEAN
4.0282 3.3766 3.3056 3.4991
STANDARD DEVIATION
STANDARD ERROR MAXIMUM 95 PCT CONF INT FOR MEAN
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .4450, P =
1. .3291 .1688 1. .0000 7. .0000 3.6907 TO 4. .3658 1. .0331 .0832 1. .5000 6, .2500 3.2122 TO 3, .5411 1. .0658 .1256 1. .2500 6. .7500 3.0551 TO 3, .5560 1. .1416 .0673 1. .0000 7. .0000 3.3667 TO 3, .6315 1. .1109 .0655 3.3703 TO 3, .6280
.2221 2.5433 TO 4, .4550
Bartlett-Box F = 3.091 , P = Maximum Variance / Minimum Variance 1.655
_ _ _ _ _ _ _ _ _ - - - - - O N E W A Y -Variable F10 (Opportunity) By Variable EDUC2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.48 3.48 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.7855 * RANGE * DSQRT(1/N(I) + 1/N(J)) (*) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
.009 (Approx.)
.046
Mean 3.3056 3.3766 4.0282
Group Grp 3 Grp 2 Grp 1
Variable F1 (Reputation) By Variable ETHNIC
3 2 1
- - - - O N E W A Y SIGNIFICANT
ethnic origin ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
4 278 282
SUM OF SQUARES
16.3258 254.1102 270.4360
MEAN SQUARES
4.0814 .9141
RATIO PROB.
4.4652 .0016
GROUP
Grp 1(Cau) Grp 2(AfAm) Grp 3(His) Grp 4 (Amlnd) Grp 5(Asian) TOTAL
COUNT STANDARD STANDARD
MEAN DEVIATION ERROR MINIMUM 95 PCT CONF INT FOR MEAN
218 5.0648 .9589 32 5.5586 1.0090 20 5.7375 .6929 6 5.6250 1.4895 7 5.6429 .6825
283 5.1943 .9793 FIXED EFFECTS MODEL .9561
RANDOM EFFECTS MODEL
0649 2. .1250 6. .8750 4.9368 TO 5, .1928 1784 2. .1250 6, .6250 5.1948 TO 5, .9224 1549 4, .5000 7. .0000 5.4132 TO 6. .0618 6081 3, .1250 7. .0000 4.0618 TO 7. .1882 2580 4. .5000 6. .6250 5.0117 TO 6. .2740 0582 2, .1250 7. .0000 5.0798 TO 5, .3089 0568 5.0825 TO 5. .3062 2719 4.4395 TO 5. .9492
0.1155 RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .4349, P = .000 (Approx.) Bartlett-Box F = Maximum Variance
1.738 4.764 Minimum Variance _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 0 N E W A
Variable F1 (Reputation) By Variable ETHNIC ethnic origin MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
4.39 4.39 4.39 4.39 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I)
0.6760 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 0 N E W A y _ _ _ _ _ _ _ _
Variable F2 (Physician Socio-Demographic) SIGNIFICANT
.139
IS.
By Variable ETHNIC ethnic origin ANALYSIS OF VARIANCE
SUM OF SQUARES
MEAN SQUARES
BETWEEN GROUPS 4 60.3294 15.0823 WITHIN GROUPS 266 316.1592 1.1886 TOTAL 270 376.4886
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR
Grp 1 211 3. .2346 1.0816 .0745 Grp 2 28 4. .3705 • 1.1214 .2119 Grp 3 20 4. .3125 • 1.0391 .2324 Grp 4 5 5. .0000 * 1.7207 .7695 Grp 5 7 3. .5357 .8345 .3154 TOTAL 271 3. .4719 1.1808 .0717
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
.0662
.5863
RATIO PROB.
12.6895 .0000
Tests for Homogeneity of Variances Cochrans C = Max. Variance/Sum(Variances) = .4133, Bartlett-Box F = .7 65 !
= .000 = .548
0.5445
(Approx.)
95 PCT CONF INT FOR MEAN
1, .1250 6, .5000 3.0878 TO 3, .3814 1, .7500 6, .3750 3.9357 TO 4, .8054 2, .3750 6. .1250 3.8262 TO 4. .7988 2. .0000 6. .2500 2.8635 TO 7. .1365 2. .1250 4, .8750 2.7639 TO 4. .3075 1. .1250 6. .5000 3.3306 TO 3, .6131
3.3415 TO 3. .6023 1.8440 TO 5. .0997
205
Maximum Variance / Minimum Variance 4.252 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ O N E W A Y - - - - - - - - - - - -Variable F2 (Physician Socio-Demographic) By Variable ETHNIC ethnic origin MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
4.39 4.39 4.39 4.39 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS..
0.7709 * RANGE * DSQRT(1/N(I) + 1/N(J)) (*) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
Mean 3.2346 3.5357 4.3125 4.3705 5.0000
Variable F3 By Variable
Group 1 5 3 2 4 Grp 1 Grp 5 Grp 3 * Grp 2 • Grp 4 *
O N E W A Y (Economic) SIGNIFICANT ETHNIC ethnic origin
ANALYSIS OF VARIANCE
D.F. SUM OF
SQUARES MEAN
SQUARES RATIO PROB.
BETWEEN GROUPS 4 31.0328 7.7582 6. 7617 .0000 WITHIN GROUPS 268 307.4966 1.1474 TOTAL 272 338.5294
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 212 3.7426 1.0622 .0730 1.0000 6.1429 3.5988 TO 3. 8864 Grp 2 30 4.6333 1.1688 .2134 1.7143 6.8571 4.1969 TO 5. 0698 Grp 3 19 4.5113 .8197 .1881 2.4286 5.8571 4.1162 TO 4. 9064 Grp 4 5 4.3143 1.4757 .6599 1.8571 5.4286 2.4821 TO 6. 1465 Grp 5 7 3.4082 1.2245 .4628 1.8571 5.7143 2.2757 TO 4. 5407 TOTAL 273 3.8959 1.1156 .0675 1.0000 6.8571 3.7629 TO 4. 0288
FIXED EFFECTS : MODEL 1.0712 .0648 3.7682 TO 4. 0235 RANDOM EFFECTS 1 MODEL .4036 2.7754 TO 5. 0164
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.2555
.3182,
.944 , 3.241
P = .005 P = .438
Tests for Homogeneity of Variances Cochrans C = Max. Variance/Sum(Variances) = Bartlett-Box F = Maximum Variance / Minimum Variance
_ _ _ _ _ _ - _ - _ _ _ _ _ _ _ 0 N E W A Y - - - - - - - - - - - - - -Variable F3 (Economic) By Variable ETHNIC ethnic origin MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
4.39 4.39 4.39 4.39 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS..
0.7574 * RANGE * DSQRT(1/N(I) + 1/N(J)) (*) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
(Approx.)
Mean Group 5 1 4 3 2 3.4082 Grp 5 3.7426 Grp 1 4.3143 Grp 4 4.5113 Grp 3 4.6333 Grp 2 * _ _ _ _ O N E W A Y
F4 (Environmental) SIGNIFICANT Variable By Variable ETHNIC ethnic origin
ANALYSIS OF VARIANCE
SUM OF SQUARES
MEAN SQUARES RATIO PROB.
BETWEEN GROUPS 4 37.1944 9.2986 7. 2940 .0000 WITHIN GROUPS 282 359.5029 1.2748 TOTAL 286 396.6973
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 220 5 .1557 1.1405 .0769 1.0000 7, .0000 5.0041 TO 5.3072 Grp 2 33 6 .2273 • 1.0258 .1786 2.2500 7 . .0000 5.8636 TO 6.5910 Grp 3 20 5 .6500 1.1511 .2574 3.0000 7, .0000 5.1113 TO 6.1887 Grp 4 6 5 .4167 1.3663 .5578 3.2500 7 .0000 3.9829 TO 6.8504 Grp 5 8 5 .8125 .9613 .3399 4.5000 7. .0000 5.0088 TO 6.6162 TOTAL 287 5 .3371 1.1777 .0695 1.0000 7. .0000 5.2003 TO 5.4739
FIXED EFFECTS ] MODEL 1.1291 .0666 5.2059 TO 5.4683 RANDOM EFFECTS 1 MODEL .4208 4.1688 TO 6.5055
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0 .2845 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .2886, P = .037 Bartlett-Box F = .326 , P = .860 Maximum Variance / Minimum Variance 2.020
(Approx.)
206
_ _ _ _ _ _ O N E W A Y Variable F4 (Environmental) By Variable ETHNIC ethnic origin MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
4.39 4.39 4.39 4.39 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.7984 * RANGE * DSQRT(1/N(I) + 1/N(J)) (*) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
Mean Group 1 4 3 5 2 5.1557 Grp 1 5.4167 Grp 4 5.6500 Grp 3 5.8125 Grp 5 6.2273 Grp 2 *
O N E W A Y (Perceptuals) NOT SIGNIFICANT Variable F5
By Variable ETHNIC ethnic origin ANALYSIS OF VARIANCE
D.F. SUM OF SQUARES
MEAN SQUARES
F RATIO
F PROB.
BETWEEN GROUPS 4 5.5498 1.3874 1. 5869 .1780 WITHIN GROUPS 272 237.8121 .8743 TOTAL 276 243.3618
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 213 5 .6291 .9409 .0645 2.6667 7, .0000 5.5020 TO 5. ,7562 Grp 2 29 5 .8678 1.0591 .1967 3.3333 7. .0000 5.4649 TO 6. ,2707 Grp 3 22 6 .0455 .6710 .1431 4.6667 7. .0000 5.7480 TO 6. .3430 Grp 4 6 6 .0833 .8740 .3568 4.8333 7 . .0000 5.1661 TO 7. ,0005 Grp 5 7 5 .5476 .9512 .3595 4.3333 7. .0000 4.6679 TO 6. ,4273 TOTAL 277 5 .6949 .9390 .0564 2.6667 7 , .0000 5.5839 TO 5. ,8060
FIXED EFFECTS MODEL .9350 .0562 5.5843 TO 5. ,8056 RANDOM EFFECTS MODEL .1214 5.3580 TO 6. ,0319
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0. .0190
.2719, 1.148 , 2.492
P = P =
Tests for Homogeneity of Variances Cochrans C = Max. Variance/Sum(Variances) = Bartlett-Box F = Maximum Variance / Minimum Variance
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ o N E W A Y - - -Variable F5 (Perceptuals) By Variable ETHNIC ethnic origin MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
4.39 4.39 4.39 4.39 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I)
0.6612 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL _ _ _ _ _ _ - _ _ - _ _ - _ _ _ 0 N E W A Y - - - - - - - -Variable F6 (Self-Efficacy) NOT SIGNIFICANT
.120 (Approx.)
.332
IS. .
By Variable ETHNIC ethnic origin ANALYSIS OF VARIANCE
D.F. SUM OF SQUARES
MEAN SQUARES RATIO PROB.
BETWEEN GROUPS 4 2.0922 .5231 5022 .7341 WITHIN GROUPS 275 286.4173 1.0415 TOTAL 279 288.5095
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 215 4 .8031 .9975 .0680 1.8333 7.0000 4.6690 TO 4.9372 Grp 2 31 4 .7258 1.2499 .2245 2.1667 7.0000 4.2674 TO 5.1843 Grp 3 21 4 .7540 .9077 .1981 3.3333 7.0000 4.3408 TO 5.1672 Grp 4 6 4 .9444 1.0470 .4275 4.1667 7.0000 3.8457 TO 6.0432 Grp 5 7 4 .2857 .8804 .3328 2.8333 5.5000 3.4715 TO 5.1000 TOTAL 280 4 .7810 1.0169 .0608 1.8333 7.0000 4.6613 TO 4.9006
FIXED EFFECTS ] MODEL 1.0205 .0610 4.6609 TO 4.9010 RANDOM EFFECTS ! MODEL .0610 4.6116 TO 4.9503
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0189 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .2974, P = .021 (Approx.) Bartlett-Box F = .917 , p - .453 Maximum Variance / Minimum Variance 2.015
- - - - - - - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - - - -Variable F6 (Self-Efficacy) By Variable ETHNIC ethnic origin MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
4.39 4.39 4.39 4.39 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS..
207
0.7216 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
O N E W A Y Variable F7 (Insurance) NOT SIGNIFICANT By Variable ETHNIC ethnic origin
ANALYSIS OF VARIANCE
SUM OF SQUARES
MEAN SQUARES RATIO PROB.
BETWEEN GROUPS 4 5.0063 1.2516 6013 .6620 WITHIN GROUPS 276 574.4866 2.0815 TOTAL 280 579.4929
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 216 5.9861 1.4753 .1004 1.0000 7.0000 5.7883 TO 6.1840 Grp 2 32 6.1563 1.6136 .2853 1.0000 7.0000 5.5745 TO 6.7380 Grp 3 21 6.2619 .8459 .1846 4.0000 7.0000 5.8769 TO 6.6469 Grp 4 5 5.5000 1.3229 .5916 3.5000 7.0000 3.8575 TO 7.1425 Grp 5 7 6.5000 .8660 .3273 5.0000 7.0000 5.6991 TO 7.3009 TOTAL 281 6.0302 1.4386 .0858 1.0000 7.0000 5.8613 TO 6.1992
FIXED EFFECTS 1 MODEL 1.4427 .0861 5.8608 TO 6.1997 RANDOM EFFECTS i MODEL .0861 5.7913 TO 6.2692
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0303 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .3256, P = .002 (Approx.) Bartlett-Box F = 2.798 , P = .025 Maximum Variance / Minimum Variance 3.639
- - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - - -Variable F7 (Insurance) By Variable ETHNIC ethnic origin MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
4.39 4.39 4.39 4.39 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
1.0202 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL - - - - - - - O N E W A Y -Variable F8 (Communication) TREND By Variable ETHNIC ethnic origin
ANALYSIS OF VARIANCE
D.F. SUM OF SQUARES
MEAN SQUARES RATIO PROB.
BETWEEN GROUPS 4 3.4832 .8708 2. 1223 .0782 WITHIN GROUPS 282 115.7076 .4103 TOTAL 286 119.1909
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 219 6.5419 (2) .6229 .0421 4.3333 7 , .0000 6.4589 TO 6. ,6248 Grp 2 32 6.5625 (3) .7402 .1309 4.3333 7, .0000 6.2956 TO 6. .8294 Grp 3 22 6.5758 (4) .4953 .1056 5.6667 7, .0000 6.3562 TO 6. .7954 Grp 4 6 6.7778 (5) .2722 .1111 6.3333 7, .0000 6.4922 TO 7. 0634 Grp 5 8 5.9167 (1) 1.1091 .3921 4.3333 7, .0000 4.9894 TO 6. 8439 TOTAL 287 6.5343 .6456 .0381 4.3333 7, .0000 6.4593 TO 6. 6093
FIXED EFFECTS ! MODEL .6406 .0378 6.4598 TO 6. 6087 RANDOM EFFECTS : MODEL .1055 6.2414 TO 6. 8272
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0, .0161 6.2414 TO 8272
Tests for Homogeneity of Variances Cochrans C = Max. Variance/Sum(Variances) = .4949,
3.602 16.607
P = P = Bartlett-Box F =
Maximum Variance / Minimum Variance - - - - - - - - - - - - - - - - O N E W A Y - - - - - - - -Variable F8 (Communication) By Variable ETHNIC ethnic origin MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
4.39 4.39 4.39 4.39 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.4529 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL - - - - - - - - - - - - - - - - O N E W A Y - - - - - - - -Variable F9 (Technology) SIGNIFICANT
. 0 0 0
. 0 0 6 (Approx.)
By Variable ETHNIC ethnic origin ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
4 282 286
SUM OF SQUARES
27.4584 301.2648 328.7232
MEAN SQUARES
6.8646 1.0683
RATIO PROB.
6.4256 .0001
208
GROUP
Grp 1 Grp 2 Grp 3 Grp 4 Grp 5 TOTAL
STANDARD STANDARD MEAN DEVIATION ERROR MINIMUM
5.6070 (1) 1.0974 .0743 2.0000 6.4747 (5) .7994 .1392 ^ 3 3 3 6.2121 (4) .5199 .1108 5.3333 6.1111 (3) 1.4402 .5879 3.6667 5.9583 (2) .7001 .2475 5.3333 5.7735 1.0721 .0633 2.0000
FIXED EFFECTS MODEL 1.0336 .0610 RANDOM EFFECTS MODEL .3515
COUNT
218 33 22 6 8
287
MAXIMUM
7.0000 7.0000 7.0000 7.0000 7.0000 7.0000
0.2006
95 PCT CONF INT FOR MEAN
5.4605 TO 6.1913 TO 5.9816 TO 4.5998 TO 5.3731 TO 5.6490 TO 5.6534 TO 4.7977 TO
5.7535 6.7582 6.4426 7.6224 6.5436 5.8981 5.8936 6.7493
KwlA/n or r EA- i 0 rawiMJ -RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances _ n o o (A -ox )
Cochrans C = Max. Variance/Sum(Variances) = .4434, P - .000 (Approx.) Bartlett-Box F = 5.194 , P = .°°° Maximum Variance / Minimum Variance 7.6/J
O N E W A Y Variable F9 (Technology) By Variable ETHNIC ethnic origin MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
4.39 4.39 4.39 4.39 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.7309 * RANGE * DSQRT(1/N(I) + 1/N(J)) (*) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
Mean 5.6070 5.9583 6.1111 6.2121 6.4747
Variable F10 By Variable
Group Grp 1 Grp 5 Grp 4 Grp 3 Grp 2
(Opportunity) ETHNIC
1 5 4 3 2
- - - O N E W A Y - - - - -SIGNIFICANT
ethnic origin ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
4 274 278
SUM OF SQUARES
15.2242 344.8201 360.0444
MEAN SQUARES
3.8061 1.2585
F RATIO
F PROB.
3.0244 .0183
GROUP COUNT
Grp 1 216 Grp 2 31 Grp 3 19 Grp 4 6 Grp 5 7 TOTAL 279
STANDARD STANDARD MEAN DEVIATION ERROR
3.3981 (1) 1.1178 .0761 4.0484 (4) 1.1840 .2126 3.5921 (2) 1.0145 .2327 4.2500 (5) 1.2550 .5123 3.6429 (3) 1.1352 .4291 3.5081 1.1380 .0681
FIXED EFFECTS MODEL 1.1218 .0672 RANDOM EFFECTS MODEL .2519
MINIMUM
1.2500 2.5000 1.0000 2.2500 2.2500 1.0000
MAXIMUM
7.0000 6.7500 5.0000 6.0000 5.5000 7.0000
95 PCT CONF INT FOR MEAN
3.2482 TO 3.6141 TO 3.1031 TO 2.9330 TO 2.5930 TO 3.3739 TO 3.3758 TO 2.8086 TO
3.5481 4.4827 4.0811 5.5670 4.6927 3.6422 3.6403 4.2075
.596
.959 (Approx.)
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .2407, P = Bartlett-Box F = -160 , P = Maximum Variance / Minimum Variance 1.530
_ _ _ _ _ - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - -Variable F10 (Opportunity) By Variable ETHNIC ethnic origin MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
4.39 4.39 4.39 4.39 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.7932 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL _ _ _ _ _ _ _ _ - - - - - - - - - - O N E W A Y - - - - - - - - - - - - -Variable F1 (Reputation) NOT SIGNIFICANT By Variable INCOME2 (Grpl =< 15K; Grp2 15K-30K; Grp3 30K-50K; Grp4 >50K)
ANALYSIS OF VARIANCE
0.0955
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
GROUP COUNT
D.F.
3 283 286
MEAN
SUM OF SQUARES
1.9904 271.4614 273 .4518
MEAN SQUARES
.6635
.9592
RATIO PROB.
.6917 .5578
STANDARD STANDARD
Grp 1(1,2,3) 64 5.2090 Grp 2(4,5) 65 5.2077 Grp 3(6,7) 90 5.2792 Grp 4 (8) 68 5.0551 TOTAL 287 5.1943
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE
DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
1.0963 .1370 2.1250 7.0000 4.9351 TO 5.4828 .9993 .1240 3.0000 6.7500 4.9601 TO 5.4553 .9805 .1034 2.1250 6.8750 5.0738 TO 5.4845 . 8309 .1008 3.1250 6.6250 4.8540 TO 5.2563 .9778 .0577 2.1250 7.0000 5.0806 TO 5.3079 .9794 .0578 5.0805 TO 5.3080 .9794
.0578 5.0103 TO 5.3782
209
IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE
Tests for Homogeneity of Variances Cochrane C = Max. Variance/Sum(Variances) = .3120, P = .195 (Approx.) Bartlett-Box F = Maximum Variance
1.669 1.741
P = .172 Minimum Variance2 _ _ _ _ _ _ O N E W A Y
Variable F1 (Reputation) By Variable INCOME2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I)
0.6925 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
- O N E W A Y -Variable F2 (Physician Socio-Demographic) SIGNIFICANT By Variable INCOME2
ANALYSIS OF VARIANCE
IS.
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
3 273 276
SUM OF SQUARES
15.7744 372.0654 387.8398
MEAN SQUARES
5.2581 1.3629
RATIO PROB.
3.8581 .0099
STANDARD STANDARD GROUP COUNT MEAN
Grp 1(1,2,3) 63 3.8175 Grp 2(4,5) 62 3.4899 Grp 3 (6,7) 88 3.4688 Grp 4(8) 64 3.1133 TOTAL 277 3.4707
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
(4) 1.3355 .1683 1.2500 6.3750 3.4811 TO 4.1538 (3) 1.1881 .1509 1.2500 6.5000 3.1882 TO 3.7916 (2) 1.1710 .1248 1.3750 6.0000 3.2206 TO 3.7169 (1) .9435 .1179 1.1250 4.7500 2.8776 TO 3.3490 (1)
1.1854 .0712 1.1250 6.5000 3.3305 TO 3.6109 1.1674 .0701 3.3326 TO 3.6088
.1395 3.0269 TO 3.9145
.094 (Approx.) .060
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .3269, P = Bartlett-Box F = 2.478 , P : Maximum Variance / Minimum Variance 2.004
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ O N E W A Y - - - - - - - - - - - -Variable F2 (Physician Socio-Demographic) By Variable INCOME2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL ~
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.8255 * RANGE * DSQRT(1/N(I) + 1/N(J)) (*) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
0.0567
Mean 3.1133 3.4688 3.4899 3.8175
Variable F3 By Variable
Group Grp 4 Grp 3 Grp 2 Grp 1
(Economic) INCOME2
4 3 2 1
- - - - O N E W A Y SIGNIFICANT
ANALYSIS OF VARIANCE
SUM OF MEAN F F SOURCE D.F. SQUARES SQUARES RATIO PROB.
BETWEEN GROUPS 3 40.3183 13.4394 12. 0363 .0000 WITHIN GROUPS 275 307.0590 1.1166 TOTAL 278 347.3772
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 66 4.1905 (3) 1.0155 .1250 2.2857 6.2857 3.9408 TO 4. 4401 Grp 2 63 4.2540 (4) 1.1273 .1420 2.0000 6.8571 3.9701 TO 4. 5379 Grp 3 86 3.8953 (2) 1.0736 .1158 1.0000 5.8571 3.6652 TO 4. 1255 Grp 4 64 3.2522 (1) 1.0020 .1253 1.1429 5.5714 3.0019 TO 3. 5025 TOTAL 279 3.8986 1.1178 .0669 1.0000 6.8571 3.7669 TO 4. 0304
FIXED EFFECTS : MODEL 1.0567 .0633 3.7741 TO 4. 0232 RANDOM EFFECTS : MODEL .2219 3.1923 TO 4. 6049
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.1778 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) Bartlett-Box F = Maximum Variance / Minimum Variance
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ O N E W A Y -Variable F3 (Economic) By Variable INCOME2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES.
= .2850, .374 ,
1.266
= .680 = .772
(Approx.)
THE VALUE ACTUALLY COMPARED WITH MEAN (J) -MEAN (I) IS.. 0.7472 * RANGE * DSQRT(1/N(I) + 1/N(J))
(*) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
210
Mean 3.2522 3.8953 4.1905 4.2540
Group Grp 4 Grp 3 Grp 1 Grp 2
4 3 1 2
Variable F4 By Variable
(Environmental) INCOME2
- - - - O N E W A Y SIGNIFICANT
ANALYSIS OF VARIANCE
SOURCE D.F. SUM OF
SQUARES MEAN
SQUARES F
RATIO F
PROB.
BETWEEN GROUPS 3 16.1396 5.3799 4. 0321 .0078 WITHIN GROUPS 289 385.6023 1.3343 TOTAL 292 401.7419
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1(1,2,3) 70 5.6179 (4) 1.2852 .1536 2.2500 7, .0000 5.3114 TO 5. ,9243 Grp 2(4,5) 64 5.2070 (2) 1.2195 .1524 1.0000 7. .0000 4.9024 TO 5. .5117 Grp 3 (6,7) 91 5.4643 (3) 1.0604 .1112 3.5000 7, .0000 5.2435 TO 5. .6851 Grp 4(8) 68 4.9926 (1) 1.0703 .1298 1.7500 7. .0000 4.7336 TO 5. .2517 TOTAL 293 5.3353 1.1730 .0685 1.0000 7, .0000 5.2005 TO 5. .4702
FIXED EFFECTS ! MODEL 1.1551 .0675 5.2025 TO 5. 4681 RANDOM EFFECTS : MODEL .1369 4.8997 TO 5. 7710
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0. .0556
.3054, P = 1.346 , P = 1.469
Tests for Homogeneity of Variances Cochrane C = Max. Variance/Sum(Variances) = Bartlett-Box F = Maximum Variance / Minimum Variance
- - - - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - - -Variable F4 (Environmental) By Variable INCOME2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS..
0.8168 * RANGE * DSQRT(1/N(I) + 1/N(J)) (*) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
.268 (Approx.)
.258
Mean Group 4 2 3 1 4.9926 Grp 4 5.2070 Grp 2 5.4643 Grp 3 5.6179 Grp 1 *
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ - - O N E W A Y - - - -Variable F5 (Perceptuals) SIGNIFICANT By Variable INCOME2
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
3 279 282
SUM OF SQUARES
7.9444 254.9203 262.8647
MEAN SQUARES
2.6481 .9137
RATIO PROB.
2.8983 .0355
GROUP
Grp 1(1,2,3) Grp 2(4,5) Grp 3 (6,7) Grp 4(8) TOTAL
COUNT MEAN STANDARD
DEVIATION
68 5.8186 62 5.6747 89 5.7903 64 5.3854
283 5.6802 FIXED EFFECTS MODEL
RANDOM EFFECTS MODEL
(4) ( 2 ) (3) (1)
1.0877 .9440 .8731 .9277 .9655 .9559
STANDARD ERROR 95 PCT CONF INT FOR MEAN
1319 2. .3333 7 , .0000 5.5554 TO 6, .0819 1199 2. .6667 7 , .0000 5.4350 TO 5. .9145 0925 3. .0000 7. .0000 5.6063 TO 5. .9742 1160 3. .0000 6. .8333 5.1537 TO 5. .6171 0574 2. .3333 7. .0000 5.5672 TO 5, .7932 0568 5.5684 TO 5. .7921 0977 5.3693 TO 5. .9912
Tests for Homogeneity of Variances Cochrans C = Max. Variance/Sum(Variances) = .3200, P = Bartlett-Box F = 1.302 , P = Maximum Variance / Minimum Variance 1.552
_ _ _ _ _ _ _ _ _ _ O N E W A Y - - - - -Variable F5 (Perceptuals) By Variable INCOME2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS..
0.6759 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
.130
.272
0.0247
(Approx.)
211
- - - - - O N E W A Y -Variable F6 (Self-Efficacy) NOT SIGNIFICANT By Variable INCOME2
ANALYSIS OF VARIANCE
SOURCE D.F. SUM OF SQUARES
MEAN SQUARES RATIO PROB.
BETWEEN GROUPS 3 1.1855 .3952 3809 .7668 WITHIN GROUPS 283 293.5650 1.0373 TOTAL 286 294.7505
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF
Grp 1(1,2,3) 69 4.8309 1.1251 .1355 2.1667 7. .0000 4.5606 TO Grp 2(4,5) 63 4.8095 1.0177 .1282 2.8333 7, .0000 4.5532 TO Grp 3 (6,7) 89 4.6873 .9431 .1000 1.8333 7, .0000 4.4886 TO Grp 4(8) 66 4.8333 1.0000 .1231 2.5000 7, .0000 4.5875 TO TOTAL 287 4.7822 1.0152 .0599 1.8333 7, .0000 4.6643 TO
FIXED EFFECTS MODEL 1.0185 .0601 4.6639 TO RANDOM EFFECTS MODEL .0601 4.5909 TO
.3021, P
.820 , P 1.423
.320 (Approx.)
.483
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0090 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum (Variances) = Bartlett-Box F = Maximum Variance / Minimum Variance
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Q N E W A Y - - - - -Variable F6 (Self-Efficacy) By Variable INCOME2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.7202 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL _ _ _ _ _ _ _ - - - - - - - - - - O N E W A Y - - - - - - -Variable F7 (Insurance) NOT SIGNIFICANT By Variable INCOME2
ANALYSIS OF VARIANCE
5.1012 5.0658 4.8859 5.0792 4.9002 4.9006 4.9736
SOURCE D.F. SUM OF SQUARES
MEAN SQUARES
F RATIO
F PROB.
BETWEEN GROUPS WITHIN GROUPS TOTAL
3 282 285
9.4984 587.8757 597.3741
3.1661 2.0847
1.5188 .2098
GROUP
Grp 1(1,2,3) Grp 2(4,5) Grp 3 (6,7) Grp 4(8) TOTAL
COUNT MEAN STANDARD DEVIATION
STANDARD ERROR MAXIMUM 95 PCT CONF INT FOR MEAN
67 6.0224 65 6.1538 89 6.1573 65 5.7000 286 6.0210
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
1. .3636 .1666 1. .0000 7. .0000 5.6898 TO 6, .3550 1, .2117 .1503 2. .5000 7. .0000 5.8536 TO 6, .4541 1. .4013 .1485 1. ,0000 7, .0000 5.8621 TO 6, .4525 1. .7607 .2184 1. ,0000 7, .0000 5.2637 TO 6, .1363 1, .4478 .0856 1. ,0000 7. .0000 5.8525 TO 6, .1895 1. .4438 .0854 5.8529 TO 6, .1890
.1057 5.6846 TO 6, .3574 0.0152 RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE
Tests for Homogeneity of Variances Cochrans C = Max. Variance/Sum(Variances) = .3694, P = .004 (Approx.) Bartlett-Box F = 3.266 , P = .021 Maximum Variance / Minimum Variance 2.112
- - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - -Variable F7 (Insurance) By Variable INCOME2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
1.0209 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
_ _ _ _ _ _ _ O N E W A Y Variable F8 (Communication) NOT SIGNIFICANT By Variable INCOME2
ANALYSIS OF VARIANCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
3 289 292
SUM OF SQUARES
1.4354 133 .0682 134.5036
MEAN SQUARES
.4785
.4604
F RATIO
F PROB.
1.0391 .3756
212
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1(1, 2,3) 71 6.4742 .8389 .0996 3.6667 7.0000 6.2756 TO 6.6727 Grp 2(4, 5) 64 6.5885 .5931 .0741 4.6667 7.0000 6.4404 TO 6.7367 Grp 3(6, 7) 90 6.5741 .6222 .0656 4.0000 7.0000 6.4438 TO 6.7044 Grp 4(8) 68 6.4167 .6371 .0773 4.6667 7.0000 6.2625 TO 6.5709 TOTAL 293 6.5165 .6787 .0396 3.6667 7.0000 6.4385 TO 6.5945
FIXED EFFECTS ! MODEL .6786 .0396 6.4385 TO 6.5945 RANDOM EFFECTS ! MODEL .0404 6.3878 TO 6.6452
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .3 807, P = Bartlett-Box F = 3.697 , P = Maximum Variance / Minimum Variance 2.000 - - _ _ O N E W A Y - - - - - -
Variable F8 (Communication) By Variable INCOME2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.4798 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL - - - - - - - - - - - - - - - - - O N E W A Y - - - - - - - -Variable F9 (Technology) SIGNIFICANT By Variable INCOME2
ANALYSIS OF VARIANCE
0.0002
.002 (Approx.)
.011
SOURCE D.F. SUM OF SQUARES
MEAN SQUARES
F RATIO
F PROB.
BETWEEN GROUPS WITHIN GROUPS TOTAL
3 289 292
9.6432 325.7114 335.3546
3.2144 1.1270
2.8521 .0376
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1(1,2,3) 70 5.9048 (3) 1.1577 .1384 2.3333 7. .0000 5.6287 TO 6. 1808 Grp 2(4,5) 65 5.8256 (2) 1.0054 .1247 3.3333 7. .0000 5.5765 TO 6. 0748 Grp 3 (6,7) 90 5.9185 (4) 1.0353 .1091 3.0000 7. .0000 5.7017 TO 6. 1354 Grp 4(8) 68 5.4657 (1) 1.0448 .1267 2.0000 7. .0000 5.2128 TO 5. 7186 TOTAL 293 5.7895 1.0717 .0626 2.0000 7. .0000 5.6663 TO 5. 9128
FIXED EFFECTS ; MODEL 1.0616 .0620 5.6675 TO 5. 9116 RANDOM EFFECTS ! MODEL .1056 5.4536 TO 6. 1255
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0, .0287 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = Bartlett-Box F = Maximum Variance
.2969,
.533 , 1.326
P = P =
A Y Minimum Variance
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ O N E W Variable F9 (Technology) By Variable INCOME2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I)
0.7507 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL - - - - - - _ - - _ - _ _ - _ _ o N E W A Y - - - - - - - -Variable F10 (Opportunity) SIGNIFICANT By Variable INCOME2
ANALYSIS OF VARIANCE
.400
.660 (Approx.)
IS. .
SOURCE D.F. SUM OF
SQUARES MEAN
SQUARES F
RATIO F
PROB.
BETWEEN GROUPS WITHIN GROUPS TOTAL
3 281 284
14.8549 357.3916 372.2465
4.9516 1.2719
3.8932 .0095
GROUP COUNT STANDARD DEVIATION
STANDARD ERROR MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1(1, 2,3) 68 3.8493 (4) 1. .3088 .1587 1. .0000 7. .0000 3.5325 TO 4. .1661 Grp 2(4, 5) 64 3.5664 (3) 1, .0628 .1328 1. .2500 6, .7500 3.3009 TO 3. .8319 Grp 3(6, 7) 88 3.4091 (2) 1, .0974 .1170 1. .2500 6, .0000 3.1766 TO 3. .6416 Grp 4(8) 65 3.2077 (1) 1. .0208 .1266 1. .5000 6. .7500 2.9547 TO 3. .4606 TOTAL 285 3.5035 1. .1449 .0678 1. .0000 7. .0000 3.3700 TO 3. .6370
FIXED EFFECTS : MODEL 1. .1278 .0668 3.3720 TO 3. .6350 RANDOM EFFECTS : MODEL .1330 3.0801 TO 3. .9269
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0520 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .3366, P = .049 (Approx.) Bartlett-Box F = 1.667 , P = .172
213
_ _ _ _ _ _ _ O N E W A Y - - _ _ _ _ _ _ _ Variable F10 (Opportunity) By Variable INCOME2 MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS..
0.7975 * RANGE * DSQRT(1/N(I) + 1/N(J)) (*) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
Mean 3.2077 3.4091 3.5664 3.8493
Variable F1 By Variable
Group 4 3 2 1 Grp 4 Grp 3 Grp 2 Grp 1 •
O N E W A Y - - -(Reputation) SIGNIFICANT LRES2 (Grpl =< 2yrs; Grp2 > 2 yrs)
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 289 290
SUM OF SQUARES
3.8388 272.2615 276.1003
MEAN SQUARES
3.8388 .9421
RATIO PROB.
4.0748 .0445
GROUP
Grp 1(1,2,3) Grp 2(4) TOTAL
COUNT
108 183 291
MEAN
5.0532 5.2910 5.2027
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.0251 .9371 .9757 .9706
STANDARD ERROR
.0986
.0693
.0572
.0569
.1209
MINIMUM
2.1250 2.1250 2.1250
MAXIMUM
7.0000 7.0000 7.0000
95 PCT CONF INT FOR MEAN
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0213 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5448, P = .281 (Approx.) Bartlett-Box F = 1.098 , P = .295 Maximum Variance / Minimum Variance 1.4197
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. O N E W A Y
Variable F2 (Physician Socio-Demographic) NOT SIGNIFICANT By Variable LRES2
ANALYSIS OF VARIANCE
4.8577 TO 5.1543 TO 5.0902 TO 5.0908 TO 3.6670 TO
5.2488 5.4277 5.3153 5.3147 6.7385
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 279 280
SUM OF SQUARES
.0471 393.7732 393.8203
MEAN SQUARES
.0471 1.4114
F F RATIO PROB.
.0334 .8552
GROUP
Grp 1(1,2,3) Grp 2(4) TOTAL
COUNT
106 175 281
MEAN
3.4540 3.4807 3.4706
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.2011 1 . 1 8 0 0 1.1860 1.1880
STANDARD ERROR
.1167
.0892
.0707
.0709
.0709
MINIMUM
1.2500 1.1250 1.1250
MAXIMUM
6.5000 6.2500 6.5000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0103 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5088, P = .834 (Approx.) Bartlett-Box F = .041 , p = .840 Maximum Variance / Minimum Variance 1.036
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. - - - - - - - - - - O N E W A Y
Variable F3 (Economic) NOT SIGNIFICANT By Variable LRES2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
3.2227 TO 3.3047 TO 3.3314 TO 3.3311 TO 2.5701 TO
3.6853 3.6568 3.6099 3.6102 4.3711
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 280 281
SUM OF SQUARES
.6768 348.8775 349.5543
MEAN SQUARES
.6768 1.2460
RATIO PROB.
.5432 .4617
GROUP C
Grp 1(1,2,3) Grp 2(4) TOTAL
111 171 282
MEAN
3.8404 3.9407 3.9012
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.0896 1.1331 1.1153 1.1162
STANDARD ERROR
.1034
.0867
.0664
.0665 .0665
1.1429 1.0000 1.0000
MAXIMUM
6.2857 6.8571 6.8571
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0042 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5196, P = .644 (Approx
95 PCT CONF INT FOR MEAN
3.6355 TO 3.7696 TO 3.7705 TO 3.7704 TO 3.0566 TO
4.0454 4.1117 4.0320 4.0321 4.7458
.)
214
Bartlett-Box F = .203 , P = .653 Maximum Variance / Minimum Variance 1.081
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. - - - - O N E W A Y _ _ _ _ _ _ _ _
Variable F4 (Environmental) NOT SIGNIFICANT By Variable LRES2
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 295 296
SUM OF SQUARES
.0281 404.7144 404.7424
MEAN SQUARES
.0281 1.3719
RATIO PROB.
.0204 .8864
GROUP MEAN STANDARD DEVIATION
STANDARD ERROR MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1(1,2,3) Grp 2(4) TOTAL
112 185 297
5.3259 5.3459 5.3384
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
1.2075 1.1489 1.1693 1.1713
.1141
.0845
.0679
.0680
.0680
1.0000 1.7500 1.0000
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0096 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5249, P = .545 (Approx.) Bartlett-Box F = .345 , P = .557 Maximum Variance / Minimum Variance 1.105
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ _ O N E W A Y -
Variable F5 (Perceptuals) NOT SIGNIFICANT By Variable LRES2
ANALYSIS OF VARIANCE
5.0998 TO 5.1793 TO 5.2048 TO 5.2046 TO 4.4748 TO
5.5520 5.5126 5.4719 5.4721 6.2020
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 285 286
SUM OF SQUARES
.3288 264.0841 264.4129
MEAN SQUARES
.3288
.9266
RATIO PROB.
.3549 .5518
GROUP MEAN STANDARD DEVIATION
STANDARD ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1(1,2,3) Grp 2(4) TOTAL
107 180 287
5.6402 5.7102 5.6841
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
.9861
.9484
.9615
.9626
.0953
.0707
.0568
.0568
.0568
2.3333 3.0000 2.3333
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0045 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5194, P = .643 (Approx.) Bartlett-Box F = .202 , P = .653 Maximum Variance / Minimum Variance 1.081
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ o N E W A Y - - - - - - - - - - - - - - -Variable F6 (Self-Efficacy) NOT SIGNIFICANT By Variable LRES2
ANALYSIS OF VARIANCE
5.4512 TO 5.5707 TO 5.5724 TO 5.5722 TO 4.9621 TO
5.8292 5.8497 5.7958 5.7959 6.4061
SOURCE D.F. SUM OF
SQUARES MEAN
SQUARES F
RATIO F
PROB.
BETWEEN GROUPS WITHIN GROUPS TOTAL
1 288 289
.2469 299.1175 299.3644
.2469 1.0386
.2377 .6262
GROUP
Grp 1(1,2,3) Grp 2(4) TOTAL
COUNT
111 179 290
MEAN
4.7538 4.8138 4.7908
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
.9969 1.0326 1.0178 1.0191
STANDARD ERROR
.0946
.0772
.0598
.0598
.0598
MINIMUM
2.8333 1.8333 1.8333
MAXIMUM
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0058 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5176, P = .674 (Approx.) Bartlett-Box F = .166 , P = .683 Maximum Variance / Minimum Variance 1.073
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS.
95 PCT CONF INT FOR MEAN
4.5662 TO 4.6615 TO 4.6732 TO 4.6730 TO 4.0304 TO
4.9413 4.9661 4.9084 4.9086 5.5512
215
_ _ _ _ _ _ _ _ _ O N E W A Y - -Variable F7 (Insurance) NOT SIGNIFICANT By Variable LRES2
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 288 289
SUM OF SQUARES
1.3988 600.4770 601.8759
MEAN SQUARES
1.3988 2.0850
RATIO PROB.
.6709 .4134
GROUP COUNT MEAN STANDARD DEVIATION
STANDARD ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1(1,2,3) Grp 2(4) TOTAL
109 181 290
5.9312 6.0746 6.0207
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
1.4312 1.4515 1.4431 1.4439
.1371
.1079
.0847
.0848
.0848
1.0000 1.0000 1.0000
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0050 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5070, P = .866 (Approx.) Bartlett-Box F = .027 , P = .871 Maximum Variance / Minimum Variance 1.029
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. ONEWAY
Variable F8 (Communication) NOT SIGNIFICANT By Variable LRES2
ANALYSIS OF VARIANCE
5.6595 TO 5.8617 TO 5.8539 TO 5.8538 TO 4.9433 TO
6.2029 6.2875 6.1875 6.1876 7.0981
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 295 296
SUM OF SQUARES
.0362 134.7786 134.8148
MEAN SQUARES
.0362
.4569
RATIO PROB.
.0793 .7784
GROUP C
Grp 1(1,2,3) Grp 2(4) TOTAL
113 184 297
MEAN
6.5044 6.5272 6.5185
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
.7156
.6504
.6749
.6759
STANDARD ERROR
.0673
.0480
.0392
.0392
.0392
3.6667 4.0000 3.6667
MAXIMUM
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0030 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5476, P = .246 (Approx.) Bartlett-Box F = 1.281 , P = .258 Maximum Variance / Minimum Variance 1.211
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. ONEWAY
Variable F9 (Technology) NOT SIGNIFICANT By Variable LRES2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
6.3710 TO 6.4326 TO 6.4415 TO 6.4413 TO 6.0202 TO
6.6378 6.6218 6.5956 6.5957 7.0169
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 295 296
SUM OF SQUARES
.0082 336.0726 336.0808
MEAN SQUARES
.0082 1.1392
RATIO PROB.
.0072 .9323
GROUP MEAN STANDARD
DEVIATION STANDARD
ERROR MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1(1,2,3) Grp 2(4) TOTAL
112 185 297
5.7946 5.7838 5.7879
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
1.0703 1.0655 1.0656 1.0673
.1011
.0783
.0618
.0619
.0619
2.0000 3.0000 2.0000
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0081 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5023, P = .956 (Approx.) Bartlett-Box F = .003 , P = .958 Maximum Variance / Minimum Variance 1.009
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ O N E W A Y - - - - - - - - - - - - - - - - - -Variable F10 (Opportunity) NOT SIGNIFICANT By Variable LRES2
ANALYSIS OF VARIANCE
5.5942 TO 5.6292 TO 5.6662 TO 5.6660 TO 5.0009 TO
5.9951 5.9383 5.9096 5.9098 6.5748
BETWEEN GROUPS WITHIN GROUPS TOTAL
1 286 287
SUM OF SQUARES
.3796 373.6827 374.0623
MEAN SQUARES
.3796 1.3066
F RATIO
F PROB.
216
GROUP C
Grp 1(1,2,3) Grp 2(4) TOTAL
112 176 288
MEAN
3.5446 3.4702 3.4991
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.1322 1.1499 1.1416 1.1431
STANDARD ERROR
.1070
.0867
.0673
.0674
.0674
1.0000 1.5000 1.0000
MAXIMUM
6.2500 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0068 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5078, P = .853 (Approx.) Bartlett-Box F = .033 , P = .856 Maximum Variance / Minimum Variance 1.032
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ _ _ _ - - O N E W A Y _ _ _ _ _ _ _ _ Variable F1 (Reputation) NOT SIGNIFICANT By Variable PAID3 (Grpl=No Insurance; Grp2 Insurance)
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
3.3327 TO 3.2991 TO 3.3667 TO 3.3666 TO 2.6433 TO
3.7566 3.6412 3.6315 3.6317 4.3550
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 288 289
SUM OF SQUARES
.2165 275.0304 275.2468
MEAN SQUARES
.2165
.9550
RATIO PROB.
.2267 .6344
GROUP
Grp l(NOINS) Grp 2(INS) TOTAL
COUNT
62 228 290
MEAN
5.1472 5.2138 5.1996
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
. 9092
.9947
.9759
. 9772
STANDARD ERROR
.1155
.0659
.0573
.0574
.0574
2.1250 2.1250 2.1250
MAXIMUM
6.7500 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0076 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5448, P = .282 (Approx.) Bart21ett-Box F = .746 , P = .388 Maximum Variance / Minimum Variance 1.197
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. O N E W A Y -
Variable F2 (Physician Socio-Demographic) NOT SIGNIFICANT By Variable PAID3
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
4.9163 TO 5.0840 TO 5.0868 TO 5.0866 TO 4.4704 TO
5.3781 5.3436 5.3124 5.3125 5.9287
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 279 280
SUM OF SQUARES
1.8492 391.9711 393.8203
MEAN SQUARES
1.8492 1.4049
F RATIO
F PROB.
1.3162 .2523
GROUP
Grp l(NOINS) Grp 2(INS) TOTAL
COUNT
56 225 281
MEAN
3.3080 3.5111 3.4706
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.1384 1.1965 1.1860 1.1853
STANDARD ERROR
.1521
.0798
.0707
.0707
.0915
MINIMUM
1.2500 1.1250 1.1250
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5249, P = Bartlett-Box F = .213 , P = Maximum Variance / Minimum Variance 1.105
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. O N E W A Y
Variable F3 (Economic) NOT SIGNIFICANT By Variable PAID3
ANALYSIS OF VARIANCE
.557
.644
MAXIMUM
6.5000 6.3750 6.5000
0.0050
(Approx.)
95 PCT CONF INT FOR MEAN
3.0032 TO 3.3539 TO 3.3314 TO 3.3315 TO 2.3080 TO
3.6129 3.6683 3.6099 3.6098 4.6333
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
GROUP COU
Grp l(NOINS) Grp 2(INS) TOTAL
58 224 282
D.F.
1 280 281
MEAN
3.9877 3.8788 3.9012
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
SUM OF SQUARES
.5459 349.0083 349.5543 STANDARD
DEVIATION
1.0825 1.1250 1.1153 1.1164
MEAN SQUARES
.5459 1.2465
STANDARD ERROR
.1421
.0752
.0664
.0665
.0665
F F RATIO PROB.
.4380 .5086
MAXIMUM
1.7143 1.0000 1.0000
6.0000 6.8571 6.8571
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0076 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5193, P = .649 (Approx.) Bartlett-Box F = .132 , P = .716 Maximum Variance / Minimum Variance 1.080
95 PCT CONF INT FOR MEAN
3.7031 TO 3.7307 TO 3.7705 TO 3.7703 TO 3.0565 TO
4.2723 4.0270 4.0320 4.0321 4.7460
217
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. - - O N E W A Y
Variable F4 (Environmental) TREND By Variable PAID3
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 294 295
SUM OF SQUARES
4.2689 399.2850 403.5538
MEAN SQUARES
4.2689 1.3581
F RATIO
F PROB.
3.1432 .0773
GROUP COUNT MEAN STANDARD
DEVIATION STANDARD
ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp l(NOINS) Grp 2(INS) TOTAL
7.0000 7.0000 7.0000
0.0293
63 5.1111 1.2377 .1559 1.7500 233 5.4045 • 1.1453 .0750 1.0000 296 5.3421 1.1696 .0680 1.0000
FIXED EFFECTS MODEL 1.1654 .0677 RANDOM EFFECTS MODEL .1552
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5387, P = .348 (Approx.) Bartlett-Box F = .603 , P = .438 Maximum Variance / Minimum Variance 1.168
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. ONEWAY
Variable F5 (Perceptuals) SIGNIFICANT By Variable PAID3
ANALYSIS OF VARIANCE
4.7994 TO 5.2567 TO 5.2083 TO 5.2088 TO 3.3694 TO
5.4228 5.5523 5.4759 5.4754 7.3147
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 284 285
SUM OF SQUARES
4.2425 259.9367 264.1792
MEAN SQUARES
4.2425 .9153
F RATIO
F PROB.
4.6352 .0322
GROUP COUNT
Grp l(NOINS) Grp 2(INS) TOTAL
59 227 286
MEAN STANDARD
DEVIATION STANDARD
ERROR MINIMUM
1 .0666 .9264 .9628 .9567
.1389
.0615
.0569
.0566
.1646
2.6667 2.3333 2.3333
MAXIMUM
7.0000 7.0000 7.0000
5.4435 5.7445 5.6824
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(^Variances) = .5700, P = .094 (Approx.) - - - - - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - - - - - -Variable F6 (Self-Efficacy) NOT SIGNIFICANT By Variable PAID3
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
5.1656 TO 5.6233 TO 5.5703 TO
5.5710 TO 3.5910 TO
5.7215 5.8657 5.7945 5.7938 7.7738
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 287 288
SUM OF SQUARES
.5421 297.9023 298.4444
MEAN SQUARES
.5421 1.0380
RATIO PROB.
.5223 .4705
GROUP C
Grp l(NOINS) Grp 2(INS) TOTAL
61 228 289
MEAN
4.7104 4.8165 .7941
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
.8985 1.0483 1.0180 1.0188
STANDARD ERROR
.1150
.0694
.0599
.0599
.0599
MINIMUM
2.1667 1.8333 1.8333
MAXIMUM
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0052 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5765, P = .065 (Approx.) Bartlett-Box F = 2.110 , P = .146 Maximum Variance / Minimum Variance 1.361
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. - - - - - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - - - - - -Variable F7 (Insurance) SIGNIFICANT By Variable PAID3
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
4.4803 TO 4.6797 TO 4.6763 TO 4.6762 TO 4.0326 TO
4.9405 4.9533 4.9120 4.9121 5.5556
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
1 287 288
SUM OF SQUARES
56.0938 545.5515 601.6453
MEAN SQUARES
56.0938 1.9009
F RATIO
F PROB.
29.5095 .0000
218
GROUP C
Grp l(NOINS) Grp 2(INS) TOTAL
60 229 289
MEAN
5.1583 6.2445 6.0190
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.7284 1.2727 1.4454 1.3787
STANDARD ERROR
.2231
.0841
.0850
.0811
.6237
1.0000 1.0000 1.0000
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .6484, P = Bartlett-Box F = 9.762 , P = Maximum Variance / Minimum Variance 1.844
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ __ _ _ __ - - O N E W A Y
Variable F8 (Communication) NOT SIGNIFICANT
MAXIMUM
7.0000 7.0000 7.0000
0.5699
95 PCT CONF INT FOR MEAN
4.7119 TO 6.0788 TO 5.8517 TO 5.8594 TO -1.9057 TO
5.6048 6.4103 6.1864 6.1787 13.9438
.000 (Approx.)
.002
ANALYSIS OF VARIANCE
SUM OF MEAN F F SOURCE D.F. SQUARES SQUARES RATIO PROB.
BETWEEN GROUPS 1 .2665 .2665 .5823 .4460 WITHIN GROUPS 294 134.5263 .4576 TOTAL 295 134.7928
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 63 6.4603 .7512 .0946 4.0000 7.0000 6.2711 TO 6.6495 Grp 2 233 6.5336 .6550 .0429 3.6667 7.0000 6.4491 TO 6.6182 TOTAL 296 6.5180 .6760 .0393 3.6667 7.0000 6.4407 TO 6.5953
FIXED EFFECTS MODEL .6764 .0393 6.4 406 TO 6.5954 RANDOM EFFECTS MODEL .0393 6.0184 TO 7.0176
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0019 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5681, P = .098 (Approx.) Bartlett-Box F = 1.921 , P = .166 Maximum Variance / Minimum Variance 1.315
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ O N E W A Y _ _ _ _ _ _ _ _
Variable F9 (Technology) NOT SIGNIFICANT By Variable PAID3
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 294 295
SUM OF SQUARES
1.1404 334.6419 335.7823
MEAN SQUARES
1.1404 1.1382
F RATIO
F PROB.
1.0019 .3177
GROUP C
Grp l(NOINS) Grp 2(INS) TOTAL
63 233 296
MEAN
5.6667 5.8183 5.7860
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.0473 1.0721 1.0669 1.0669
STANDARD ERROR
.1319
.0702
.0620
.0620
.0621
3.3333 2.0000 2 .0000
MAXIMUM
7.0000 7.0000 7.0000
0.0000 RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5117, P = .777 (Approx.) Bartlett-Box F = .053 , P = .818 Maximum Variance / Minimum Variance 1.048
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ _ - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - - -Variable F10 (Opportunity) NOT SIGNIFICANT By Variable PAID3
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
5.4029 TO 5.6799 TO 5.6640 TO 5.6640 TO 4.9966 TO
5.9304 5.9567 5.9081 5.9081 6.5755
SOURCE D.F. SUM OF
SQUARES MEAN
SQUARES F
RATIO F
PROB.
BETWEEN GROUPS 1 .2955 .2955 2261 .6348 WITHIN GROUPS 286 373.7668 1.3069 TOTAL 287 374.0623
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp l(NOINS) 58 3.4353 1.2804 .1681 1.2500 7.0000 3.0987 TO 3.7720 Grp 2(INS) 230 3.5152 1.1064 .0730 1.0000 6.7500 3.3715 TO 3.6590 TOTAL 288 3.4991 1.1416 .0673 1.0000 7.0000 3.3667 TO 3.6315
FIXED EFFECTS MODEL 1.1432 .0674 3.3665 TO 3.6317 RANDOM EFFECTS MODEL .0674 2.6432 TO 4.3551
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0109
219
- - - - - - - - - - - - - - O N E W A Y Variable F1 (Reputation) NOT SIGNIFICANT By Variable TRAVEL2 (Grp 1 <30 Miles;Grp 2 >30 Miles)
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 289 290
SUM OF SQUARES
.0744 276.0259 276.1003
MEAN SQUARES
.0744
.9551
RATIO PROB.
.0779 .7804
GROUP
Grp 1(1,2) Grp 2(3) TOTAL
COUNT
281 10
291
MEAN
5.1997 5.2875 5.2027
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
.9828
.7863
.9757
. 9773
STANDARD ERROR
.0586
.2486
.0572
.0573
.0573
MINIMUM
2.1250 4.0000 2.1250
MAXIMUM
7.0000 6.5000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0456 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .6097, P = .008 (Approx.) Bartlett-Box F = .731 , P = .3 93 Maximum Variance / Minimum Variance 1.562
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - - - -Variable F2 (Physician Socio-Demographic) NOT SIGNIFICANT By Variable TRAVEL2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
5.0843 TO 4.7250 TO 5.0902 TO 5.0900 TO 4.4748 TO
5.3151 5.8500 5.3153 5.3155 5.9307
SOURCE SUM OF SQUARES
MEAN SQUARES RATIO PROB.
BETWEEN GROUPS 1 .0014 .0014 0010 .9748 WITHIN GROUPS 279 393.8189 1.4115 TOTAL 280 393.8203
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1(1,2) 272 3.4710 1.1853 .0719 1.1250 6.5000 3.3296 TO 3.6125 Grp 2(3) 9 3.4583 1.2778 .4259 2.0000 6.0000 2.4761 TO 4.4405 TOTAL 281 3.4706 1.1860 .0707 1.1250 6.5000 3.3314 TO 3.6099
FIXED EFFECTS ! MODEL 1.1881 .0709 3.3311 TO 3.6102 RANDOM EFFECTS : MODEL .0709 2.5701 TO 4.3712
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0809 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5375, P = .375 (Approx.) Bartlett-Box F = .088 , P = .766 Maximum Variance / Minimum Variance 1.162
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ _ - _ _ _ _ _ - _ _ - O N E W A Y - - - - - - - - - - - - - - - -Variable F3 (Economic) TREND By Variable TRAVEL2
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 280 281
SUM OF SQUARES
4.2684 345.2859 349.5543
MEAN SQUARES
4.2684 1.2332
RATIO PROB.
3.4613 .0639
GROUP COUNT MEAN
3.8776 4.5429 3.9012
STANDARD DEVIATION
1.1184 .8379
1.1153 1.1105
STANDARD ERROR
.0678
.2650
.0664
.0661
.3885
MINIMUM
1.0000 2.8571 1.0000
MAXIMUM
6.8571 5.2857 6.8571
0.1573
Grp 1(1,2) 272 Grp 2(3) 10 TOTAL 282
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .6405, P = .001 (Approx.) Bartlett-Box F = 1.178 , P = .278 Maximum Variance / Minimum Variance 1.7 82
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ O N E W A Y
Variable F4 (Environmental) NOT SIGNIFICANT By Variable TRAVEL2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
3.7441 TO 3.9435 TO 3.7705 TO 3.7710 TO -1.0354 TO
4.0111 5.1422 4.0320 4.0314 8.8379
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
1 295 296
SUM OF SQUARES
.0808 404.6616 404.7424
MEAN SQUARES
.0808 1.3717
RATIO PROB.
.0589 .8084
220
GROUP
Grp 1(1,2) Grp 2(3) TOTAL
COUNT
287 10
297
MEAN
5.3415 5.2500 5.3384
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.1601 1.4814 1.1693 1.1712
STANDARD ERROR
.0685
.4684
.0679
.0680
.0680
MINIMUM
1.0000 2.2500 1.0000
95 PCT CONF INT FOR MEAN
7.0000 7.0000 7.0000
5.2067 TO 4.1903 TO 5.2048 TO 5.2046 TO 4.4749 TO
5.4762 6.3097 5.4719 5.4721 6.2019
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0668 Tests for Homogeneity of Variances
Cochrane C = Max. Variance/Sum(Variances) = .6198, P = .003 (Approx.) Bartlett-Box F = 1.177 , P = .278 Maximum Variance / Minimum Variance 1.631
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. O N E W A Y *
Variable F5 (Perceptuals) NOT SIGNIFICANT By Variable TRAVEL2
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
GROUP
Grp 1(1,2) Grp 2(3) TOTAL
COUNT
D.F.
1 285 286
MEAN
278 5.6871 9 5.5926
287 5.6841 FIXED EFFECTS MODEL
RANDOM EFFECTS MODEL
SUM OF SQUARES
.0778 264.3351 264.4129 STANDARD DEVIATION
.9475 1.3997 .9615 .9631
MEAN SQUARES
.0778
.9275
F F RATIO PROB.
.0839 .7723
STANDARD ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
0568 2, .3333 7, .0000 5.5752 TO 5, .7989 4666 3. .3333 7, .0000 4.5167 TO 6, .6685 0568 2, .3333 7, .0000 5.5724 TO 5, .7958 0568 5.5722 TO 5 .7960 0568 4.9618 TO 6 .4064
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0487 Tests for Homogeneity of Variances _ _ _ _ _ _ _ _ _ - _ _ _ - - - - _ O N E W A Y - - - - - - - - - - - - - -Variable F6 (Self-Efficacy) NOT SIGNIFICANT By Variable TRAVEL2
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
GROUP COUNT
D.F.
1 288 289
MEAN
SUM OF SQUARES
2.4949 296.8694 299.3644
STANDARD DEVIATION
MEAN SQUARES
2.4949 1.0308
RATIO PROB.
2.4204 .1209
STANDARD ERROR
.0600
.4156
.0598
.0596
.2726
MINIMUM
1.8333 2.1667 1.8333
MAXIMUM
7.0000 6.1667 7.0000
0.0758
Grp 1(1,2) 280 4.8083 1.0042 Grp 2(3) 10 4.3000 1.3142 TOTAL 290 4.7908 1.0178
FIXED EFFECTS MODEL 1.0153 RANDOM EFFECTS MODEL
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .6314, P = .001 (Approx.) Bartlett-Box F = 1.449 , P = .229 Maximum Variance / Minimum Variance 1.713
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. __ _ _ - O N E W A Y
Variable F7 (Insurance) NOT SIGNIFICANT By Variable TRAVEL2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
4.6902 TO 3.3599 TO 4.6732 TO 4.6735 TO 1.3267 TO
4.9265 5.2401 4.9084 4.9081 8.2549
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
GROUP COUNT
D.F.
1 288 289
MEAN
SUM OF SQUARES
.1509 601.7250 601.8759
STANDARD DEVIATION
MEAN SQUARES
.1509 2.0893
1.0000 1.0000 1.0000
7.0000 7.0000 7.0000
Grp 1(1,2) 280 6.0250 1.4297 Grp 2(3) 10 5.9000 1.8679 TOTAL 290 6.0207 1.4431
FIXED EFFECTS MODEL 1.4454 RANDOM EFFECTS MODEL
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.1004
STANDARD ERROR
.0854
.5907
.0847
.0849
.0849
RATIO PROB.
.0722 .7883
MAXIMUM 95 PCT CONF INT FOR MEAN
5.8568 TO 4.5638 TO 5.8539 TO 5.8536 TO 4.9422 TO
6.1932 7.2362 6.1875 6.1878 7.0992
221
_ _ _ _ _ _ O N E W A Y -Variable F8 (Communication) NOT SIGNIFICANT By Variable TRAVEL2
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
GROUP COUNT
D.F.
1 295 296
MEAN
SUM OF SQUARES
.0751 134.7397 134.8148
STANDARD DEVIATION
.6680
.8896
.6749
.6758
MEAN SQUARES
.0751
.4567
RATIO PROB.
.1644 .6854
STANDARD ERROR
.0394
.2813
.0392
.0392
.0392
MAXIMUM
3.6667 4.3333 3.6667
7.0000 7.0000 7.0000
Grp 1(1,2) 287 6.5215 Grp 2(3) 10 6.4333 TOTAL 297 6.5185
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0197 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .6394, P = .001 (Approx.) Bartlett-Box F = 1.663 , P = .197 Maximum Variance / Minimum Variance 1.773
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ _ - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - - -Variable F9 (Technology) NOT SIGNIFICANT By Variable TRAVEL2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
6.4439 TO 5.7970 TO 6.4415 TO 6.4413 TO 6.0202 TO
6.5991 7.0697 6.5956 6.5957 7.0168
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
GROUP
Grp 1(1,2) Grp 2(3) TOTAL
COUNT
D.F.
1 295 296
MEAN
287 5.7944 10 5.6000 297 5.7879
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
SUM OF SQUARES
.3653 335.7155 336.0808
STANDARD DEVIATION
1.0596 1.2746 1.0656 1.0668
MEAN SQUARES
.3653 1.1380
RATIO PROB.
.3210 .5714
STANDARD ERROR
.0625
.4031
.0618
.0619
.0619
MINIMUM
2.0000 3.3333 2.0000
MAXIMUM
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0400 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5914, P = .025 (Approx.) Bartlett-Box F = .647 , P = .421 Maximum Variance / Minimum Variance 1.447
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ - _ _ _ _ _ _ - - - O N E W A Y - - - - - - - - - - - - - - - - - - -Variable F10 (Opportunity) NOT SIGNIFICANT By Variable TRAVEL2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
5.6713 TO 4.6882 TO 5.6662 TO
5.6661 TO 5.0014 TO
5.9175 6.5118 5.9096 5.9097 6.5744
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
GROUP
Grp 1(1,2) Grp 2(3) TOTAL
COUNT
D.F.
1 286 287
MEAN
278 3.4946 10 3.6250 288 3.4991
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
SUM OF SQUARES
.1641 373.8982 374.0623
STANDARD DEVIATION
1.1368 1.3294 1.1416 1.1434
MEAN SQUARES
.1641 1.3073
RATIO PROB.
.1255 .7234
STANDARD ERROR
.0682
.4204
.0673
.0674
.0674
MINIMUM
1.0000 2.2500 1.0000
MAXIMUM
7.0000 6.2500 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0592 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5776, P = .062 (Approx.) Bartlett-Box F = .455 , P = .500 Maximum Variance / Minimum Variance 1.368
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ - _ _ o N E W A Y ~ - - - - - - - - - - - - - -Variable F1 (Reputation) NOT SIGNIFICANT By Variable LASTIME2 (Grpl < 6mos : Grp2 > 6 mos)
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
3.3604 TO 2.6740 TO 3.3667 TO 3.3665 TO 2.6431 TO
3.6288 4.5760 3.6315 3.6317 4.3552
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 289 290
SUM OF SQUARES
.4486 275.6517 276.1003
MEAN SQUARES
.4486
.9538
RATIO PROB.
.4703 .4934
222
Grp 1 Grp 2 TOTAL
COUNT
213 78 291
MEAN
5.1790 5.2676 5.2027
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.0308 .8090 .9757 .9766
STANDARD ERROR
.0706
.0916
.0572
.0573
.0573
2.1250 3.2500 2.1250
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0044 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .6188, P = .004 (Approx.) Bartlett-Box F = 6.086 , P = .014 Maximum Variance / Minimum Variance 1.623
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. O N E W A Y
Variable F2 (Physician Socio-Demographic) NOT SIGNIFICANT By Variable LASTIME2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
5.0398 TO 5.0852 TO 5.0902 TO 5.0901 TO 4.4753 TO
5.3182 5.4500 5.3153 5.3154 5.9302
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 279 280
SUM OF SQUARES
.8182 393.0021 393.8203
MEAN SQUARES
.8182 1.4086
RATIO PROB.
.5809 .4466
GROUP
Grp 1 Grp 2 TOTAL
COUNT MEAN
203 3.4372 78 3.5577 281 3.4706
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.2077 1.1304 1.1860 1.1868
STANDARD ERROR
.0848
.1280
.0707
.0708
.0708
MINIMUM
1.1250 1.2500 1.1250
MAXIMUM
6.5000 6.3750 6.5000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0052 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5330, P = .435 (Approx.) Bartlett-Box F = .475 , P = .491 Maximum Variance / Minimum Variance 1.141
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ _ _ _ - - - - - _ - _ _ - O N E W A Y - - - - - - - - - - - - - -Variable F3 (Economic) NOT SIGNIFICANT By Variable LASTIME2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
3.2701 TO 3.3028 TO 3.3314 TO 3.3313 TO 2.5710 TO
3.6043 3.8126 3.6099 3.6100 4.3703
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 280 281
SUM OF SQUARES
.0269 349.5274 349.5543
MEAN SQUARES
.0269 1.2483
RATIO PROB.
.0215 .8834
GROUP
Grp 1 Grp 2 TOTAL
COUNT MEAN
206 3.8953 76 3.9173 282 3.9012
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.1278 1.0880 1.1153 1.1173
STANDARD ERROR
.0786
.1248
.0664
.0665
.0665
MINIMUM
1.0000 1.8571 1.0000
6.8571 6.2857 6.8571
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0110 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5179, P = .672 (Approx.) Bartlett-Box F = .139 , P = .709 Maximum Variance / Minimum Variance 1.074
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. - - - - - - - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - - - - -Variable F4 (Environmental) NOT SIGNIFICANT By Variable LASTIME2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
3.7404 TO 3.6687 TO 3.7705 TO 3.7702 TO 3.0558 TO
4.0502 4.1659 4.0320 4.0322 4.7466
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 295 296
SUM OF SQUARES
1.5671 403.1753 404.7424
MEAN SQUARES
1.5671 1.3667
F RATIO
F PROB.
1.1466 .2851
STANDARD DEVIATION
STANDARD ERROR MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 217 5.3825 1. .1319 .0768 1. .7500 7. .0000 5.2310 TO 5, .5339 Grp 2 80 5.2188 1. .2650 .1414 1. .0000 7, .0000 4.9372 TO 5. .5003 TOTAL 297 5.3384 1. 1693 .0679 1. .0000 7. .0000 5.2048 TO 5. .4719
FIXED EFFECTS MODEL 1. .1691 .0678 5.2049 TO 5, .4719 RANDOM EFFECTS MODEL .0751 4.3841 TO 6, .2927
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0017 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5554, P = .177 (Approx.) Bartlett-Box F = 1.471 , P = .225
223
Maximum Variance / Minimum Variance 1.249 NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS.
O N E W A Y Variable F5 (Perceptuals) SIGNIFICANT By Variable LASTIME2
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 285 286
SUM OF SQUARES
4.0871 260.3258 264.4129
MEAN SQUARES
4.0871 .9134
F RATIO
F PROB.
4.4745 .0353
STANDARD DEVIATION
STANDARD ERROR 95 PCT CONF INT FOR MEAN
Grp 1 Grp 2 TOTAL
210 5.7563 .9403 .0649 2. .3333 7, .0000 5.6284 TO 5, .8843 77 5.4870 . 9970 .1136 2. .6667 7, .0000 5.2607 TO 5, .7133 287 5.6841 .9615 .0568 2. .3333 7, .0000 5.5724 TO 5, .7958
FIXED EFFECTS MODEL .9557 .0564 5.5730 TO 5, .7951 RANDOM EFFECTS MODEL .1424 3.8742 TO 7 , .4940
0 . 0 2 8 2 RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5292, P = .485 (Approx.) _ _ _ _ _ _ - - - - - - - O N E W A Y - - - - - - - - - - - - - - - - -Variable F6 (Self-Efficacy) NOT SIGNIFICANT By Variable LASTIME2
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 288 289
SUM OF SQUARES
.5092 298.8552 299.3644
MEAN SQUARES
.5092 1.0377
RATIO PROB.
.4907 .4842
GROUP
Grp 1 Grp 2 TOTAL
COUNT MEAN
210 4.8167 80 4.7229
290 4.7908 FIXED EFFECTS MODEL
RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.0558 .9132
1.0178 1.0187
STANDARD ERROR
.0729
.1021
.0598
.0598
.0598
MINIMUM
1.8333 2.8333 1.8333
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0046 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5720, P = .083 (Approx.) Bartlett-Box F = 2.294 , P = .130 Maximum Variance / Minimum Variance 1.337
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. ONEWAY
Variable F7 (Insurance) NOT SIGNIFICANT By Variable LASTIME2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
4.6730 TO 4.5197 TO 4.6732 TO 4.6731 TO 4.0307 TO
4.9603 4.9261 4.9084 4.9085 5.5509
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 288 289
SUM OF SQUARES
1.3012 600.5746 601.8759
MEAN SQUARES
1.3012 2.0853
RATIO PROB.
.6240 .4302
GROUP COUNT MEAN STANDARD
DEVIATION STANDARD
ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 Grp 2 TOTAL
212 78 290
6.0613 5.9103 6.0207
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
1.4583 1.4044 1.4431 1.4441
.1002
.1590
.0847
.0848
.0848
1.0000 1.5000 1.0000
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0069 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5188, P = .652 (Approx.) Bartlett-Box F = .157 , P = .692 Maximum Variance / Minimum Variance 1.078
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ _ - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - - -Variable F8 (Communication) SIGNIFICANT By Variable LASTIME2
ANALYSIS OF VARIANCE
5.8639 TO 5.5936 TO 5.8539 TO 5.8538 TO 4.9432 TO
6.2588 6.2269 6.1875 6.1876 7.0982
D.F. SUM OF
SQUARES MEAN
SQUARES F
RATIO F
PROB.
BETWEEN GROUPS WITHIN GROUPS TOTAL
1 295 296
3.5247 131.2901 134.8148
3.5247 .4451
7.9197 .0052
224
GROUP
Grp 1 Grp 2 TOTAL
218 79 297
MEAN
6.5841 6.3376 6.5185
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
.6158
.7926
.6749
.6671
STANDARD ERROR
.0417
.0892
.0392
.0387
.1330
MINIMUM
3.6667 4.0000 3.6667
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 0 N E W A Y - - - - _ _ _
Variable F9 (Technology) NOT SIGNIFICANT By Variable LASTIME2
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 295 296
ANALYSIS OF VARIANCE SUM OF
SQUARES
.3774 335.7034 336.0808
MEAN SQUARES
.3774 1.1380
MAXIMUM
7.0000 7.0000 7.0000
0 . 0 2 6 6
RATIO PROB.
.3317 .5651
95 PCT CONF INT FOR MEAN
6.5019 TO 6.1600 TO 6.4415 TO
6.4423 TO 4.8288 TO
6.6663 6.5151 6.5956 6.5947 8 .2082
GROUP
Grp 1 Grp 2 TOTAL
COUNT MEAN
217 5.8095 80 5.7292
297 5.7879 FIXED EFFECTS MODEL
RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.0287 1.1645 1.0656 1.0668
STANDARD ERROR
.0698
.1302
.0618
.0619
.0619
2.3333 2 . 0 0 0 0 2 . 0 0 0 0
MAXIMUM
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0065 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5617, P = .132 (Approx.) Bartlett-Box F = 1.837 , P = .175 Maximum Variance / Minimum Variance 1.282
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. O N E W A Y _ _ _ _
Variable F10 (Opportunity) NOT SIGNIFICANT By Variable LASTIME2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
5.6719 TO 5.4700 TO 5.6662 TO
5.6661 TO 5.0014 TO
5.9472 5.9883 5.9096 5.9097 6.5744
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 286 287
SUM OF SQUARES
2.8661 371.1961 374.0623
MEAN SQUARES
2.8661 1.2979
F RATIO
F PROB.
2.2083 .1384
GROUP
Grp 1 Grp 2 TOTAL
COUNT MEAN
209 3.4378 79 3.6614 288 3.4991
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.1635 1.0720 1.1416 1.1392
STANDARD ERROR
.0805
.1206
.0673
.0671
.1129
MINIMUM
1.0000 1.7500 1.0000
MAXIMUM
7.0000 6.7500 7.0000
0.0137 RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5409, P = .328 (Approx.) Bartlett-Box F = .739 , p = 390
- - O N E W A Y Variable F1 (Physician Reputation) (TREND) By Variable OCC occupation
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
3.2791 TO 3.4213 TO 3.3667 TO 3.3670 TO 2.0650 TO
3.5965 3.9015 3.6315 3.6313 4.9332
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
9 277 286
SUM OF SQUARES
15.7272 255.9690 271.6962
MEAN SQUARES
1.7475 .9241
RATIO PROB.
1.8910 .0532
GROUP COUNT
Grp Grp Grp Grp Grp Grp Grp Grp 8 Grp 9 GrplO TOTAL
(Unskill) (Skilled) (Office) (Prof) (Mgmt) (Selfemp) (Homemake)33 (Student) 19 (Unemploy) 6 (Other) 18
287
MEAN
4.9167 5.4524 5.3021 5.1760 4.9405 5.2054 5.4545 4.6053 5.8542 5.0764 5.1956
STANDARD STANDARD DEVIATION ERROR MINIMUM MAXIMUM
.9540 .3180 2. .7500 6.0000
.8125 .1773 4. .0000 6.6250 1. .0320 .1490 2, .5000 6.8750 1. .0436 .1054 2. .1250 6.8750 .8584 .1873 3. .0000 6.1250 .6787 .1814 3. .7500 6.0000 .7929 .1380 3. .3750 7.0000
1, .0402 .2386 2. .1250 6.3750 .3104 .1267 5. .5000 6.2500
l! .0564 .2490 3. .1250 6.6250 ,9747 .0575 2. ,1250 7.0000 .9613 .0567
.0944
95 PCT CONF INT FOR MEAN
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0 0315 - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - - _ - _ _ l _ _ _ Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .1423, P = .581 (Approx ) Bartlett-Box F = 1.668 , P = .091 Maximum Variance / Minimum Variance 11.583
4.1833 TO 5.0825 TO 5.0024 TO 4.9668 TO 4.5497 TO 4.8135 TO 5.1734 TO 4.1039 TO 5.5284 TO 4.5510 TO 5.0823 TO 5.0839 TO 4.9820 TO
5.6500 5.8222 5.6017 5.3853 5.3312 5.5972 5.7357 5.1066 6.1799 5.6017 5.3088 5.3073 5.4091
225
O N E W A Y
Variable F1 (Physician Reputation) By Variable OCC occupation MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
5.87 5.87 5.87 5.87 5.87 5.87 5.87 5.87 5.87 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.6797 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
O N E W A Y - -Variable F2 (Physician Socio-Demographic) (SIGNIFICANT) By Variable OCC occupation
ANALYSIS OF VARIANCE
SUM OF SQUARES
MEAN SQUARES
F RATIO
F PROB.
BETWEEN GROUPS 9 32 .4492 3.6055 2. ,7274 .0047 WITHIN GROUPS 267 352 .9644 1.3220 TOTAL 276 385 .4136
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 9 3 .6667 1. 1110 .3703 1.5000 4.6250 2.8127 TO 4.5207 Grp 2 20 4 .1125 1. 0426 .2331 2.3750 6.2500 3.6246 TO 4.6004 Grp 3 46 3 .5924 1. 1718 .1728 1.3750 6.1250 3.2444 TO 3.9404 Grp 4 92 3 .3370 1. 1495 .1198 1.1250 6.0000 3.0989 TO 3.5750 Grp 5 21 3 .2560 1. 2701 .2772 1.3750 6.0000 2.6778 TO 3.8341 Grp 6 15 2 .9000 7809 .2016 1.6250 4.3750 2.4675 TO 3.3325 Grp 7 32 3 .6563 1. 2107 .2140 1.2500 6.5000 3.2198 TO 4.0927 Grp 8 18 2 .8403 1. 0640 .2508 1.2500 4.5000 2.3112 TO 3.3694 Grp 9 6 4 .5625 1. 1639 .4752 3.2500 6.3750 3.3411 TO 5.7839 GrplO 18 3 .5972 1. 2866 .3033 1.8750 6.2500 2.9574 TO 4.2371 TOTAL 277 3 .4644 1. 1817 .0710 1.1250 6.5000 3.3246 TO 3.6041
FIXED EFFECTS MODEL 1. 1498 .0691 3.3283 TO 3.6004 RANDOM EFFECTS MODEL .1433 3.1403 TO 3.7884
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0899 _ _ _ _ _ _ _ _ _ _ - O N E W A Y
.1289,
.535 , 2.715
Tests for Homogeneity of Variances Cochrans C = Max. Variance/Sum(Variances) = Bartlett-Box F = Maximum Variance / Minimum Variance _ „ - O N E W A Y - - - - - -
Variable F2 (Physician Socio-Demographic) By Variable OCC occupation MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
5.87 5.87 5.87 5.87 5.87 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I)
0.8130 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL _ _ _ _ - O N E W A Y Variable F3 (Economic) (SIGNIFICANT)
1.000 .850
(Approx.)
5.87 5.87
IS. .
By Variable OCC occupation ANALYSIS OF VARIANCE
SOURCE D.F. SUM OF SQUARES
MEAN SQUARES
F RATIO
F PROB.
BETWEEN GROUPS WITHIN GROUPS TOTAL
9 269 278
32.5683 315.9348 348.5031
3.6187 1.1745
3.0811 .0015
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 9 4 .2222 .9506 .3169 2, .2857 5, .5714 3.4915 TO 4 < .9529 Grp 2 20 4 .7929 .7679 .1717 3. .2857 6. .1429 4.4335 TO 5, .1522 Grp 3 46 4 .0714 1, .0643 .1569 2. .4286 6. .8571 3.7554 TO 4, .3875 Grp 4 94 3 .6702 1, .1558 .1192 1. .0000 5, .7143 3.4335 TO 3, .9070 Grp 5 20 3 .7071 .9538 .2133 2, .1429 5, .4286 3.2608 TO 4. .1535 Grp 6 14 3 .6735 .9417 .2517 2. .4286 5, .7143 3.1298 TO 4. .2172 Grp 7 32 3 .8125 1. .1009 .1946 1. .8571 6, .1429 3.4156 TO 4. .2094 Grp 8 19 3 .7519 1, .1721 .2689 1. .1429 5. .8571 3.1870 TO 4. .3168 Grp 9 7 4 .9184 1. .0264 .3879 3. .7143 6. .2857 3.9691 TO 5. .8676 GrplO 18 3 .9048 1. .2092 .2850 2. .0000 5. .7143 3.3034 TO 4. .5061 TOTAL 279 3 .9058 1. .1196 .0670 1. .0000 6. .8571 3.7738 TO 4. .0377
FIXED EFFECTS MODEL 1. .0837 .0649 3.7780 TO 4. .0335 RANDOM EFFECTS MODEL .1455 3.5766 TO 4. .2350
0RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0. .0958 .2350
- - - - - - - - - - - - O N E W A Y - - - - - - - - - -Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .1346, Bartlett-Box F = .7 03 , Maximum Variance / Minimum Variance 2.480
P = .967 P = .7 07
(Approx.)
226
_ _ _ O N E W A Y - - -Variable F3 (Economic) By Variable OCC occupation MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
5.87 5.87 5.87 5.87 5.87 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS..
0.7663 * RANGE * DSQRT(1/N(I) + 1/N(J)) (*) DENOTES PAIRS OF GROUPS SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
5.87 5.87 5.87 5.87
Mean Group 3. .6702 Grp 4 3. .6735 Grp 6 3. .7071 Grp 5 3, .7519 Grp 8 3. .8125 Grp 7 3. .9048 GrplO 4, .0714 Grp 3 4, .2222 Grp 1 4, .7929 Grp 2 4, .9184 Grp 9
4 6 5
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ O N E W A Y ----- - - - - - -Variable F4 (Environmental-Location/Appt) (NOT SIGNIFICANT) By Variable OCC occupation
ANALYSIS OF VARIANCE
SOURCE D.F. SUM OF
SQUARES MEAN
SQUARES F
RATIO F
PROB.
BETWEEN GROUPS WITHIN GROUPS TOTAL
9 283 292
16.4365 382.5063 398.9428
1.8263 L.3516
1.3512 .2103
GROUP COUNT STANDARD DEVIATION
STANDARD ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 Grp 2 Grp 3 Grp 4 Grp 5 Grp 6 Grp 7 Grp 8 Grp 9 GrplO TOTAL
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE _ _ _ _ _ _ _ _ _ _ 0 N E W A Y - - - - - - - - - - - - - - -
Tests for Homogeneity of Variances Cochrans C = Max. Variance/Sum(Variances) = .1823, P = .027
11 5.7500 ,7665 .2311 4. .5000 6. .5000 5.2351 TO 6. .2649 19 5.3816 1. .0941 .2510 2. .2500 7, .0000 4.8543 TO 5. .9089 48 5.3802 1. .0171 .1468 3. .2500 7, .0000 5.0849 TO 5. .6756 99 5.3005 1. .0720 .1077 2. .7500 7, .0000 5.0867 TO 5. .5143 21 5.3690 1. .4023 .3060 2. .7500 7, .0000 4.7307 TO 6. .0074 15 4.9833 1. .0154 .2622 3. .7500 6, .7500 4.4210 TO 5, .5456 35 5.4071 1. .5316 .2589 1. .0000 7, .0000 4.8810 TO 5. .9333 19 4.8553 1. .2425 .2851 2, .2500 7, .0000 4.2564 TO 5. .4541 7 6.3929 .5563 .2103 5. .5000 7, .0000 5.8783 TO 6. .9074 19 5.3684 1. .3054 .2995 3, .0000 7, .0000 4.7393 TO 5. .9976
293 5.3387 1. .1689 .0683 1, .0000 7, .0000 5.2043 TO 5. .4731 FIXED EFFECTS MODEL 1. .1626 .0679 5.2050 TO 5. .4724 RANDOM EFFECTS MODEL .0881 5.1394 TO 5, .5380
Bartlett-Box F = Maximum Variance
2.044 7.579
.031
0.0177
(Approx.)
Minimum Variance _ _ _ _ _ _ _ _ _ _ __ __ - O N E W A Y Variable F4 (Environmental) By Variable OCC occupation MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
5.87 5.87 5.87 5.87 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.8221 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL _ _ _ _ - - - - - - - - - - O N E W A Y - - - - - - - - - - -Variable F5 (Perceptuals) (NOT SIGNIFICANT)
5.87 5.87 5.87
By Variable OCC occupation ANALYSIS OF VARIANCE
SOURCE D.F. SUM OF
SQUARES MEAN
SQUARES F
RATIO F
PROB.
BETWEEN GROUPS 9 9 .5230 1.0581 1. 1436 .3320 WITHIN GROUPS 273 252 .5871 .9252 TOTAL 282 262 .1101
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 10 6.0667 9819 .3105 3, .6667 7, .0000 5.3642 TO 6. 7691 Grp 2 21 5.9683 1. 0009 .2184 3. .3333 7 , .0000 5.5127 TO 6. 4238 Grp 3 45 5.7148 9222 .1375 3. .6667 7. .0000 5.4377 TO 5. 9919 Grp 4 95 5.6053 9740 .0999 2. .6667 7, .0000 5.4069 TO 5. 8037 Grp 5 20 5.5917 9963 .2228 3. .0000 7. .0000 5.1254 TO 6. 0580 Grp 6 15 5.4000 1. 1283 .2913 2. .3333 6. .6667 4.7752 TO 6. 0248 Grp 7 33 5.9394 7871 .1370 3 , .6667 7. .0000 5.6603 TO 6. 2185 Grp 8 19 5.3772 1. 0597 .2431 3. .6667 7 . .0000 4.8664 TO 5. 8880 Grp 9 7 5.8333 1. 0364 .3917 4, .3333 7 , .0000 4.8749 TO 6. 7918 GrplO 18 5.5648 9113 .2148 4, .1667 7. .0000 5.1116 TO 6. ,0180 TOTAL 283 5.6808 9641 .0573 2, .3333 7, .0000 5.5680 TO 5. 7936
FIXED EFFECTS MODEL 9619 .0572 5.5682 TO 5. .7934
227
0.0051 RANDOM EFFECTS MODEL .0646
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE - - O N E W A Y - -Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .1315, P = 1.000 (Approx.) Bartlett-Box F = .422 , P = .924 Maximum Variance / Minimum Variance 2.055
- - - - -- - - - - - - - O N E W A Y - - - - - - - - - - - - - - - - - - - -Variable F5 (Perceptuals) By Variable OCC occupation MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
5.87 5.87 5.87 5.87 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I)
0.6802 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL - - - - O N E W A Y - - - - - - - - - -Variable F6 (Self-Efficacy) (NOT SIGNIFICANT)
5.5348 TO 5.8268
5.87 5.87 5.87 5.87 5.87
IS.
By Variable OCC occupation ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
MEAN
GROUP COUNT
Grp 1 10 Grp 2 20 Grp 3 47 Grp 4 98 Grp 5 21 Grp 6 15 Grp 7 32 Grp 8 19 Grp 9 6 GrplO 18 TOTAL 286
D.F. SQUARES SQUARES RATIO PROB.
9 14 .7434 1.6382 1. ,6007 .1147 276 282 1.4560 1.0234 285 297 .1994
STANDARD STANDARD MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
1.5667 1. 0068 .3184 3. .1667 6 .0000 3.8465 TO 5. ,2869 1.5333 1. 1155 .2494 2, .1667 7 .0000 4.0112 TO 5. .0554 1.7872 1. 0522 .1535 2. .8333 7 .0000 4.4783 TO 5. ,0962 1.7211 9673 .0977 1. .8333 7 .0000 4.5272 TO 4. ,9150 1.6667 1. 0541 .2300 3, .0000 6 .6667 4.1868 TO 5. ,1465 1.5778 8994 .2322 2. .8333 6 .1667 4.0797 TO 5. ,0759 5.2656 1. 0514 .1859 3. .3333 7 .0000 4.8865 TO 5. ,6447 1.5965 1. 1046 .2534 2. .6667 6 .6667 4.0641 TO 5. ,1289 >.4722 9215 .3762 3. .8333 6 .3333 4.5052 TO 6. 4392 1.9907 9065 .2137 3. .6667 6 .5000 4.5399 TO 5. 4415 1.7873 1. 0212 .0604 1. .8333 7 .0000 4.6684 TO 4. 9062 MODEL 1. 0116 .0598 4.6695 TO 4. 9051 MODEL .0885 4.5872 TO 4. 9874
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE - - - - - - - - - - O N E W A Y - - - -
Tests for Homogeneity of Variances Cochrans C = Max. Variance/Sum(Variances) = .1218, P = 1.000 Bartlett-Box F = .238 , P = .989 Maximum Variance / Minimum Variance 1.538
. - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - - - - -Variable F6 (Self-Efficacy) By Variable OCC occupation MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
5.87 5.87 5.87 5.87 5.87 5.87 5.87 5.87 5.87 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS..
0.7153 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
_ _ _ _ _ _ _ O N E W A Y Variable F7 (Insurance) (NOT SIGNIFICANT)
0.0236
(Approx.)
By Variable OCC occupation ANALYSIS OF VARIANCE
SUM OF SQUARES
MEAN SQUARES
F RATIO
F PROB.
BETWEEN GROUPS 9 12.9585 1.4398 WITHIN GROUPS 276 586.9855 2.1268 TOTAL 285 599.9441
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR
Grp 1 11 6, .5455 9606 .2896 Grp 2 21 6. .0476 1. 5565 .3397 Grp 3 48 5, .8542 1. 4548 .2100 Grp 4 96 6. .0833 1. 3643 .1392 Grp 5 19 6, .1579 1. 3129 .3012 Grp 6 14 5. .9286 1. 5046 .4021 Grp 7 33 5. .8182 1. 8278 .3182 Grp 8 19 5. ,7368 1. 5756 .3615 Grp 9 6 6. .9167 2041 .0833 GrplO 19 5. ,9737 I! 5044 .3451 TOTAL 286 6. ,0140 i. 4509 .0858
.6770 .7296
MINIMUM
4.0000 1.0000 2.5000 1.0000 3.0000 2.5000 1.0000 2.0000 6.5000 2.0000 1.0000
MAXIMUM
7.0000 7.0000 7.0000 7.0000 7.0000 7.0000 7.0000 7.0000 7.0000 7.0000 7.0000
FIXED EFFECTS MODEL 1.4583 .0862 RANDOM EFFECTS MODEL .0862
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
95 PCT CONF INT FOR MEAN
5.9001 TO 5.3391 TO 5.4317 TO 5.8069 TO 5.5251 TO 5.0599 TO 5.1701 TO 4.9774 TO 6.7025 TO 5.2486 TO 5.8451 TO 5.8442 TO 5.8189 TO
7.1908 6.7561 6.2766 6.3598 6.7907 6.7973 6.4663 6.4962 7.1309 6.6988 6.1829 6.1837 6.2091
228
. . . . . . - - - - O N E W A Y Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .1719, P = .066 (Approx.) Bartlett-Box F = 2.487 , P = .008 Maximum Variance / Minimum Variance 80.182
O N E W A Y Variable F7 (Insurance) By Variable OCC occupation MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
5.87 5.87 5.87 5.87 5.87 5.87 5.87 5.87 5.87 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS..
1.0312 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL _ . _ _ _ _ _ _ _ _ _ _ O N E W A Y - - - - - - -Variable F8 (Communication) (NOT SIGNIFICANT) By Variable OCC occupation
ANALYSIS OF VARIANCE
SUM OF MEAN F F SOURCE D.F. SQUARES SQUARES RATIO PROB.
BETWEEN GROUPS 9 4.8956 .5440 1. 1938 .2987 WITHIN GROUPS 283 128.9519 .4557 TOTAL 292 133.8476
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 11 6.1515 .6388 .1926 5. ,0000 7.0000 5.7224 TO 6.5807 Grp 2 21 6.6349 .6984 .1524 4. .3333 7.0000 6.3170 TO 6.9529 Grp 3 47 6.5390 .6160 .0899 4, .3333 7.0000 6.3581 TO 6.7199 Grp 4 98 6.5476 .6059 .0612 4, .3333 7.0000 6.4261 TO 6.6691 Grp 5 21 6.5556 .5409 .1180 5. .3333 7.0000 6.3093 TO 6.8018 Grp 6 15 6.1556 .9910 .2559 3. .6667 7.0000 5.6068 TO 6.7043 Grp 7 35 6.6571 .6641 .1123 4. .6667 7.0000 6.4290 TO 6.8853 Grp 8 19 6.4737 .6787 .1557 4. .6667 7.0000 6.1465 TO 6.8008 Grp 9 7 6.3333 1.0364 .3917 4, .6667 7.0000 5.3749 TO 7.2918 GrplO 19 6.4561 .8404 .1928 4. .0000 7.0000 6.0511 TO 6.8612 TOTAL 293 6.5154 .6770 .0396 3. .6667 7.0000 6.4375 TO 6.5932
FIXED EFFECTS MODEL .6750 .0394 6.4377 TO 6.5930 RANDOM EFFECTS MODEL .0462 6.4109 TO 6.6198
0.0033 RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE O N E W A Y
Tests for Homogeneity of Variances Cochrans C = Max. Variance/Sum(Variances) = .1918, P = .012 (Approx.) Bartlett-Box F = 1.641 , P = .098 Maximum Variance / Minimum Variance 3.671
O N E W A Y Variable F8 (Communication)2 By Variable OCC occupation MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
5.87 5.87 5.87 5.87 5.87 5.87 5.87 5.87 5. THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS..
0.4773 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL - - - - - - - - - O N E W A Y - - - - - - - - - -Variable F9 (Technology) (TREND)
.87
By Variable OCC occupation ANALYSIS OF VARIANCE
SOURCE SUM OF
SQUARES MEAN
SQUARES F
RATIO F
PROB.
BETWEEN GROUPS 9 16 .5651 1.8406 1. 6549 .0997 WITHIN GROUPS 283 314 .7599 1.1122 TOTAL 292 331 ..3250
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 11 6 .0303 9939 .2997 3, .6667 7. .0000 5.3626 TO 6, .6980 Grp 2 21 5 .9524 l] 0661 .2326 3. .3333 7. .0000 5.4671 TO 6, .4377 Grp 3 48 6 .0694 9987 .1442 3 .0000 7 , .0000 5.7794 TO 6. .3594 Grp 4 99 5 .6599 l! 0135 .1019 3, .3333 7, .0000 5.4578 TO 5, .8621 Grp 5 21 5 .8254 1. 1861 .2588 3, .0000 7, .0000 5.2855 TO 6. .3653 Grp 6 15 5 .2000 9241 .2386 3, .6667 6. .6667 4.6882 TO 5. .7118 Grp 7 34 5 .9216 1. 0185 .1747 3, .6667 7. .0000 5.5662 TO 6. .2770 Grp 8 19 5 .4386 1. 2865 .2951 2, .3333 7, .0000 4.8185 TO 6, .0586 Grp 9 6 6 .3333 6992 .2854 5. .0000 7, .0000 5.5996 TO 7, .0671 GrplO 19 5 .7895 l! 2483 .2864 2, .0000 7. .0000 5.1878 TO 6, .3911 TOTAL 293 5 .7884 1. 0652 .0622 2, .0000 7, .0000 5.6659 TO 5, .9109
FIXED EFFECTS MODEL 1. 0546 .0616 5.6671 TO 5. .9097 RANDOM EFFECTS MODEL .0929 5.5783 TO 5. .9985
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0. .0272 5.5783 TO .9985
_ _ _ _ - O N E W A Y ~ -Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .1484, Bartlett-Box F = .535 , Maximum Variance / Minimum Variance 3.385
P = P =
.386
.768 (Approx.)
229
O N E W A Y - - -Variable F9 (Technology) By Variable OCC occupation MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
5.87 5.87 5.87 5.87 5.87 5.87 5.87 5.87 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.7457 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
- _ O N E W A Y - - -Variable F10 (Opportunity-time) (NOT SIGNIFICANT)
5.87
By Variable OCC occupation ANALYSIS OF VARIANCE
D.F. SUM OF
SQUARES MEAN
SQUARES F
RATIO F
PROB.
BETWEEN GROUPS 9 12 .1681 1.3520 1. .0371 .4105 WITHIN GROUPS 275 358 .4929 1.3036 TOTAL 284 370 .6610
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 10 3 .8750 1. 4203 .4492 1. .7500 6 .2500 2.8590 TO 4, .8910 Grp 2 20 4 .1375 8251 .1845 2. .7500 6. .0000 3.7514 TO 4, .5236 Grp 3 47 3 .4521 l] 2637 .1843 1. .2500 6, .7500 3.0811 TO 3. .8232 Grp 4 95 3 .4316 1. 0168 .1043 1. .5000 6, .7500 3.2245 TO 3, .6387 Grp 5 21 3 .3095 1. 0244 .2235 1. .7500 5. .2500 2.8432 TO 3, .7758 Grp 6 15 3 .5167 1. 4314 .3696 1, .7500 5, .5000 2.7240 TO 4, .3093 Grp 7 33 3 .4621 1. 1182 .1947 1. .0000 5, .5000 3.0656 TO 3, .8586 Grp 8 19 3 .3553 1. 0617 .2436 1. .2500 4. .5000 2.8435 TO 3. .8670 Grp 9 7 3 .8571 1. 9465 .7357 2. .0000 7. .0000 2.0570 TO 5. .6573 GrplO 18 3 .5139 1. 1896 .2804 1. .7500 6, .2500 2.9223 TO 4, .1055 TOTAL 285 3 .5096 1. 1424 .0677 1. .0000 7, .0000 3.3764 TO 3, .6429
FIXED EFFECTS MODEL 1. 1418 .0676 3.3765 TO 3, .6428 RANDOM EFFECTS MODEL .0700 3.3513 TO 3. .6680
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0, .0019 . _ _ _ _ _ _ _ _ _ _ . - - - 0 N E W ' A Y -
.2367, 1.633 , 5.565
P = P =
Tests for Homogeneity of Variances Cochrane C = Max. Variance/Sum(Variances) Bartlett-Box F = Maximum Variance / Minimum Variance
- - - - - - - - - - - - - O N E W A Y - - - -Variable F10 (Opportunity) By Variable OCC occupation MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
5.87 5.87 5.87 5.87 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I)
0.8073 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL - . - - - - - - - _ _ _ _ O N E W A Y - - - - - - - - - - -Variable F1 (Reputation) (NOT SIGNIFICANT)
.000
.100 (Approx.)
5.87 5.87 5.87 5.87 5.87
IS. .
By Variable MARITAL marital status ANALYSIS OF VARIANCE
SUM OF SQUARES
MEAN SQUARES RATIO PROB.
BETWEEN GROUPS 3 2 .1866 .7289 .7701 .5115 WITHIN GROUPS 286 270 .6725 .9464 TOTAL 289 272 .8591
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM
Grp 1 56 5 . 1496 1. 0309 .1378 2.1250 6.7500 Grp 2 179 5 .1913 9234 .0690 2.1250 6.7500 Grp 3 8 5 .7031 1. 3245 .4683 2.7500 6.8750 Grp 4 47 5 .1862 1. 0231 .1492 3.1250 7.0000 TOTAL 290 5 .1966 9717 .0571 2.1250 7.0000
FIXED EFFECTS MODEL 9728 .0571 RANDOM EFFECTS MODEL .0571
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0041 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .3719, P = .003 (Approx.) Bartlett-Box F = 1.050 , P = .3 69 Maximum Variance / Minimum Variance 2.057
_ _ _ - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - - - - - - -Variable F1 (Reputation) By Variable MARITAL marital status MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.6879 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
95 PCT CONF INT FOR MEAN
4.8735 TO 5.0551 TO 4.5959 TO 4.8858 TO 5.0842 TO 5.0841 TO 5.0148 TO
5.4256 5.3275 6.8104 5.4866 5.3089 5.3090 5.3784
230
. . . - - - - - - - O N E W A Y - - -Variable F2 (Physician Socio-Demographic) (NOT SIGNIFICANT) By Variable MARITAL
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
marital status ANALYSIS OF VARIANCE
D.F.
3 276 279
GROUP COUNT
Grp 1 53 Grp 2 175 Grp 3 6 Grp 4 46 TOTAL 280
MEAN
3.4316 3.4136 4.5000 3.5598 3.4643
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
SUM OF SQUARES
7.3624 383.2804 390.6429
STANDARD DEVIATION
1.1933 1.1574 1.2450 1.2329 1.1833 1.1784
MEAN SQUARES
2.4541 1.3887
F RATIO
F PROB.
1.7672 .1537
STANDARD ERROR
.1639
.0875
.5083
.1818
.0707
.0704
.1202
MINIMUM
1.2500 1.2500 2.8750 1.1250 1.1250
95 PCT CONF INT FOR MEAN
6.3750 6.5000 6.2500 6.2500 6.5000
0.0209 RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .2657, P = 1.000 (Approx.) Bartlett-Box F = -113 , P = .952 Maximum Variance / Minimum Variance 1.157
__ _ _ _ _ _ _ - - _ - O N E W A Y - - - - - --- - - - - - - - - - - - - - -Variable F2 (Physician Socio-Demographic) By Variable MARITAL marital status MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.8333 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
O N E W A Y Variable F3 (Economic) (TREND) By Variable MARITAL marital status
ANALYSIS OF VARIANCE
3.1027 TO 3.2409 TO 3.1935 TO 3.1937 TO 3.3251 TO 3.3256 TO 3.0818 TO
3.7605 3.5863 5.8065 3.9259 3.6035 3.6029 3.8468
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
3 277 280
SUM OF SQUARES
MEAN SQUARES
F RATIO
F PROB.
GROUP COUNT
Grp 1 55 Grp 2 172 Grp 3 9 Grp 4 45 TOTAL 281
MEAN
3.8260 3.8397 4.8254 4.0317 3.8993
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
9.4150 3.1383 2. 5579 .0555 339.8602 1.2269 349.2752
STANDARD STANDARD DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
1.1920 .1607 1.1429 6.2857 3.5037 TO 4.1482 1.1145 .0850 1.0000 6.8571 3.6720 TO 4.0075 .7206 .2402 3.8571 5.7143 4.2715 TO 5.3793
1.0288 .1534 1.5714 6.1429 3.7227 TO 4.3408 1.1169 .0666 1.0000 6.8571 3.7682 TO 4.0305 1.1077 .0661 3.7693 TO 4.0294
.1427 3.4451 TO 4.3536 0.0364 RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE
-Tests for Homogeneity of Variances Cochrans C = Max. Variance/Sum(Variances) = .3350, P = .056 (Approx.) Bartlett-Box F Maximum Variance
1.095 2.736
.350 / Minimum Variance
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ - O N E W A Y -Variable F3 (Economic) By Variable MARITAL marital status MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I)
0.7832 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
O N E W A Y -Variable F4 (Environmental) (NOT SIGNIFICANT)
IS..
By Variable MARITAL marital status ANALYSIS OF VARIANCE
SUM OF SQUARES
MEAN SQUARES RATIO PROB.
BETWEEN GROUPS 3 3.1180 1.0393 7609 .5168 WITHIN GROUPS 291 397.4871 1.3659 TOTAL 294 400.6051
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 58 5. .2112 1.1696 .1536 2.2500 7.0000 4.9037 TO 5.5187 Grp 2 179 5. .3087 1.1946 .0893 1.0000 7.0000 5.1325 TO 5.4849 Grp 3 9 5. .6944 1.4565 .4 855 2.2500 7.0000 4.5748 TO 6.8140 Grp 4 49 5. .4745 1.0055 .1436 3.2500 7.0000 5.1857 TO 5.7633 TOTAL 295 5, .3288 1.1673 .0680 1.0000 7.0000 5.1951 TO 5.4626
231
FIXED EFFECTS MODEL 1.1687 .0680 RANDOM EFFECTS MODEL .0680
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0059 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/SumVariances) = .3579, P = .009 (Approx.) Bartlett-Box F = .997 , P = .3 93 Maximum Variance / Minimum Variance 2.098
- - - - - - - - - - - - - - O N E W A Y - - - - --- - - - - - - - - - - - - -Variable F4 (Environmental) By Variable MARITAL marital status MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS..
0.8264 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL _ _ O N E W A Y Variable F5 (Perceptuals) (NOT SIGNIFICANT)
5.1949 5.1123
TO TO
5.4627 5.5454
By Variable MARITAL marital status ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
3 282 285
SUM OF SQUARES
1.3523 262.0918 263 .4441
MEAN SQUARES
.4508
.9294
RATIO PROB.
.4850 .6930
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 56 5.5565 1.0779 .1440 2.3333 7.0000 5.2679 TO 5.8452 Grp 2 175 5.6962 .9121 .0690 3.0000 7.0000 5.5601 TO 5.8323 Grp 3 7 5.8810 1.4100 .5329 3.3333 7.0000 4.5769 TO 7.1850 Grp 4 48 5.7396 .9396 .1356 3.5000 7.0000 5.4667 TO 6.0124 TOTAL 286 5.6807 .9614 .0569 2.3333 7.0000 5.5688 TO 5.7926
FIXED EFFECTS ! MODEL .9641 .0570 5.5684 TO 5.7929 RANDOM EFFECTS ; MODEL .0570 5.4992 TO 5.8621
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0090 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .4087, P = .000 (Approx.) Bartlett-Box F s 1.577 , P = .193 Maximum Variance / Minimum Variance 2.390
O N E W A Y Variable F5 (Perceptuals) By Variable MARITAL marital status MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS..
0.6817 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL _ - _ _ - _ - - _ _ _ 0 N E W A Y - - - - - - - - - - - - - - - - - - - - - -Variable F6 (Self-Efficacy) (NOT SIGNIFICANT) By Variable MARITAL marital status
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
3 284 287
SUM OF SQUARES
4.1513 287.9043 292.0556
MEAN SQUARES
1.3838 1.0137
RATIO PROB.
1.3650 .2537
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF
Grp 1 56 4.6280 1.0474 .1400 2.6667 6.3333 4.3475 TO Grp 2 175 4.8248 .9701 .0733 1.8333 7.0000 4.6800 TO Grp 3 9 4.2963 1.2184 .4061 2.1667 6.1667 3.3597 TO Grp 4 48 4.8715 1.0514 .1518 3.1667 7.0000 4.5662 TO TOTAL 288 4.7778 1.0088 .0594 1.8333 7.0000 4.6608 TO
FIXED EFFECTS MODEL 1.0069 .0593 4.6610 TO RANDOM EFFECTS MODEL .0806 4.5213 TO
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0068 4.5213 TO
Tests for Homogeneity of Variances Cochrans C = Max. Variance/Sum(Variances) = Bartlett-Box F = Maximum Variance / Minimum Variance
_ _ _ _ _ _ _ _ _ _ O N E W A Y - - - - - - - - - -Variable F6 (Self-Efficacy) By Variable MARITAL marital status MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN (J)-MEAN (I) IS.
.3208,
.488 , 1.578
P = P =
.121
.691 (Approx.)
4.9085 4.9695 5.2329 5.1768 4.8948 4.8946 5.0343
232
0.7120 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL - - - - - - - - - - - - - - O N E W A Y - - - - - - - - - -
Variable F7 (Insurance) (NOT SIGNIFICANT) By Variable MARITAL marital status
ANALYSIS OF VARIANCE
SOURCE D.F. SUM OF SQUARES
MEAN SQUARES RATIO PROB.
BETWEEN GROUPS 3 .9817 .3272 1552 .9263 WITHIN GROUPS 284 598.9627 2.1090 TOTAL 287 599.9444
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 56 6 .0536 1.4228 .1901 1.0000 7.0000 5.6725 TO 6.4346 Grp 2 174 6 .0259 1.4478 .1098 1.0000 7.0000 5.8092 TO 6.2425 Grp 3 9 6 .1667 1.9685 .6562 1.0000 7.0000 4.6535 TO 7.6798 Grp 4 49 5 .8980 1.3993 .1999 2.5000 7.0000 5.4960 TO 6.2999 TOTAL 288 6 .0139 1.4458 .0852 1.0000 7.0000 5.8462 TO 6.1816
FIXED EFFECTS MODEL 1.4522 .0856 5.8454 TO 6.1823 RANDOM EFFECTS MODEL .0856 5.7416 TO 6.2862
WARNING ~ BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0327 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .3893, P = .001 (Approx.) Bartlett-Box F = .658 , P = .578 Maximum Variance / Minimum Variance 1.979 _ _ _ _ _ _ _ _ _ _ _ O N E W A Y - - - - - - - - - - - - - - - - - - .
Variable F7 (Insurance) By Variable MARITAL marital status MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
1.0269 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
- - O N E W A Y _ _ _ _ _ Variable F8 (Communication) (NOT SIGNIFICANT) By Variable MARITAL marital status
ANALYSIS OF VARIANCE
SUM OF MEAN SOURCE D.F. SQUARES SQUARES ]
BETWEEN GROUPS 3 2.5580 .8527 1 WITHIN GROUPS 291 132.0017 .4536 TOTAL 294 134.5597
.4536
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM
Grp 1 58 6 .4425 .8293 .1089 3.6667 Grp 2 181 6 .5046 .6389 .0475 4.0000 Grp 3 9 6 .2593 1.0379 .3460 4.3333 Grp 4 47 6 .7021 .4827 .0704 5.3333 TOTAL 295 6 .5164 .6765 .0394 3.6667
F RATIO
F PROB.
1.8797 .1331
MAXIMUM 95 PCT CONF INT FOR MEAN
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
.6735 .0392 .0689
0.0073 RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .4477, P = .000 (ADDrox ) Bartlett-Box F = 6.230 , P = .000 Maximum Variance / Minimum Variance 4.623
- O N E W A Y _ _ _ _ Variable F8 (Communication) By Variable MARITAL marital status MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS .
0.4762 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
- - - - - - - - - - O N E W A Y - -Variable F9 (Technology) (NOT SIGNIFICANT) By Variable MARITAL marital status
ANALYSIS OF VARIANCE
7 , .0000 6.2245 TO 6.6606 7, .0000 6.4109 TO 6.5983 7, .0000 5.4615 TO 7.0570 7, .0000 6.5604 TO 6.8439 7, .0000 6.4389 TO 6.5939
6.4392 TO 6.5936 6.2972 TO 6.7356
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
3 291 294
SUM OF SQUARES
2.8114 330.3110 333.1224
MEAN SQUARES
.9371 1.1351
RATIO PROB.
.8256 .4806
233
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 58 5.6897 1.0704 .1405 2.3333 7.0000 5.4082 TO 5.9711 Grp 2 180 5.7556 1.0330 .0770 2.0000 7.0000 5.6036 TO 5.9075 Grp 3 8 6.2083 1.2716 .4496 3.3333 7.0000 5.1452 TO 7.2714 Grp 4 49 5.9048 1.1426 .1632 3.0000 7.0000 5.5766 TO 6.2330 TOTAL 295 5.7797 1.0645 .0620 2.0000 7.0000 5.6577 TO 5.9016
FIXED EFFECTS : MODEL 1.0654 .0620 5.6576 TO 5.9017 RANDOM EFFECTS 1 MODEL .0620 5.5823 TO 5.9771
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0036 _ - - - - O N E W A Y - - - - - - - - - - - _ _ _ _ Variable F9 (Technology) By Variable MARITAL marital status MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.7534 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
O N E W A Y - -Variable F10 (Opportunity) (NOT SIGNIFICANT) By Variable MARITAL marital status
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
3 282 285
SUM OF SQUARES
3.0207 364.5153 367.5361
MEAN SQUARES
1.0069 1.2926
RATIO PROB.
.7790 .5065
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 54 3.6389 1 1902 .1620 1.5000 6.2500 3.3140 TO 3.9638 Grp 2 175 3.4329 1 1251 .0851 1.2500 7.0000 3.2650 TO 3.6007 Grp 3 9 3.8056 1 1910 .3970 2.0000 6.0000 2.8901 TO 4.7210 Grp 4 48 3.5885 1 1091 .1601 1.2500 6.0000 3.2665 TO 3.9106 TOTAL 286 3.5096 1 1356 .0671 1.2500 7.0000 3.3774 TO 3.6418
FIXED EFFECTS MODEL 1 1369 .0672 3.3773 TO 3.6419 RANDOM EFFECTS MODEL .0672 3.2957 TO 3.7236
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0053 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .2661, P = 1.000 (Approx.) Bartlett-Box F = .118 , P = .950 Maximum Variance / Minimum Variance 1.153
- - - O N E W A Y - - -Variable F10 (Opportunity) By Variable MARITAL marital status MULTIPLE RANGE TEST SCHEFFE PROCEDURE RANGES FOR THE 0.050 LEVEL -
3.98 3.98 3.98 THE RANGES ABOVE ARE TABLE RANGES. THE VALUE ACTUALLY COMPARED WITH MEAN(J)-MEAN(I) IS..
0.8039 * RANGE * DSQRT(1/N(I) + 1/N(J)) NO TWO GROUPS ARE SIGNIFICANTLY DIFFERENT AT THE 0.050 LEVEL
O N E W A Y Variable F1 (Reputation) (NOT SIGNIFICANT) By Variable MARITAL2
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 288 289
SUM OF SQUARES
.0127 272.8464 272.8591
MEAN SQUARES
.0127
.9474
RATIO PROB.
.0134 .9079
GROUP
Grp 1 Grp 2 TOTAL
COUNT MEAN
179 5.1913 111 5.2050 290 5.1966
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
.9234 1.0491 .9717 .9733
STANDARD ERROR
.0690
.0996
.0571
.0572
.0572
MINIMUM
2.1250 2.1250 2.1250
6.7500 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0068 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5634, P = .127 (Approx.) Bartlett-Box F = 2.242 , P = .134 Maximum Variance / Minimum Variance 1.291
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS.
95 PCT CONF INT FOR MEAN
5.0551 TO 5.0076 TO 5.0842 TO 5.0841 TO 4.4703 TO
5.3275 5.4023 5.3089 5.3090 5.9228
234
. . . . . - . - . . . - - O N E W A Y - - - - - - - -Variable F2 (Physician Socio-Demographic) (NOT SIGNIFICANT) By Variable MARITAL2
ANALYSIS OF VARIANCE
SOURCE SUM OF SQUARES
MEAN SQUARES
F RATIO
F PROB.
BETWEEN GROUPS 1 1.2002 1.2002 8568 .3554 WITHIN GROUPS 278 389.4426 1.4009 TOTAL 279 390.6429
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 175 3 .4136 1.1574 .0875 1.2500 6.5000 3.2409 TO 3.5863 Grp 2 105 3 .5488 1.2262 .1197 1.1250 6.3750 3.3115 TO 3.7861 TOTAL 280 3 .4643 1.1833 .0707 1.1250 6.5000 3.3251 TO 3.6035
FIXED EFFECTS MODEL 1.1836 .0707 3.3250 TO 3.6035 RANDOM EFFECTS MODEL .0707 2.5655 TO 4.3630
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0015 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5288, P = .497 (Approx.) O N E W A Y
Variable F3 (Economic) (NOT SIGNIFICANT) By Variable MARITAL2
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 279 280
SUM OF SQUARES
1.5771 347.6981 349.2752
MEAN SQUARES
1.5771 1.2462
RATIO PROB.
1.2655 .2616
GROUP COUNT MEAN STANDARD DEVIATION
STANDARD ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 172 3.8397 1.1145 .0850 1.0000 Grp 2 109 3.9934 1.1192 .1072 1.1429 TOTAL 281 3.8993 1.1169 .0666 1.0000
FIXED EFFECTS MODEL 1.1163 .0666 RANDOM EFFECTS MODEL .0757
6.8571 6.2857 6.8571
0.0025 RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5021, P = .961 (Approx.) Bartlett-Box F = .002 , P = .962 Maximum Variance / Minimum Variance 1.008
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. O N E W A Y - - - -
Variable F4 (Environmental) (NOT SIGNIFICANT) By Variable MARITAL2
ANALYSIS OF VARIANCE
3.6720 TO 3.7810 TO 3.7682 TO 3.7 682 TO 2.9369 TO
4.0075 4.2059 4.0305 4.0304 4.8617
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 293 294
SUM OF SQUARES
.1849 400.4202 400.6051
MEAN SQUARES
.1849 L.3666
RATIO PROB.
.1353 .7133
GROUP
Grp 1 Grp 2 TOTAL
COUNT MEAN
179 5.3087 116 5.3599 295 5.3288
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.1946 1.1283 1.1673 1.1690
STANDARD ERROR
.0893
.1048
.0680
.0681
.0681
MINIMUM
1.0000 2.2500 1.0000
MAXIMUM
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0084 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5285, P = .490 (Approx.) Bartlett-Box F = .449 , P = .503 Maximum Variance / Minimum Variance 1.121
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. __ _ _ _ _ _ O N E W A Y - - - - - _ _ _ _ _ _ Variable F5 (Perceptuals) (NOT SIGNIFICANT) By Variable MARITAL2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
5.1325 TO 5.1524 TO 5.1951 TO 5.1949 TO 4.4640 TO
5.4849 5.5674 5.4626 5.4628 6.1936
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 284 285
SUM OF SQUARES
.1089 263.3352 263.4441
MEAN SQUARES
.1089
.9272
F RATIO
F PROB.
.1174 .7321
235
GROUP
Grp 1 Grp 2 TOTAL
COUNT
175 111 286
MEAN
5.6962 5.6562 5.6807
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
.9121 1.0382 .9614 .9629
STANDARD ERROR
.0690
.0985
.0569
.0569
.0569
3.0000 2.3333 2.3333
MAXIMUM
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0060 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5644, P = .124 (Approx.) Bartlett-Box F = 2.290 , P = .130
- - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - - - - - - -Variable F6 (Self-Efficacy) (NOT SIGNIFICANT) By Variable MARITAL2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
5.5601 TO 5.4609 TO 5.5688 TO 5.5686 TO 4.9572 TO
5.8323 5.8514 5.7926 5.7927 6.4041
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 286 287
SUM OF SQUARES
.9846 291.0710 292.0556
MEAN SQUARES
.9846 1.0177
RATIO PROB.
.9674 .3262
GROUP
Grp 1 Grp 2 TOTAL
COUNT MEAN
175 4.8248 113 4.7050 288 4.7778
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
.9701 1.0663 1.0088 1.0088
STANDARD ERROR
.0733
.1003
.0594
.0594
.0594
1.8333 2.1667 1.8333
MAXIMUM
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0002 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5471, P = .259 (Approx.) Bartlett-Box F = 1.229 , P = .268 Maximum Variance / Minimum Variance 1.208
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. O N E W A Y
Variable F7 (Insurance) (NOT SIGNIFICANT) By Variable MARITAL2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
4.6800 TO 4.5063 TO 4.6608 TO 4.6608 TO 4.0224 TO
4.9695 4.9038 4.8948 4.8948 5.5331
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 286 287
SUM OF SQUARES
.0630 599.8814 599.9444
MEAN SQUARES
.0630 2.0975
RATIO PROB.
.0300 .8625
GROUP
Grp 1 Grp 2 TOTAL
COUNT MEAN
174 6.0259 114 5.9956 288 6.0139
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.4478 1.4490 1.4458 1.4483
STANDARD ERROR
.1098
.1357
.0852
.0853
.0853
MINIMUM
1.0000 1.0000 1.0000
MAXIMUM
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0148 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5004, P = .992 (Approx.) Bartlett-Box F = .000 , P = .992 Maximum Variance / Minimum Variance 1.002
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. - - - - - - _ - - _ _ _ - _ _ _ 0 N E W A Y - - - - - - - - - - - - - - - - -Variable F8 (Communication) (NOT SIGNIFICANT) By Variable MARITAL2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
5.8092 TO 5.7267 TO 5.8462 TO 5.8459 TO 4.9295 TO
6.2425 6.2645 6.1816 6.1819 7.0982
SUM OF MEAN F F SOURCE D.F. SQUARES SQUARES RATIO PROB.
BETWEEN GROUPS 1 .0650 .0650 1416 .7070 WITHIN GROUPS 293 134.4947 .4590 TOTAL 294 134.5597
STANDARD STANDARD GROUP COUNT MEAN DEVIATION ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAT
Grp 1 181 6.5046 .6389 .0475 4.0000 7 .0000 6.4109 TO 6.5983 Grp 2 114 6.5351 .7349 .0688 3.6667 7 .0000 6.3987 TO 6.6714 TOTAL 295 6.5164 .6765 .0394 3.6667 7 .0000 6.4389 TO 6.5939
FIXED EFFECTS MODEL .6775 .0394 6.4387 TO 6.5940 RANDOM EFFECTS MODEL .0394 6.0152 TO 7.0176
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0028 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5696, P = .091 (Approx.) Bartlett-Box F = 2.7 62 , P = .097
236
Maximum Variance / Minimum Variance 1.323 NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ - _ - _ - _ _ - O N E W A Y - - - - - - - - - - - - - -Variable F9 (Technology) (NOT SIGNIFICANT) By Variable MARITAL
ANALYSIS OF VARIANCE
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 293 294
SUM OF SQUARES
.2683 332.8541 333.1224
MEAN SQUARES
.2683 1.1360
RATIO PROB.
.2362 .6273
GROUP
Grp 1 Grp 2 TOTAL
COUNT MEAN
180 5.7556 115 5.8174 295 5.7797
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.0330 1.1154 1.0645 1.0658
STANDARD ERROR
.0770
.1040
.0620
.0621
.0621
MINIMUM
2 . 0 0 0 0 2.3333 2 . 0 0 0 0
MAXIMUM
7.0000 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0062 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5383, P = .353 (Approx.) Bartlett-Box F = .825 , P = .364 Maximum Variance / Minimum Variance 1.166
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. O N E W A Y
Variable F10 (Opportunity) (NOT SIGNIFICANT) By Variable MARITAL2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
5.6036 TO 5.6113 TO 5.6577 TO
5.6575 TO 4.9912 TO
5.9075 6.0234 5.9016 5.9018 6.5682
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 284 285
SUM OF SQUARES
2.6566 364.8794 367.5361
MEAN SQUARES
2.6566 1.2848
RATIO PROB.
2.0678 .1515
GROUP
Grp 1 Grp 2 TOTAL
COUNT MEAN
175 3.4329 111 3.6306 286 3.5096
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.1251 1.1466 1.1356 1.1335
STANDARD ERROR
.0851
.1088
.0671
.0670
.0990
1.2500 1.2500 1.2500
7.0000 6.2500 7.0000
0.0101 RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C - Max. Variance/Sum(Variances) = .5094, P = .823 (Approx.) Bartlett-Box F = .048 , P = .827 Maximum Variance / Minimum Variance 1.038
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ _ _ _ - - O N E W A Y Variable F1 (Reputation) (NOT SIGNIFICANT) By Variable PLACE2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
3.2650 TO 3.4150 TO 3.3774 TO
3.3777 TO 2.2521 TO
3.6007 3.8463 3.6418 3.6415 4.7671
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 288 289
SUM OF SQUARES
.9234 274.5391 275.4625
MEAN SQUARES
.9234
.9533
RATIO PROB.
.9687 .3258
GROUP MEAN STANDARD
DEVIATION STANDARD
ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 Grp 2 TOTAL
139 151 290
5.1412 5.2541 5.2000
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
.9884
.9652
.9763
.9764
.0838
.0785
.0573
.0573
.0573
2.1250 2.5000 2.1250
6.8750 7.0000 7.0000
WARNING - BETWEEN COMPONENT VARIANCE IS NEGATIVE IT WAS REPLACED BY 0.0 IN COMPUTING ABOVE RANDOM EFFECTS MEASURES
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE -0.0002 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5119, P = .776 (Approx.) Bartlett-Box F = .081 , P = .776 Maximum Variance / Minimum Variance 1.049
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ _ _ _ _ _ _ _ 0 N E W A Y - - - - - - - - - - - - - - - - - - - -Variable F2 (Physician Socio-Demographic) (SIGNIFICANT) By Variable PLACE2
ANALYSIS OF VARIANCE
4.9754 TO 5.0989 TO 5.0872 TO 5.0872 TO 4.4715 TO
5.3069 5.4093 5.3128 5.3128 5.9285
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
1 278 279
SUM OF SQUARES
19.6265 372.8565 392.4830
MEAN SQUARES
19.6265 1.3412
F RATIO
F PROB.
14.6334 .0002
237
GROUP
Grp 1 Grp 2 TOTAL
COUNT
131 149 280
MEAN
3.1842 3.7148 3.4665
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
STANDARD DEVIATION
1.1413 1.1727 1.1861 1.1581
STANDARD ERROR
.0997
.0961
.0709
.0692
.2658
MINIMUM
1.1250 1.2500 1.1250
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5136, P = Bartlett-Box F = .102 , P = Maximum Variance / Minimum Variance 1.056
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ - - - - - - - - - - O N E W A Y - - - - - - - - - - - - - -Variable F3 (Economic) (SIGNIFICANT) By Variable PLACE2
ANALYSIS OF VARIANCE
6.5000 6.3750 6.5000
0.1312
.7 49 (Approx.)
.750
95 PCT CONF INT FOR MEAN
2.9869 TO 3.5249 TO 3.3270 TO 3.3303 TO .0895 TO
3.3814 3.9046 3.6060 3.6028 6.8435
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
GROUP
Grp 1 Grp 2 TOTAL
131 150 281
D.F.
1 279 280
MEAN
3.6423 4.1324 3.9039
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
SUM OF SQUARES
16.7946 332.1825 348.9771
STANDARD DEVIATION
1.0709 1.1086 1.1164 1.0912
MEAN SQUARES
16.7946 1.1906
STANDARD ERROR
.0936
.0905
.0666
.0651
.2455
F RATIO
F PROB.
14.1058 .0002
MINIMUM
1.1429 1.0000 1.0000
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5173, P = Bartlett-Box F = .165 , P = Maximum Variance / Minimum Variance 1.072
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. . . . _ _ _ _ _ _ _ _ - - O N E W A Y - - - - - - - - - - - - -Variable F4 (Environmental) (SIGNIFICANT) By Variable PLACE2
ANALYSIS OF VARIANCE
.683
.684
MAXIMUM
6.1429 6.8571 6.8571
0.1116
(Approx.)
95 PCT CONF INT FOR MEAN
3.4572 TO 3.9535 TO 3.7728 TO 3.7758 TO .7844 TO
3.8274 4.3112 4.0350 4.0321 7.0235
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
GROUP
Grp 1 Grp 2 TOTAL
140 156 296
D.F.
1 294 295
MEAN
5.0161 5.6346 5.3421
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
SUM OF SQUARES
28.2294 375.3244 403.5538
STANDARD DEVIATION
1.1510 1.1106 1.1696 1.1299
MEAN SQUARES
28.2294 1.2766
STANDARD ERROR
.0973
.0889
.0680
.0657
.3097
F RATIO
F -PROB.
22.1127 .0000
MINIMUM
1.7500 1.0000 1.0000
MAXIMUM
7.0000 7.0000 7.0000
0 . 1 8 2 6 RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Vari.ances) == .5179, P = .665 (Approx.) Bartlett-Box F = .187 , P = .665 Maximum Variance / Minimum Variance 1.074
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ O N E W A Y Variable F5 (Perceptuals) (SIGNIFICANT) By Variable PLACE2
ANALYSIS OF VARIANCE
95 PCT CONF INT FOR MEAN
4.8237 TO 5.4590 TO 5.2083 TO 5.2128 TO 1.4072 TO
5.2084 5.8103 5.4759 5.4713 9.2770
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
Grp 1 Grp 2 TOTAL
132 154 286
D.F.
1 284 285
MEAN
5.5404 5.8063 5.6836
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
SUM OF SQUARES
5.0243 259.3662 264.3905
STANDARD DEVIATION
.9311
.9762
.9632
. 9556
MEAN SQUARES
5.0243 .9133
STANDARD ERROR
.0810
.0787
.0570
.0565
.1332
F RATIO
F PROB.
5.5015 .0197
MINIMUM
2.6667 2.3333 2.3333
MAXIMUM
7 .0000 7.0000 7.0000
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0289 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5237, P = .573 (Approx.) Bartlett-Box F = .314 , P = .575 Maximum Variance / Minimum Variance 1.099
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS.
95 PCT CONF INT FOR MEAN
5.3801 TO 5.6509 TO 5.5715 TO
5.5723 TO 3.9913 TO
5.7007 5.9617 5.7957 5.7948 7.3759
238
- - - - - O N E W A Y - - -Variable F6 (Self-Efficacy) (NOT SIGNIFICANT) By Variable PLACE2
ANALYSIS OF VARIANCE
SOURCE D.F. SUM OF
SQUARES MEAN
SQUARES F
RATIO F
PROB.
BETWEEN GROUPS WITHIN GROUPS TOTAL
1 287 288
2.2086 296.0651 298.2737
2.2086 1.0316
2.1410 .1445
GROUP COUNT MEAN STANDARD
DEVIATION STANDARD
ERROR MINIMUM 95 PCT CONF INT FOR MEAN
Grp 1 Grp 2 TOTAL
135 154 289
4.6938 4.8690 4.7872
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
1.0232 1.0090 1.0177 1.0157
.0881
.0813
.0599
.0597
.0876
2.1667 1.8333 1.8333
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5070, P = Bartlett-Box F = .028 , P = Maximum Variance / Minimum Variance 1.028
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ O N E W A Y
Variable F7 (Insurance) (SIGNIFICANT) By Variable PLACE2
ANALYSIS OF VARIANCE
.867
.868
7.0000 7.0000 7.0000
0 . 0 0 8 2
(Approx.)
4.5197 TO 4.7084 TO 4.6694 TO
4.6696 TO 3.6738 TO
4.8680 5.0297 4.9050 4.9048 5.9005
SOURCE D.F. SUM OF
SQUARES MEAN
SQUARES F
RATIO F
PROB.
BETWEEN GROUPS WITHIN GROUPS TOTAL
1 287 288
8.2424 592.6711 600.9135
8.2424 2.0651
3.9914 .0467
GROUP COUNT MEAN STANDARD
DEVIATION STANDARD
ERROR MAXIMUM 95 PCT CONF INT FOR MEAN
137 5.8394 1. ,6246 .1388 1. ,0000 7, .0000 5.5649 TO 6, .1139 152 6.1776 1. .2441 .1009 1. .0000 7, .0000 5.9783 TO 6. .3770 289 6.0173 1. ,4445 .0850 1. ,0000 7, .0000 5.8501 TO 6. .1845
FIXED EFFECTS MODEL 1. .4370 .0845 5.8509 TO 6. .1837 RANDOM EFFECTS MODEL .1692 3.8671 TO 8. ,1675
Grp 1 Grp 2 TOTAL
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .6304, P = Bartlett-Box F = 10.134 , P = Maximum Variance / Minimum Variance 1.705
_ _ _ _ _ _ _ _ _ - O N E W A Y -Variable F8 (Communication) (NOT SIGNIFICANT) By Variable PLACE2
ANALYSIS OF VARIANCE
.001
. 0 0 1
0.0429
(Approx.)
SOURCE D.F. SUM OF
SQUARES MEAN
SQUARES F
RATIO F
PROB.
BETWEEN GROUPS WITHIN GROUPS TOTAL
1 294 295
.6995 133.8827 134.5822
.6995
.4554 1.5361 .2162
GROUP MEAN STANDARD
DEVIATION STANDARD
ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 Grp 2 TOTAL
139 157 296
6.4652 6.5626 6.5169
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
.6841
.6665
.6754
.6748
.0580
.0532
.0393
.0392
.0487
4.0000 3.6667 3.6667
7.0000 7.0000 7 . 0 0 0 0
0.0017 RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5130, P = .753 (Approx.) Bartlett-Box F = .099 , P = .753 Maximum Variance / Minimum Variance 1.053
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 0 N E W A Y - - - - ~ - - - - - - - - - - - - -Variable F9 (Technology) (SIGNIFICANT) By Variable PLACE2
ANALYSIS OF VARIANCE
6.3505 TO 6.4576 TO 6.4396 TO
6.4397 TO 5.8984 TO
6.5800 6.6677 6.5942 6.5941 7.1354
SOURCE D.F. SUM OF
SQUARES MEAN
SQUARES F
RATIO F
PROB.
BETWEEN GROUPS WITHIN GROUPS TOTAL
1 294 295
16.7782 319.0953 335.8735
16.7782 1.0854
15.4587 .0001
GROUP STANDARD
DEVIATION STANDARD
ERROR 95 PCT CONF INT FOR MEAN
Grp 1 Grp 2 TOTAL
140 156 296
5.5381 6.0150 5.7894
FIXED EFFECTS MODEL
1.0940 . 9927
1.0670 1.0418
.0925
.0795
. 0 6 2 0
. 0606
2.3333 2 . 0 0 0 0 2 . 0 0 0 0
7.0000 7 . 0 0 0 0 7.0000
5.3553 TO 5.8580 TO 5.6674 TO
5.6702 TO
5.7209 6.1720 5.9115 5.9086
239
0.1063 RANDOM EFFECTS MODEL .2387
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5484, P = .240 (Approx.) Bartlett-Box F = 1.381 , P = .240 Maximum Variance / Minimum Variance 1.214
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS. _ - - _ _ - - _ - _ O N E W A Y - ~ - - ~ - - - - - - - - - - - - - - - -
Variable F10 (Opportunity) (SIGNIFICANT) By Variable PLACE2
ANALYSIS OF VARIANCE
2.7560 TO 8 . 8 2 2 8
SOURCE
BETWEEN GROUPS WITHIN GROUPS TOTAL
D.F.
1 285 286
SUM OF SQUARES
5.2068 367.2854 372.4922
MEAN SQUARES
5.2068 1.2887
RATIO PROB.
4.0403 .0454
GROUP COUNT MEAN STANDARD
DEVIATION STANDARD
ERROR MINIMUM MAXIMUM 95 PCT CONF INT FOR MEAN
Grp 1 Grp 2 TOTAL
135 152 287
3.3519 3.6217 3.4948
FIXED EFFECTS MODEL RANDOM EFFECTS MODEL
1.1339 1.1364 1.1412 1.1352
.0976
.0922
.0674
.0670
.1350
1.5000 1.0000 1.0000
6.7500 7.0000 7.0000
RANDOM EFFECTS MODEL - ESTIMATE OF BETWEEN COMPONENT VARIANCE 0.0274 Tests for Homogeneity of Variances
Cochrans C = Max. Variance/Sum(Variances) = .5011, P = .979 (Approx.) Bartlett-Box F = .001 , P = .979 Maximum Variance / Minimum Variance 1.004
NO RANGE TESTS PERFORMED WITH FEWER THAN THREE NON-EMPTY GROUPS.
3.1588 TO 3.4396 TO 3.3622 TO 3.3629 TO 1.7788 TO
3.5449 3.8038 3.6274 3.6267 5.2107
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REGRESSION ANALYSIS LISTING
267
268
REGRESSION ANALYSIS
REGRESSION /VARIABLES GENDER AGE EDUC INCOME REP DRBK ECON ENIV PRECEP SELF INS COMM SUPP OPPORT /DESCRIPTIVES DEFAULT /DEPENDENT REP DRBK ECON ENIV PRECEP SELF INS COMM SUPP OPPORT /METHOD STEPWISE.
* * * M U L T I P L E R E G R E S S I O N
Listwise Deletion of Missing Data
Mean Std Dev Label
GENDER 1. .791 .407 gender of respondent AGE 3. ,289 1, .176 age EDUC 4, .639 1, .507 educational background INCOME 5, .482 2. .180 yearly household income REP 5, .496 1, .021 reputation DRBK 3, .452 1, .396 Physician socio-demographic ECON 4. .169 1, .177 economic considerations EN IV 5, .280 1, .167 environmental factors PRECEP 5, .652 .930 perceptuals SELF 4, • 870 l! .028 patient self-efficacy INS 5, . 982 1, .481 insurance COMM 6, .514 .672 doctor patient communication SUPP 5 .748 1, .089 support (technology and staff) OPPORT 3 .465 1, .149 opportunity
M U L T I P L E R E G R E S S I O N
N of Cases =
Correlation:
249
GENDER AGE EDUC INCOME REP DRBK ECON
GENDER 1.000 -.075 -.130 -.004 .067 .123 -.008 AGE -.075 1.000 .200 .232 .026 -.031 -.015 EDUC -.130 .200 1.000 .398 -.115 -.200 -.237 INCOME -.004 .232 .398 1.000 .026 -.125 -.266 REP .067 .026 -.115 .026 1.000 .480 .376 DRBK .123 -.031 -.200 -.125 .480 1.000 .318 ECON -.008 -.015 -.2:37 - .266* .376 .318 1.000 EN IV .151 -.100 -.191 -.110 .414 .467 .388 PRECEP .082 -.003 -.239 -.117 .490 .538 .335 SELF .176 .091 -.091 .004 .124 .115 .126 INS .101 -.160 -.016 -.049 .146 .165 .169 COMM .158 -.046 .046 -.016 .166 .105 .141 SUPP .123 -.057 -.212 -.082 .470 .520 .359 OPPORT -.063 -.136 -.218 -.179 .273 .341 .347
* * * * M U L T I P L E R E G R E S S I O N * * • * EN IV PRECEP SELF INS COMM SUPP OPPORT
GENDER .151 .($82 .176 .101 .158 .123 -.063 AGE -.100 -.003 .091 -.160 -.046 -.057 -.136 EDUC -.191 -.239 -.091 -.016 .046 -.212 -.218 INCOME -.110 -.117 .004 -.049 -.016 -.082 -.179 REP .414 .490 .124 .146 .166 .470 .273 DRBK .467 .538 .115 .165 .105 .520 .341 ECON .388 .335 .126 .169 .141 .359 .347 EN IV 1.000 .462 .173 .331 .228 .627 .181 PRECEP .462 1.000 .205 .239 .368 .619 .163 SELF .173 .205 1.000 .074 .247 .192 -.122 INS .331 .239 .074 1.000 . 198 .245 .054 COMM .228 .368 .247 .198 1.000 .321 -.072 SUPP .627 .619 .192 .245 .321 1.000 .186 OPPORT .181 .163 -.122 .054 -.072 .186 1.000
* • • • M U L T I P L E R E G R E S S I O N * • • *
Equation Number 1 Dependent Variable.. REP reputation
Block Number 1. Method: Stepwise Criteria PIN .0500
No variables entered/removed for this block.
POUT .1000
269
» * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 2 Dependent Variable.. DRBK Physician socio-demographic
Block Number 1. Method: Stepwise Criteria PIN .0500 POUT .1000
Variable(s) Entered on Step Number 1.. EDUC educational background
Multiple R .20022 R Square .04009 Adjusted R Square .03620 Standard Error 1.37069
Analysis of Variance DF
Regression 1 Residual 247
F = 10.31559
Sum of Squares 19.38081
464.06048
Signif F = .0015
Mean Square 19.38081 1.87879
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 2 Dependent Variable.. DRBK Physician socio-demographic
Variables in the Equation
Variable B SE B Beta T Sig T
EDUC (Constant)
Variable
-.185460 4.312476
.057744
.281580 -.200223
GENDER .098407 .099589 .983096 AGE .009120 .009120 .959931 INCOME -.053704 -.050283 .841506
-3.212 .0015 15.315 .0000
- Variables not in the Equation
Beta In Partial Min Toler T Sig T
1.570 .1177 .143 .8864
-.790 .4305
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 3 Dependent Variable.. ECON economic considerations
* * * * * * * * * * * * * * * * * * * * * * * *
Block Number 1. Method: Stepwise Criteria PIN .0500 POUT .1000
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 3 Dependent Variable.. ECON economic considerations
Variable(s) Entered on Step Number 1.. INCOME yearly household income
Multiple R .26607 R Square .07079 Adjusted R Square .06703 Standard Error 1.13663
Analysis of Variance DF
Regression 1 Residual 247
F = 18.81774
Sum of Squares 24.31104 319.10462
Signif F = .0000
Mean Square 24.31104 1.29192
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 3 Dependent Variable.. ECON economic considerations
Variable
INCOME (Constant)
-.143647 4.956140
Variables in the Equation --
B SE B Beta
-.266067 .033114 .195298
T Sig T
-4.338 .0000 25.377 .0000
270
Variable
GENDER AGE EDUC
- Variables not in the Equation
Beta In Partial Min Toler
-.008670 -.008995 .999982 .049808 .050265 .946336
-.155488 -.147968 .841506
T Sig T
-.141 .8879 .789 .4307
-2.347 .0197
M U L T I P L E R E G R E S S I O N
Equation Number 3 Dependent Variable.. ECON economic considerations
Variable(s) Entered on Step Number 2.. EDUC educational background
Multiple R .30189 R Square .09114 Adjusted R Square .08375 Standard Error 1.12640
Analysis of Variance DF
Regression 2 Residual 246
Sum of Squares 31.29772
312.11794
Mean Square 15.64886 1.26877
F = 12.33386 Signif F .0000
• * • * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 3 Dependent Variable.. ECON economic considerations
Variables in the Equation
Variable B SE B Beta T Sig T
INCOME EDUC (Constant)
Variable
GENDER AGE
-.110227 -.121387 5.335992
.035773
.051728
.252310
-.204166 -.155488
-3.081 .0023 -2.347 .0197 21.149 .0000
- Variables not in the Equation
Beta In Partial Min Toler
-.029193 -.030321 .068548 .069433
.825041
.817449
T Sig T
-.475 .6353 1.089 .2770
End Block Number PIN .050 Limits reached.
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 4 Dependent Vairiable.. ENIV environmental factors
Block Number 1. Method: Stepwise Criteria PIN .0500 .1000
M U L T I P L E R E G R E S S I O N * * * *
Dependent Variable.. ENIV environmental factors Equation Number 4
Variable(s) Entered on Step Number 1.. EDUC educational background
Multiple R .19099 R Square .03648 Adjusted R Square .03257 Standard Error 1.14745
Analysis of Variance DF
Regression 1 Residual 247
F = 9.35052
Sum of Squares 12.31137
325.21273
Mean Square 12.31137 1.31665
Signif F .0025
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 4 Dependent Variable.. ENIV environmental factors
Variable
EDUC (Constant)
Variables in the Equation --
B SE B Beta
-.190986
T Sig T
-.147815 5.965767
.048339
.235721 -3.058 25.309
.0025
.0000
271
Variable
GENDER AGE INCOME
- Variables not in the Equation
Beta In Partial Min Toler
.128534 .129833 .983096 -.064760 -.064639 .959931 -.040360 -.037718 .841506
T Sig T
2.054 .0411 -1.016 .3106 -.592 .5544
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 4 Dependent Variable.. ENIV environmental factors
Variable(s) Entered on Step Number 2.. GENDER gender of respondent
Multiple R .22960 R Square .05272 Adjusted R Square .04502 Standard Error 1.14005
Analysis of Variance DF
Regression 2 Residual 246
F = 6.84508
Sum of Squares 17.79334
319.73075
Signif F = .0013
Mean Square 8.89667 1.29972
* * * * * * * * M U L T I P L E R E G R E S S I O N
Equation Number 4 Dependent Variable.. ENIV environmental factors
Variables in the Equation
Variable B SE B Beta T Sig T
EDUC GENDER {Constant)
Variable
AGE INCOME
-.134881 .048439 -.174274 -2.785 .0058 .368159 .179263 .128534 2.054 .0411
5.246340 .421380 12.450 .0000
- Variables not in the Equation
Beta In Partial Min Toler
-.058295 -.058607 -.047744 -.044938
.946650
.825041
T Sig T
-.919 .3590 -.704 .4820
End Block Number 1 PIN = .050 Limits reached.
* * * * M U L T I P L E R E G R E S S I O N * * *
Equation Number 5 Dependent Variable.. PRECEP perceptuals
* * * * * * * * * * * * *
Block Number 1. Method: Stepwise Criteria PIN .0500 POUT .1000
M U L T I P L E R E G R E S S I O N
Equation Number 5 Dependent Variable.. PRECEP perceptuals
Variable(s) Entered on Step Number 1.. EDUC educational background
Multiple R .23859 R Square .05693 Adjusted R Square .05311 Standard Error .90545
Analysis of Variance DF 1
247 Regression Residual
Sum of Squares 12.22366
202.50012
Mean Square 12.22366
.81984
F = 14.90984 Signif F .0001
* * * * M U L T I P L E R E G R E S S I O N * * *
Equation Number 5 Dependent Variable.. PRECEP perceptuals
Variables in the Equation
Variable B SE B Beta T Sig T
EDUC (Constant)
-.147287 6.335141
.038144
.186006 -.238595 -3.861 .0001
34.059 .0000
272
Variable
GENDER AGE INCOME
- Variables not in the Equation
Beta In Partial Min Toler
.052150 .053246 .983096
.046787 .047203 .959931 -.025887 -.024453 .841506
T Sig T
.836 .4038
.741 .4593 -.384 .7016
End Block Number 1 PIN = .050 Limits reached.
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 6 Dependent Variable.. SELF patient self-efficacy * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
Block Number 1. Method: Stepwise Criteria PIN .0500 POUT .1000
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 6 Dependent Variable.. SELF patient self-efficacy
Variable(s) Entered on Step Number 1.. GENDER gender of respondent
Multiple R .17559 R Square .03083 Adjusted R Square .02691 Standard Error 1.01412
Analysis of Variance DF
Regression 1 Residual 247
Sum of Squares 8.08130
254.02280
Mean Square 8.08130 1.02843
F = 7.85788 Signif F .0055
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 6 Dependent Variable.. SELF patient self-efficacy
Variables in the Equation
Variable B SE B Beta T Sig T
GENDER (Constant)
Variable
AGE EDUC INCOME
.443206 4.076025
.158108
.290397 .175592 2.803 .0055
14.036 .0000
- Variables not in the Equation
Beta In Partial Min Toler
.105099 .106454 .994309 -.069182 -.069678 .983096 .004375 .004444 .999982
T Sig T
1.679 .0944 -1.096 .2744
.070 .9445
End Block Number 1 PIN = .050 Limits reached.
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 7 Dependent Variable.. INS insurance
* * * * * * * * * * * *
Block Number 1. Method: Stepwise Criteria PIN .0500 POUT .1000
M U L T I P L E R E G R E S S I O N
Equation Number 7 Dependent Variable. INS insurance
Variable(s) Entered on Step Number 1.. AGE age
Multiple R .16020 R Square .02566 Adjusted R Square .02172 Standard Error 1.46444
Analysis of Variance DF
Regression 1 Residual 247
F = 6.50622
Sum of Squares 13.95321
529.71546
Signif F = .0114
Mean Square 13.95321 2.14460
273
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 7 Dependent Variable.. INS insurance
Variables in the Equation
Variable B SE B Beta T Sig T
AGE (Constant)
Variable
-.201640 6.645152
.079052 -.160203
.276079 -2.551 .0114 24.070 .0000
- Variables not in the Equation
Beta In Partial Min Toler
GENDER .089122 .090031 .994309 EDUC .016229 .016109 .959931 INCOME -.012054 -.011880 .946336
T Sig T
1.418 .1575 .253 .8007
-.186 .8523
End Block Number 1 PIN = .050 Limits reached.
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 8 Dependent Variable.. COMM doctor patient communication
* * * * * * * * * * * * * * * * * * *
Block. Number 1. Method: Stepwise Criteria PIN .0500 POUT .1000
M U L T I P L E R E G R E S S I O N * * * *
Equation Number Dependent Variable.. COMM doctor patient communication
Variable(s) Entered on Step Numbejr 1.. GENDER gender of respondent
Multiple R .15810 R Square .02500 Adjusted R Square .02105 Standard Error .66485
Analysis of Variance DF
Regression 1 Residual 247
Sum of Squares 2.79901
109.17957
Mean Square 2.79901 .44202
F = 6.33227 Signif F .0125
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 8 Dependent Variable.. COMM doctor patient communication
Variables in the Equation
Variable B SE B Beta T Sig T
GENDER (Constant)
Variable
.260836 6.046857
.103654
.190383 .158101 2.516
31.762 .0125 .0000
- Variables not in the Equation
Beta In Partial Min Toler T Sig T
AGE -.034240 -.034577 EDUC .067876 .068157 INCOME -.014982 -.015173
.994309
.983096
.999982
-.543 1.071 -.238
.5879
.2850
.8121
End Block Number PIN = .050 Limits reached.
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 9 Dependent Variable.. SUPP support (technology and staf * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
Block Number 1. Method: Stepwise Criteria PIN .0500 POUT .1000
274
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 9 Dependent Variable.. SUPP support (technology and staf
Variable(s) Entered on Step Number 1.. EDUC educational background
Multiple R .21199 R Square .04494 Adjusted R Square .04107 Standard Error 1.06662
Analysis of Variance DF
Regression 1 Residual 247
F = 11.62269
Sum of Squares 13.22284
281.00563
Signif F = .0008
Mean Square 13.22284 1.13767
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 9 Dependent Variable.. SUPP support (technology and staf
Variable
EDUC (Constant)
Variable
GENDER AGE INCOME
Variables in the Equation --
B SE B Beta
.211992
T Sig T
-.153189 6.458901
.044934
.219115 -3.409 29.477
.0008
.0000
- Variables not in the Equation
Beta In Partial Min Toler
.097514 .098935 -.015502 -.015541 .003144 .002951
.983096
.959931
.841506
T Sig T
1.559 .1202 -.244 .8076 .046 .9631
End Block Number PIN = .050 Limits reached.
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 10 Dependent Variable.. OPPORT opportunity * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
Block Number 1. Method: Stepwise Criteria PIN .0500 POUT .1000
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 10 Dependent Variable.. OPPORT opportunity
Variable(s) Entered on Step Number 1.. EDUC educational background
Multiple R .21753 R Square .04732 Adjusted R Square .04346 Standard Error 1.12349
Analysis of Variance DF
Regression 1 Residual 247
F = 12 .26888
Sum of Squares 15.48605
311.76897
Signif F = .0005
Mean Square 15.48605
1.26222
* * * * M U L T I P L E R E G R E S S I O N * * * *
Equation Number 10 Dependent Variable.. OPPORT opportunity
Variables in the Equation
Variable B SE B Beta T Sig T
EDUC (Constant)
-.165781 4.233844
.047330 -.217534
.230797 -3.503 .0005 18.344 .0000
Variables not in the Equation
Variable Beta In Partial Min Toler
GENDER -.093003 -.094477 .983096 AGE -.095983 -.096347 .959931 INCOME -.110059 -.103438 .841506
T Sig T
-1.488 .1379 -1.518 .1302 -1.631 .1041
275
End B l o c k Number 1 PIN = .050 L i m i t s r e a c h e d .
* * * * M U L T I P L E R E G R E S S I O N * * * *
APPENDIX C
TABLES
276
277
FACTOR VARIABLES
Factor 1 - REPUTATION (6) Record of penalties/disbarments Physician's criminal record Physician malpractice record Tests re: HIV or other communicable diseases Moral standing on medical issues Years in practice Physician's bankrupycy record
Factor 2 - PHYSICIAN SOCIO-DEMOGRAPHIC (10) Physician participates in research Physician has specialty Medical school attended/graduated Physician age Physician gender
Factor 3 - ECONOMIC FACTORS (8) Fees/costs are important Economic conquences of making wrong/poor choice
Extra time required to find best fees Selecting physician difficult due to complex services they perform
Wide difference in fees by physicians considered
Selection decision difficult because lack of knowledge about medicine
Factor 4 - ENVIRONMENTAL (5) (location & appointments) Ease of getting an appointment Appearance of office/clinic Convenient office location Office close to residence
Factor 5 - PERCEPTUALS (4) Physician personality/manner Physician's reputation Access to preferred hospital Medical school physician attended Physician recommended by other physicians Physician participates in research
Factor 6 - SELF-EFFICACY (7) {patient's self-awareness) Selecting a physician is important Worth extra time to choose physician Could help a friend select physician Felt knowledgeable re: selection criteria Professional qualifications are readily available '
278
Factor 7 - INSURANCE (2) Insurance coverage Physician belongs to insurance network
Factor 8 - COMMUNICATION (1) (doctor-patient communication) Physician spends adequate time discussing condition
Physician explains illness/issues Physician values patient's opinion
Factor 9 - TECHNOLOGY (3) Support staff Current technology/equipment Hospital the physician uses
Factor 10 - OPPORTUNITY (9) (time) Differences in performance among physicians Little time to search for information Concern re: health left little time to search
for physician Pressured to select physician quickly
279
Gender Male Female
Age
1990 Census Demographic Information North Texas
1,648,631 (49.3%) 1,695,506 (50.7%)
<5 Years 282,612 (8. 5%) >16 Years 2, 534, 564 (75 .8%) >18 Years 2, 446, 411 (73 .2%) 18-20 Years 151, 023 (4. 5%) 21-24 Years 227, 088 (6. 8%) 25-44 Years 1, 256, 459 (37 .6%) 45-54 Years 327, 318 (9. 8%) 55-59 Years 118, 924 (3. 6%) 60-64 Years 103, 734 (3. 1%) >65 Years 261, 865 (7. 8%) >75 Years 105, 729 (3. 2%) >85 Years 25, 496 (0. 8%)
Marital Status Never Married Married Divorced/Separated Widowed
289,118 (32.7%) 404,448 (45.8%) 133,228 (15.1%) 56,522 (6.4%)
Educational Background Denton County Completed High School 86.8% Completed Baccalaureate 32.3%
Dallas County Completed High School 77.1% Completed Baccalaureate 26.3
Tarrant County Completed High School 79.9% Completed Baccalaureate 24.0%
Ethnic Origin Caucasian 2,242,815 African-American 517,684 Hispanic American-Indian Asian/Pacific Islander 90,029 Other 3,696
(67.1%) (15.5%)
476,205 (14.2%) 13,708 (0.4%)
(2.7%) (0.1%)
Yearly Household Income (Median) Dallas County $31,605 Denton county $36,914 Tarrant County $32,335
Place of Residence Denton Lewisvilie Dallas/Fort Worth
66,445 (2.0%) 79,443 (2.4%)
3,198,259 (95.6%)
APPENDIX D
GRAPHICAL PRESENTATION OF DATA
280
CLINIC INFORMATION
281
282
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Gender 284
female
female
Clinic A Clinic B
male
female
missing
female
Clinic C Clinic D
male
female
male
missing
Clinic E Clinic F male
female
285
Age
Clinic A Clinic B 30 to 38 years
40 to 48 years
20 to 28 years
20 to 28 years
30 to 33 years
over 70 years
60 to 68 years
50 to 59 years
Clinic C 40 to 48 years
Clinic D 30 to 38 years
40 to 48 years
30 to 38 years 20 to 28 years
under 20 over 70 years
to 68 years 40 to 49
50 to 58 years
Clinic E Clinic F
30 to 38 years
to 28 years
20 to 28 years
under 20 years missing 60 to 68 years
to 58 years
under 20 years
over 70 years 60 to 68 years
50 to 58 years
to 28 years
under 20 years mlssir-
60 to 69 years
50 to 58 years
40 to 48 years
under 20 years
50 to 59 years
30 to 39 years
286
Marital Status
married
married
married
Clinic A
never married
married
divorced/separated
iPwidowed
Clinic C
never married
married
divorced/separated
Clinic E
never married
married
missing
divorced/separated
Clinic B
never married
divorced/separated
idowed
Clinic D
never married
missing
divorced/separated
widowed
Clinic F
widowed
never married
divorced/separated
Educational Background 287
Clinic A Clinic B
some college
completed Bac.
some post Bac
completed high sch. some college
leted grade sch.
completed completed post Bac.
Incompleted high sch.
leted grade sch.
leted post Bac.
some post Bac.
Clinic C Clinic D some college
completed Bac.
some post
some college
leted high sch,
jme high school
sleted grade schi
completed Bac.
completed post Bac.
completed high sch
some high school npjetpa grade sch.
mpleted post Baa
Some post Baa
Clinic E completed high sc
some college
Clinic F some high school
some college completed high sch.
ited grade sch.
Ipleted post Bac.
some post Bac.
completed Bac. completed
some high school
missing
some post Bac.
Bac.
2 8 8
Ethnic Origin
Clinic A
Caucasian! Caucasian
missing
Asian/Pacific island
American Indian
African-American
Clinic C
Caucasian, Caucasian
Asian/Pacific islam Hispanic African-American
Clinic E Caucasian
Caucasian
missing
other
American Indian
Clinic B
Asian/Pacific Island
Ip'Hispanic
African-American
Clinic D
missing other
'Asian/Pacific Island
'American Indian V Hispanic
African-American
Clinic F
African-American Hispanic
other
African-American
Yearly Household Income 2 8 9
Clinic A $15-20,000
$20-30,000
$30-40,000
$40-50,000
Clinic C $20-30,000
$30-40,000
$40-50,000
Clinic E $5-10,000
$10-15,1
$15-20,000
Clinic B $15-20,000
$10-15,000
$5-10,000
over $50,000
$10-15,000
$20-30,000
$30-40,000
mmm $5-10,000
less than $5,000
missing
over $50,000
$40-50,000
Clinic D $15-20.000
^$10-15,000
$5-10,000
missing $40-50,000
over $50,000
$30-40,
$20-30,000
$15-20,000
$10-15,000 missing
over $50,000
Clinic F $20-30,000
less than $5,000 $3040,000
missing
over $50,000 $40-50,000
$40-50,000
$20-30,000 i,000
$15-20,000
$10-15,000
$5-10,000
missing
over $50,000
290
Occupation
Clinic A Clinic B
professional
office/clerical/sale
professional skilled worker
unskilled worker
other
management sart-employi
homemaker
management student
office/clerical/sale
skilled worker
unskilled worker
other
student
homemaker
self-employed
Clinic C Clinic D
professional
office/clerical/sale
professional
skilled worker unskilled worker
missing
student
homemaker management self-employed
office/clerical/sale
management
skilled worker unskilled worker missing
other
homemaker
self-employed
Clinic E office/clerical/sale
professional
manage: self-empli
homemaker
Clinic F office/clerlcai/saie
skilled worker professional
unskilled worker
other
unemployed
student management
skilled worker
unskilled worker
homemaker
self-employed
Place of Residence 291
Clinic A Clinic B
Denton Denton
other
Dallas/Fort Worth
Denton county
Clinic C
Denton
Lewlsville other
Dallas/Fort Worth Lewisville
Denton county
Clinic E Dallas/Fort Worth
Denton county.
Denton county Denton
other
other
Dallas/Fort Worth
Denton county
Clinic D Denton county
Denton
missing
other
Dallas/Fort Worth
Clinic F
other
Dailas/Fort Worth
292
Length of Residence
1 to 2 years
Clinic A 6 to 12 months
Clinic B 1 to 2
;• . less than 6 months smm
6 to 12 months
loss than 6 months
over 2 years
Clinic C 1 to 2 years
over 2 years
Clinic D 1 to 2 years
6 to 12 months 6 to 12 months
less than 6 mon
over 2 years
less than 6 months
missing
over 2 years
Clinic E J5to 12 months
Clinic F 6 to 12 months.
1 to 2 years less than 6 months
1 to 2 years
less than 6 months
over 2 years over 2 years
DEMOGRAPHICS
293
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GRAPHICAL PRESENTATION OF DATA BY FACTOR
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