FACTORS ASSOCIATED WITH TECHNOLOGY
ADOPTION IN CLINICAL PRACTICE
_________________________
A Doctoral Project
Presented to
The School of Graduate Studies
Department of Psychology
Indiana State University
Terre Haute, Indiana
_________________________
In Partial Fulfillment
Of the Requirements for the Degree
Doctor of Psychology
_________________________
by
Jennifer C. Salib, MS
August 2002
Abstract
The primary focus of the current study was the investigation of
technology use and related attitudes toward technology by psychologists in
clinical practice. In addition, this study served as the initial step in a larger
effort to develop a database, the Independent Practice Network (IP-Net),
which will allow for on-going investigation of patterns and trends in
independent practice. This study employed a survey method in which
participants chose to respond either via the Internet or by mail.
A random sample of 2,000 psychologists who are members of Division
42 (Psychologists in Independent Practice) of the American Psychological
Association were invited to participate in IP-Net. Two-hundred-and-sixty-five
volunteered and 161 subsequently responded. Despite the low response
rate, the characteristics of those who participated were very similar to those
in the random sample, as well as the entire membership of Division 42.
Psychologists with more positive attitudes toward technology, and
those in the online response group, reported significantly higher rates of
technology use, which supported one of our hypotheses. Our data also
indicated an increased rate of technology usage compared to previous
studies. Additionally, based upon our findings we were able to make
recommendations for a more comprehensive system of classification of
technology applications in clinical practice.
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Preface
This research study was completed with financial assistance from
Division 42 (Psychologists in Independent Practice) of the American
Psychological Association and the Indiana State University School of Graduate
Studies. This research study was also completed with the assistance of
Andrew P. Schneider, who donated his time to design and develop the Web
application and manage the online data collection.
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Table of Contents
ABSTRACT........................................................................................................2
PREFACE...........................................................................................................3
LIST OF TABLES................................................................................................8
CHAPTER 1 INTRODUCTION..............................................................................9
AREAS FOR TECHNOLOGY APPLICATIONS IN PRACTICE.............................................10
CATEGORIES OF TECHNOLOGY APPLICATIONS IN PRACTICE.......................................11
First-wave................................................................................................11
Second-wave...........................................................................................11
Third-wave..............................................................................................12
Critique of the Current System................................................................12
RATES OF TECHNOLOGY USE IN PRACTICE............................................................15
SPECIFIC TECHNOLOGY APPLICATIONS IN PRACTICE................................................18
LEGAL CONSIDERATIONS RELATED TO TECHNOLOGY USE IN PRACTICE.......................21
POSSIBLE REASONS FOR LOW RATES OF ADOPTION OF TECHNOLOGY APPLICATIONS IN
PRACTICE.......................................................................................................22
PSYCHOLOGISTS’ ATTITUDES TOWARD TECHNOLOGY USE.......................................23
Social Psychological Theory on Attitude Change.....................................24
Attitude Change Toward Computers as a Function of Experience...........25
Other Moderators of Computer Attitudes................................................28
Gender....................................................................................................28
Age..........................................................................................................29
PRACTICAL CONCERNS RELATED TO TECHNOLOGY USE IN PSYCHOLOGY....................30
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PROPOSED STUDY...........................................................................................32
CHAPTER 2 METHOD......................................................................................35
PARTICIPANTS.................................................................................................35
Random Sample Profile...........................................................................36
Study Sample Profile...............................................................................36
MEASURES.....................................................................................................37
PROCEDURES..................................................................................................39
CHAPTER 3 RESULTS......................................................................................41
Personal Characteristics of Study Participants........................................42
Practice Characteristics of Study Participants.........................................46
Practice Structure and Organization........................................................47
Average Number of Clinical Sessions per Patient....................................49
Current and Future Technology Applications in Practice.........................50
Average Time Spent per Week with Various Technology Applications....52
Attitudes Toward Technology..................................................................55
Hypotheses Testing and Predictor Variables...........................................57
First Hypothesis...................................................................................57
Third Hypothesis..................................................................................57
Second Hypothesis..............................................................................58
Additional Between Group differences for Online and Mail Responders. .59
Possible Subgroup Differences................................................................59
Use of the Internet for Data Collection....................................................60
CHAPTER FOUR DISCUSSION..........................................................................61
FINDINGS RELATED TO SURVEY METHOD.............................................................61
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Using the Internet in Research................................................................62
Additional Advantages to Internet Research...........................................63
Disadvantages to Internet Research.......................................................65
Issues Related to Participating in IP-Net..................................................66
Issues Related to Online Response Rates................................................66
Issues Related to Mail Response Rates...................................................67
Issues for Investigation in Subsequent Surveys......................................68
FINDINGS RELATED TO COMPARABILITY OF RESPONSE GROUPS................................69
Group Differences...................................................................................69
Generalizability.......................................................................................71
FINDINGS RELATED TO ATTITUDES TOWARD TECHNOLOGY AND TECHNOLOGY USE BY
INDEPENDENT PRACTITIONERS............................................................................72
Findings Related to Attitudes Toward Technology as a Function of
Response Group......................................................................................72
Findings Related to Technology Use as a Function of Response Group...73
Findings Related to Use of Technology in Practice Administration..........74
Findings Related to Use of Technology for Assessment..........................76
Findings Related to Use of Technology for Treatment.............................76
Findings Related to Technology for Communication and Information.....77
Discussion of Hypotheses Regarding Technology Use............................78
Trends in Technology Use.......................................................................80
CONCLUSIONS AND FUTURE DIRECTIONS..............................................................81
REFERENCES..................................................................................................86
APPENDIX A....................................................................................................94
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APPENDIX B....................................................................................................96
Appendix C...................................................................................................110
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List of Tables
Table 1. Comparison of Participant Characteristics from Total Volunteer
Sample, Random Sample and Entire Division 42 Membership................43
Table 2. Participant Characteristics from Responses to Surveys for Online and
Mail Groups.............................................................................................45
Table 3. Practice Characteristics from Responses to Surveys for Online, Mail,
and Total Sample....................................................................................47
Table 4. Person Responsible for Various Administrative Tasks from Responses
to Surveys for Online, Mail, and Total Sample.........................................48
Table 5. Average Number of Clinical Sessions per Patient by Percent from
Responses to Surveys for Online, Mail, and Total Sample.......................49
Table 6. Current and Anticipated Future Technology Use in Practice from
Responses to Surveys for Online, Mail, and Total Sample.......................52
Table 7. Average Weekly Telephone Use and Reimbursement in Practice from
Responses to Surveys for Online, Mail, and Total Sample.......................53
Table 8. Average Weekly E-mail Use and Reimbursement in Practice from
Responses to Surveys for Online, Mail, and Total Sample.......................54
Table 9. Attitudes Toward Computer Questionnaire Scores from Responses to
Surveys for Online, Mail, and Total Sample.............................................56
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Chapter 1
Introduction
There are little systematic data available to psychologists about
important dimensions of the independent practice of psychology. However,
practitioners share information related to personal and practice
characteristics on a regular basis with managed care organizations for
credentialing and re-credentialing purposes, and on a more frequent basis
with submission of billing and utilization review materials. As a result, these
organizations have much more information about individual practices than
the psychologists themselves do, and a better grasp of important aspects of
practice than is available to any other group. Additionally, efficacy research
traditionally neglects experienced psychologists working in independent
practice settings, and instead focuses on university or clinic “laboratory”
settings. In response to these trends, Division 42’s Emerging Patterns of
Practice Committee provided the initial financial support for the development
of the Independent Practice Network (IP-Net). The development of the
research network was one purpose of this study. The primary focus of the
current study was the investigation of technology use and related attitudes
toward technology by psychologists in independent practice.
This chapter reviews the various areas where technology applications
can be introduced into psychotherapy, as well as the wave system of
classification for technology applications in practice. We then examine the
current literature describing the rates of technology use in practice, and
some legal and ethical considerations related to its use in practice. This
chapter ends with a discussion of possible reasons for the low rates of
9
adoption of technology applications in practice, which leads to a description
of the current study.
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Areas for Technology Applications in Practice
Although computers have dropped in cost and in size, their power and
usage has greatly increased over the past decades. Specific to this paper,
there are many technologies now available that are designed to enhance and
simplify the work of practicing psychologists. These technologies are able to
do some tasks usually only performed by a psychologist. For example,
electronically tracking therapeutic progress by directly recording patient
homework assignments and changes in emotional and behavioral symptoms
can lead to time- and cost-efficient outcome research. These technologies
are also designed to make managing an office, maintaining patient files, and
communicating with patients and other professionals much easier and more
time- and cost-efficient tasks. However, there has been relatively little
movement in the field to incorporate these advances into the practice of
psychology (Marks, Shaw, & Parkin, 1998; McMinn et al., 1999). This raises
questions such as: what factors account for the low rates of adoption, what
can or should be done to increase usage, and how would an increase in usage
impact the practice and reimbursement of psychological services?
The adoption of technology by psychologists is affected by the nature
of the applications themselves and their relative cost effectiveness.
Technology applications must address a current need, or introduce an
approach to service delivery that is innovative and cost effective. The
application also needs to be easily assimilated into practice, in terms of
learning, cost, and maintenance, and it must be efficiently employed. For
this to occur, technology applications minimally must offer time and cost
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advantages over lower technology alternatives, and be readily available and
marketed.
In addition to these practical issues, the attitudes and values of
psychologists will affect adoption of technology applications. The focus of
this investigation was on identifying patterns of technology adoption among
practicing psychologists in the following areas: 1) office management (patient
files, billing, scheduling, word processing, marketing/advertising, referrals); 2)
assessment (testing, interviewing); 3) treatment (planning,
monitoring/documentation, outcome research, patient education, online
therapy, video therapy); 4) consultation; 5) supervision; and 6) training and
continuing education.
Categories of Technology Applications in Practice
McMinn et. al (1999) have divided the technologies available to
psychotherapists into three categories: (1) first-wave or well-established
practice technologies with minimal impact on service delivery; (2) second-
wave or partially established practice technologies with moderate impact on
service delivery; and (3) third-wave or emerging practice technologies with
direct impact on service delivery. While this system may help identify
developments in technology use, this system does not adequately categorize
and define the available practice technologies.
First-wave. First-wave/well established practice technologies are likely
to be used by most practicing therapists and include equipment that allows
for greater efficiency in maintaining records and running an office. These
types of technologies have minimal impact on the delivery of clinical services.
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Examples of such technologies include computer software for billing,
scheduling, and word processing, facsimile, and voice mail services.
Second-wave. Second-wave/partially established practice technologies
are likely to be used by many practicing therapists and include equipment
that allows for greater efficiency in assessment procedures, consultation
procedures, interviewing procedures, electronic mail, and maintaining clinical
databases. These types of technologies have moderate impact on the
delivery of clinical services. Examples of these technologies include
computer software for test administration and interpretation, telephone,
electronic mail, and Internet consultation, computer software for
interviewing, corresponding with patients via electronic mail, and maintaining
a database of clinical services for outcome research.
Third-wave. Third-wave/emerging technologies are likely to be used
by few practicing therapists and include equipment that allows for greater
efficiency in treatment and education. These types of technologies have
direct impact on the delivery of clinical services. Examples of these
technologies include virtual reality therapy for specific disorders (i.e., use of a
flight simulator as part of a treatment plan for fear of flying),
teleconferencing for patients in out-lying rural areas or consultation for
practitioners, Internet therapy (i.e., patients and providers logging onto a
Web site for treatment purposes), software packages for psychoeducational
purposes, and software to facilitate treatment (i.e., completing homework
assignments and assessments on a home computer and electronically
mailing them to the therapist’s office for progress tracking, which may also
facilitate outcome research).
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Critique of the Wave System. One consideration related to the above
classification system is that technology changes today are so rapid that the
classification system frequently needs to be revised as new products enter
the field, at minimum on an annual basis. Another consideration is that this
breakdown of technology into the three-wave system is unique to those in
the field of psychology. Other fields, such as financial institutions,
educational institutions, and even those in the medical profession, would
likely look at some technologies listed in the third-wave and consider them at
least second-wave, if not first-wave. Perhaps those of us in the field of
psychology need to reevaluate what is listed in the first-wave classification,
to determine if this so called first-wave should be eliminated entirely. When
one looks at the applications listed in the first-wave (i.e., fax machine,
voicemail, computer software for billing), it is doubtful that any modern office
can exist without them (Jerome, DeLeon, James, Folen, Earles, & Gedney,
2000).
Consideration should also be given to providing greater clarity on the
difference between using the Internet for obtaining information (second-
wave), versus using the Internet for e-commerce transactions (related to
health insurance claims or pharmacy transactions; second-wave), versus
using the Internet to connect consumers with mental health professionals
directly (either through appointment scheduling or direct online connections;
third-wave). This breakdown looks at the Internet in terms of being either a
passive source of information, or performing interactive transactions. The
interactive transactions will be guided by legal developments that protect
consumers and help ensure information integrity and privacy (specifically the
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Health Insurance Portability and Accountability Act of 1996, HIPAA), thus
further distinguishing them from passive information gathering.
The wave classification system does not discuss the importance of
outcome/effectiveness research and future participation in practice research
networks. Technology applications can be highly instrumental in the
collection and storage of outcome data, which can later be incorporated with
larger practice research network data. This paper does not go into detail in
the discussion of practice research networks, however, it should be noted
that these are becoming a popular new method for collecting real-time data
with high internal and external validity embraced by state organizations as
well as the American Psychological Association, and other health-related
associations (Borkovec, Echemendia, Ragusea, & Ruiz, 2001).
Also missing from this three-wave classification of technology
applications is a section for advertising and marketing. One could advertise
their services via the Web to attract potential clients, as well as post job
openings to recruit applicants. This application of technology could likely fit
into the first or second wave grouping since it is something that could be
adopted by a large number of practicing therapists, while having minimal
direct impact on treatment.
Lastly, also missing from this three-wave classification of technology
applications is a section related to training and continuing education
purposes. This application of technology could also likely fit into the first or
second wave grouping since it is something that could be adopted by a large
number of practicing therapists, while having minimal direct impact on
treatment. While training and continuing education are important aspects of
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our field, these areas are not discussed in detail because the focus of this
paper is on technology in practice. However, given the amount of
information available related to technology in education, and the likelihood
that educational institutions can more easily absorb the cost of incorporating
technology applications, perhaps this is the optimal entry point for
technology in the field of psychology, and should be researched in the future.
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Rates of Technology Use in Practice
The use of computers in mental health care has been studied, but
findings must be approached cautiously because of the rapid expansion in
the use of computers in the recent past (i.e., Bloom, 1992; Ghosh & Greist,
1988; Gould, 1996; Kenardy & Adams, 1993; Kirkby, 1996; Kirkby & Lambert,
1996; Lawrence, 1986; Marks et al., 1998; Oakley-Browne & Toole, 1994;
Plutchik & Karasu, 1991; Zarr, 1984). The main findings from these authors
indicate that, while most practicing psychologists are aware of the available
technologies, few have begun to incorporate them beyond the basic office
(billing and scheduling) and testing (administration and interpretation)
applications. Another important finding indicated that the majority of
practicing psychologists are uncertain about including the more advanced
technologies (beyond office and testing applications), such as those listed in
the 2nd and 3rd wave classification.
Data available from McMinn, Buchanan, Ellens, and Ryan (1999)
indicated that psychology as a profession is lagging behind in terms of
making use of available technology. For example, when compared to similar
survey data from a decade ago (Farrell, 1989), McMinn et al. (1999), who
surveyed 420 independent practice psychologists across the country, found
that only 57% of psychologists reported using computer applications for
billing fairly often (compared to 63% who reported routinely using it in 1989),
only 26% reported using technology fairly often for test scoring (compared to
41% routinely using it in 1989), only 20% reported using technology for test
interpretation fairly often (compared to 29% routinely using it in 1989), and
17
only 22% reported using technology for maintaining patient records fairly
often (compared to 20% routinely using it in 1989).
The October 2000 issue of Professional Psychology: Practice and
Research devoted a special section to issues related to technology use in
psychology. A study by Maheu and Gordon (2000) in that issue reported
results of a 40-item Web-based survey of 56 practicing psychologists
engaged in online behavioral healthcare. It looked at their backgrounds,
services, clinical interventions, fees, and types of technologies used. Survey
participants were recruited through Web postings on related e-mail lists. The
sample was 98% Caucasian, 65% male and 35% female, with 70% reporting
that they practiced in or near an urban area. Ninety-three percent of the
sample reported that they were licensed or certified to practice in their
respective fields in the United States, with 57% of the sample reporting that
they were licensed psychologists, 8% psychiatrists, 2% marriage and family
counselors, 17% social workers, and 5% other.
The majority of respondents (63%) described their services as
educational or advice-oriented in nature. Only 18% described their services
as therapy or counseling interventions. The majority of problems addressed
via technology applications were clinical in nature (i.e., related to mood,
anxiety, or sexual dysfunction disorders or relationship problems). The types
of technology applications most used were e-mail, Websites, and chat rooms,
or videoconferencing. The majority of respondents (55%) stated that they
provided their services at no charge. Those that did charge averaged 50 to
60 dollars per hour. A third of the sample reported only having single
sessions with consumers, whereas 50% of the sample reported between one
18
and fifteen sessions. Half of the respondents reported that the duration of
services was less than a month, whereas 20% reported providing services
that lasted up to three months. Most respondents (78%) reported that they
also provided services to individuals living in a state other than where the
provider was licensed, despite the fact that 73% reported having legal and
ethical concerns related to this matter. Only 50% reported having made
arrangements to deal with a sudden crisis situation, and only 48% used a
consent form prior to providing services. Seventy-five percent of
respondents reported having to refer a consumer to a local mental health
professional. While the results from this study are limited by its sample size
and method in terms of generalizability, the results do raise important legal,
ethical, and practical issues that need to be addressed. Also, it would be
important for future studies to address how attitudes and practices would
differ, if the services were based on providing educational information at no
charge versus clinical services.
Also in the October 2000 special section was an article by VandenBos
and Williams that reported on the extent of health care service delivery via
the Internet. This survey had a 60% response rate (n=596), with a sample
composition of 96% Caucasian, 52% male and 48% female, median age of 50
with a range of 33 to 72. Eighty-eight percent held a Ph.D., 93% were
psychologists, 80% had over ten years experience, and approximately 70%
were employed in full time independent practice. Of the 596 practicing
psychologists who responded, only 2% of the sample reported that they had
used the Internet or satellite technology to deliver services. However, it
should be noted that telephone use for delivery of psychological services was
19
nearly universal among those surveyed. While many studies in the literature
classify telephone use as part of the technology spectrum, we again question
the need to reclassify what is considered a true application of technology in
practice, given the discrepancy in usage rates depending on the type of
technology.
Incorporating greater usage of technological advances into the practice
of psychotherapy may not only prevent the field from becoming “outdated”,
but may also serve to benefit the profession in a number of ways. Wright and
Wright (1997) suggested that computers may reduce cost of treatment,
improve access to psychotherapy, promote engagement in the
psychotherapy process, provide psychoeducation, provide systematic
feedback to the user, promote self-monitoring, provide for rehearsal of coping
skills, encourage self-help, store, analyze, and display data, provide built-in
outcome measures, and function reliably without fatigue. However, research
is needed to demonstrate that these suggested advantages actually exist.
Additional research is also needed to determine current usage patterns, as
well as what factors are affecting adoption.
Specific Technology Applications in Practice
Studies have examined specific technology applications in
psychotherapy and provide more detailed information than discussed below.
Ghosh and Marks (1987) and Gosh, Marks, and Carr (1988) described the
results of a randomized controlled trial where eighty-four adult outpatients
diagnosed with either agoraphobia, panic disorder, social phobia, or specific
phobia were randomly assigned to perform self-exposure exercises under the
guidance of either a psychiatrist, self-help book, or computer-based self-help
20
program over a twelve week period. Results were compared against twenty
matched control subjects. At the end of the twelve week treatment period,
all three groups were equally satisfied with treatment, had a similar number
of drop outs, and had made significant improvements that continued through
a six month follow-up.
Semi, Klein, Greist, Sorrell, and Erdman (1990) describe the results of a
study that compared three groups of twelve of nonsuicidal depressed
patients recruited via newspaper on symptom relief based upon random
grouping: (1) computer-administered cognitive behavior treatment, (2)
therapist-administered cognitive behavior treatment, and (3) a wait list
control group. There were no drop-outs in the study. At the end of the six
week treatment period, and at a two month follow-up, both treatment groups
had improved significantly compared to the control group. The authors also
discuss the possibility that the novelty of the computer use as part of
treatment may have influenced the positive outcome in this group. This is an
area that requires additional research.
Schneider (1986) reported the results of a five week online patient
tailored smoking cessation computer program that allowed patients and
therapists to interact. At the end of treatment, approximately 35% of the
smokers were abstinent, and at a three month follow-up, 25% were still
abstinent. The authors stated that these results are similar to results found
using traditional face-to-face therapy techniques.
Agras, Taylor, Feldman, Losch, and Burnett (1990) described the use of
a hand-held computer as part of a twelve week treatment protocol for
nonbulimic mild to moderately obese females. Ninety females, average age
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45 years, who responded to a newspaper recruitment ad, were randomly
assigned to one of three groups, (1) use of a hand-held computer with one
introductory computer session, (2) computer therapy with four group support
sessions, and (3) a therapist conducted weight loss program. At the end of
the treatment period, all three groups had recorded similar weight loss
results that were maintained at a one year follow-up. The group that utilized
the hand-held computer and only one face-to-face session was the most cost-
effective, however, some added benefits were revealed through the addition
of group therapy support that could potentially provide longer-term cost and
patient benefits.
Two additional forms of technology reported in the literature are self-
treatment via interactive voice response and virtual reality programs (Marks,
Shaw, & Parkin, 1998). Interactive voice response is beneficial for those who
cannot access a computer, but have a touch tone telephone available.
Interactive voice systems would allow patients to respond to programmed
questions by using the touch pad on their telephone. This would provide a
similar exchange of data as if the patient typed in a response on a computer
keyboard. Virtual reality is mainly used as an aid to exposure therapy,
however, its cost can often be prohibitive for use in regular treatment.
It should be kept in mind that these studies likely suffer from limited
generalizability due to issues that affect all efficacy studies, such as a highly
screened patient population and specifically working with manualized
cognitive behavioral techniques. Therefore, additional research in natural
settings needs to be done to truly understand the impact of technology in
psychotherapy practice. For the most part, all of these studies reported fairly
22
small sample sizes, and a literature search did not produce more recently
published work. Given the rapid and widespread advances in technology, as
well as its presence in our daily lives, newer studies are needed. Also, a
thorough examination of both short- and long-term costs versus benefits is
needed with future studies.
It appears that researchers have moved from conducting efficacy
studies, to doing survey research for what is being incorporated into practice,
without ever being certain that what we are incorporating truly works. This is
in line with the argument presented by Stamm and Perednia (2000) stating
that research in the area of telehealth typically addresses the technology
aspects of the care provided and not the psychosocial implications of the
technology driven care. Therefore, absent in the research is knowledge
about what telehealth means in terms of quality of care versus simple
provision of care. This is likely the result of recent rapid technological growth
paired with financial pressures on the healthcare industry to be more cost-
effective. Based upon available descriptive studies (i.e., Burghgraeve &
DeMaeseneer, 1995) it was assumed that technology was a good and cost-
effective means of achieving an end. This led to the rapid growth of
technology applications and training in the health care systems, with
accompanying research studies assessing patient and provider usage. Again,
missing from this equation is research addressing the psychosocial impact, or
meaning, behind telehealth and its quality of care.
Stamm and Perednia (2000) call for future research to address the
human aspects of using technological applications in practice that underlie
the technical interface of telehealth. Technology refers to the “nuts and
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bolts” components of the telehealth systems, and the human part involves
the actual delivery or receiving of the service. After all, the authors remind
us that the human-technology interface is the most important aspect in the
telehealth equation, and that the best piece of computer equipment is only
as good as its trained and willing human user. A practice research network,
such as IP-Net described in the current study, could serve as a useful tool to
answer these questions.
Legal Considerations Related to Technology Use in Practice
Koocher and Morray (2000) discuss some of the legal aspects related
to the use of technology in psychotherapy practice. They surveyed all fifty
states’ Attorney Generals and the Attorney General of the District of
Columbia via paper-pencil and telephone between March 1999 and August
1999. Readers are cautioned that changes in state statutes and regulations
are constantly occurring and, therefore, some results reported in this study
may not be reliable after 1999. Attorney Generals from forty-two jurisdictions
participated in this study. All those who responded indicated that their
jurisdiction had statutes regulating the practice of psychiatry, psychology,
and social work. Eighty-six percent of those responding indicated that they
regulated marriage and family counseling, twelve percent regulated pastoral
counseling, 88% regulated psychiatric nursing, 33% regulated rehabilitation
counseling, and 38% regulated “other” areas such as licensed mental health
counseling, substance abuse counseling, art therapy, employee assistance
programs, occupational therapy, and school psychology. Only 7% of those
responding indicated that they had statutes specifically addressing telehealth
issues. Of the 93% indicating that they did not have such statutes in place,
24
only 17% of them indicated that such regulations were even contemplated.
Eighty-six percent responded that no charges had been brought against
licensed mental health practitioners engaging in therapy via electronic
methods, while less than 1% reported that such complaints had been filed in
their jurisdictions. However, 17% indicated that they had received
complaints about services being provided by electronic means across state
lines. Forty-five percent of those responding indicated that they claimed
regulatory authority over practitioners residing outside their jurisdiction, but
offering services via telephone or electronic means within that particular
jurisdiction.
Possible Reasons for Low Rates of Adoption of Technology Applications in
Practice
Designers of computer therapy programs hope that patients will use,
and therapists will accept, the computer as a therapy tool. As described
above, the research literature indicates that some patients have accepted
the computer in therapy. However, the literature also indicates that
therapists are just beginning to accept the computer in therapy as a
legitimate tool as evidenced by the low usage numbers reported by survey
studies (Gould, 1996; Marks et al., 1998). Some studies have reported
concerns by psychologists against the greater incorporation of technology
applications into practice: its influence on the therapeutic relationship, ethical
and confidentiality issues, organizational resistance (including issues of start-
up costs and lack of guidelines/standards for use), and patient resistance
(i.e., McMinn et al., 1999, Wright & Wright, 1997).
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Although there are studies reporting survey results of the extent of
technology use by psychologists in their practices, there are very few studies
explaining what factors influence adoption of various technology applications.
Those studies that do report explanations for this trend tend to focus on the
attitudes and values of psychologists (i.e., McMinn et al, 1999). It also
appears that the rapid and widespread technological advances taking place
in our society have outpaced the development of ethics and training
standards or guidelines for practicing psychologists. This lack of standards or
guidelines has left many psychologists uncertain about and unprepared to
incorporate these advances into practice, as well as leaving psychology as a
field lagging behind technologically. The concerns by psychologists then
appear to fall into two broad categories: issues related to attitudes/values of
psychologists, and practical/economic concerns.
Psychologists’ Attitudes Toward Technology Use
Despite the fact that there are reliable and valid measures available in
the literature to assess attitudes toward computers and other advanced
technologies (i.e., Attitudes Toward Computers Questionnaire (ATCQ), Jay,
1989; Computer Attitude Scale (CAS), Loyd & Gressard, 1984; Stages of
Concern Questionnaire (SoCQ), Hall, George, & Rutherford, 1977), there were
no studies found in the literature that used these measures to assess the
attitudes of psychologists in comparison to technology usage. This study
measured attitudes toward computers among practicing psychologists in
comparison with reported usage of technology applications in practice.
Social Psychological Theory on Attitude Change. Attitudes are defined
as “very general evaluations that people hold of themselves, other people,
26
objects, and issues” that can be based upon and impacted by affect,
cognitions, behaviors, or a combination of these variables (Petty, 1995, p.
196). While there are numerous ways to change one’s attitude about
something, the most common means is via persuasion. Persuasion is
achieved by presenting one with a message containing information about
their current attitude topic. This makes sense since the primary purpose of
attitudes is to serve a knowledge function (help one understand and make
sense of their world) and can broadly be viewed as an information-processing
model of attitude change. Additionally, it is presumed that once attitude
change has occurred, one will engage in behaviors that are consistent with
the attitude beliefs. Therefore, persuasion can be viewed as a means of
changing behavior as well as attitude (Petty, 1995).
Research in social psychology also states that attitudes are acquired
and changed through experience (Fishbein & Ajzen, 1975; McGuire, 1985).
Experience can either be direct (e.g., actual contact with a computer) or
indirect (e.g., observation of another using a computer or through media
exposure). Therefore information gained through these experiences forms
the basis for attitude formation and change. Since social psychology
research has also shown that attitudes are likely to guide behavior (Regan &
Fazzio, 1977), it can be expected that those having positive attitudes about
something (e.g., computer use in psychotherapy) are more likely to employ
or do the thing that they have the positive attitude about (e.g., actually make
use of computers in their psychotherapy practice) compared to a person
holding a less favorable or negative attitude about the same thing.
27
In order for this information-processing model of attitude change to be
effective, McGuire (1968, 1989) stated that the informational message
related to the attitude must be received, understood, and learned and then
the recipient of the message must yield or accept this information.
Therefore, factors such as message comprehensibility, amount of distraction,
individual differences among audience members (e.g., intelligence, mood,
etc.), credibility of the information source, relevance of the information to the
audience, priming of audience members, and motivation and ability to think
about the information, will all affect how the sender’s message impacts the
recipient of the message.
Attitude Change Toward Computers as a Function of Experience.
Amount of direct computer experience has been found to be the most
consistent correlate of computer attitudes, with increased experience leading
to more positive attitudes (Jay, 1989). This is also a central hypothesis for
this study and therefore will be discussed in some detail below.
Related to computer usage, the research literature suggests that user
attitudes have important implications with respect to the acceptance and use
of technological innovations (Grudin & Markus, 1997). Mackie and Wylie
(1988) have outlined a model which demonstrates that user acceptance of
technology is affected by: (1) the user’s awareness of the technology and its
purpose; (2) the extent to which the features of the technology are consistent
with the user’s needs; (3) the user’s experience with the technology; and (4)
the availability of support when using the technology.
Czaja and Sharit (1998) examined whether attitudes toward computers
are influenced by direct computer experience and if these attitudes vary as a
28
function of age, gender, and computer task characteristics. Subjects for this
study were 384 men and women ranging in age from twenty years to
seventy-five years. Attitudes toward computers were measured before and
after the intervention using the Attitudes Toward Computers Questionnaire
(ATCQ; Jay & Willis, 1992). Findings from this study indicated that computer
attitudes are modifiable regardless of age or gender. These findings are
consistent with other reports in the research literature (i.e., Jay & Willis,
1992). Subjects’ attitudes significantly improved as a result of direct
experience with computers. Subjects also reported that their level of
comfort, feelings of competence, and feelings that computers are useful
increased as a result of the intervention. Subjects reported that the task that
required the most cognitive effort was least enjoyable. This has implications
for how computer training programs are structured. In order to maximize
attitude change and facilitate learning, it is important to employ tasks which
people find enjoyable as well as informative. This study demonstrated that
providing users with an opportunity to interact with technology that may be
unfamiliar to them is an effective means of attitude change.
Jegede, Okebukola, and Ajewole (1991) studied whether the attitudes
of students in a developing country, with little exposure to computers, would
be positively influenced by a computer-assisted learning program. This study
used 64 students enrolled in a preparatory course for the Nigerian Joint
Matriculation Examination in biology (41 boys, 23 girls, mean age = 16.4
years). Both attitude toward the use of the computer for learning biological
concepts and achievement in biology were measured before and after the
three month computer-assisted learning program. Subjects were randomly
29
assigned to one of three groups: computer used on an individual basis;
cooperative computer use; and traditional lecture-style classroom instruction.
Results indicated that both groups that used the computer had significantly
higher attitude scores at post-testing, in terms of liking the computer for
learning, compared to the classroom control group. There were no
differences found in terms of achievement. However, previous studies (i.e.,
Choi & Gennaro, 1987; Wainwright, 1989) have reported that students learn
better and achieve higher scores when working with computers as compared
to traditional classroom methods. While this study included a small sample
size and a very specific group of subjects who do not easily generalize to the
population being discussed in this paper, it is interesting to note that changes
in attitude toward computer use does not appear to be limited by culture or
socioeconomic status, gender, or age. Attitude change was again effectively
demonstrated via direct computer contact and experience.
Levine and Donitsa-Schmidt (1998) examined the extent and direction
that computer attitudes, experience, and belief are causally linked, as well as
the impact on one’s perceived level of knowledge regarding computers.
Study participants were 309 Israeli students in grades seven through twelve,
48% male and 52% female, who completed a self-report questionnaire
covering demographic factors, computer use and experience, computer
attitudes and confidence based on measures available in the literature, and
perceived computer knowledge. Results indicated that computer use
variables were significantly and positively related to computer attitudes, as
demonstrated in other research studies. Positive correlations were also found
between computer experience and computer confidence, with a significant
30
relationship between computer attitudes and computer confidence, as well as
between both computer experience and confidence compared to computer
knowledge. Study results supported the hypothesis of a causal model for
computer experience, computer confidence, computer attitudes, and
perceived computer knowledge.
Other Moderators of Computer Attitudes. Research studies have
reported that in addition to amount and quality of direct and indirect
experience, other moderators of attitudes toward computers include the
demographic characteristics of gender, age, and education and income.
Gender and age will be discussed in some detail below. Studies regarding
income and education have reported inconsistent results due to the fact that
various economic groups have differential access to computer technology.
Also, the sample used in the present study will be fairly homogenous in terms
of level of education and socioeconomic status.
Gender. Howard, Murphy, and Thomas (1987) investigated the
possibility of a gender difference in computer-related attitudes. Previous
research has demonstrated mixed results on this gender question, which may
be related to the use of different measures and different populations of
interest. For example, some studies have found significant gender
differences in computer attitudes, usually with males being more positive
(i.e., Abler & Sedlacek, 1989; Jay, 1985; Jordan & Stroup, 1982) while others
have found no gender difference (i.e., Glass & Knight, 1988; Koohnag, 1986;
Loyd & Gressard, 1984).
Subjects in the Howard et al. (1987) study were 194 undergraduate
and graduate students at a large Midwestern university. One hundred and
31
seven students took a computer training course (17 males, 90 females) and a
comparison group of 87 students (55 males, 32 females) received no
computer training. Both groups of subjects completed the Computer Attitude
Scale (Loyd & Loyd, 1985) during the first and last weeks of the sixteen week
semester. Results indicated that students who received the training were
less anxious and more confident and reported greater interest in using
computers compared to those who received no training. No significant
gender differences were found. Overall, attitudes toward computers in
general significantly improved with training, while those in the no training
group remained the same. A limitation of these findings is that the computer
training group had a significantly higher rate of female participants.
It is possible that these studies reported in the 1980’s are presenting
outdated gender information, and that more current studies would better
answer the question of gender differences, since there is greater equity in
access to computers for both genders today. However, it is also possible that
current studies would find the same mixed results or slightly higher positive
attitudes and greater experience among males. Any remaining gender
differences could be due to interest in computers and programming following
the traditional reported gender differences that is found in mathematics,
since computer programming is heavily reliant upon mathematical skills.
This is likely to be supported by base rates if one looks at the number of
female versus male computer professionals.
Age. As intuitively expected, several studies have reported results
demonstrating that younger people hold more positive attitudes towards
computers compared to older people. This holds true for comparisons of
32
young adults (twenties and thirties) to older adults (fifty plus) (Ansley &
Erber, 1988) and middle-aged adults (late thirties to mid-forties) to older
adults (fifty plus) (Kerschner & Chelsvig Hart, 1984). It should be noted that
these reported age differences may represent a cohort effect rather than a
true age difference, since younger cohorts have increased contact with
computer technology in their daily lives. It is likely that if more recent studies
were available using current cohorts of younger people, they would report
increased exposure to computer technologies at even earlier ages, which
likely impacts their amount and quality of experience with computers as well
as their attitudes toward computers. It is also possible that today’s cohort of
older people would report an increased positive attitude toward technology
use due to increased exposure in their daily lives.
Practical Concerns Related to Technology Use in Psychology
An additional area of concern related to adaptation of computer
technologies into the practice of psychotherapy, as discussed by Murphy
(2000), is that the task demands associated with psychological services do
not take advantage of the capabilities of computers, and reveal their
weaknesses compared to the human therapist. Additionally, the practical
and economic factors related to widespread adoption in clinical practice are
potential obstacles and reasons for the current under-usage of available
technologies. Thus, those in private practice settings may be less likely to
incorporate available technology applications.
For example, Murphy (2000) pointed out that although there are many
software programs available to handle the demands of file maintenance,
computerized files require the additional clinician step of entering the client
33
data into the computer, which can provide long-term cost and time-saving
benefits, but initially are non-reimbursable. It appears that the greatest
savings in cost and time are derived from the computerized scoring and
interpretation applications, which take advantage of a computer’s capacity to
calculate, apply decision rules, and display results in a variety of formats
accurately, reliably, and rapidly. Additionally, with the patient entering test
responses directly into the computer, this reduces the amount of time a
clinician must spend on scoring and interpreting the assessment tool.
Ultimately, these are also computerized clinical activities that generate
revenue.
In terms of computer applications for treatment interventions, Murphy
(2000) pointed out that the potential benefits of technology aids for therapy
are predicated on a different system of service delivery than what currently
exists. For example, issues related to development of rapport, clinical
assessment, problem formulation, and treatment planning as they exist do
not support computer interview applications. However, there is the potential
for various technology-based applications to develop in public clinics,
capitated systems, or Web-based telehealth or managed care systems. It
should also be noted that with the insertion of technology applications and
decreased therapist-patient interaction, we stand to lose valuable
observational data especially during assessment procedures, and must rely
more on a patient being aware and honest about issues.
Treatment modalities that are currently able to take advantage of
technology applications are highly structured behaviorally-based
interventions that typically promote self-monitoring, rehearsal of coping
34
skills, and provide feedback for outcome measures. However, it is possible to
incorporate these same interventions via self-help books and other workbook
type materials, at much less expense (Murphy, 2000). Additionally,
psychologists are much more likely to encounter problems dealing with self-
concept and interpersonal relationships, which are not easily treated via
structured behavioral interventions (Murphy, 2000).
Ultimately, in order for computer applications to become more widely
adopted in psychotherapy practice, Murphy (2000) argued that the
technology must offer a clear benefit over simpler and less expensive
alternatives, as well as help to generate income. The process of getting new
technologically-based services covered as reimbursable activities would thus
require considerable effort on the part of both government legislators and
third party payers in terms of reimbursement issues, licensure and
malpractice considerations, standards and guidelines for practice, and
protecting the consumer’s privacy and confidentiality (Murphy, 2000;
Nickelson, 1998).
Given this understanding from the research literature regarding
personal and practice characteristics, it appears that these areas are where
messages aimed at attitude change would need to be focused (Marks et al.,
1998). However, it is also possible that the significant under-usage of
technology in therapy may be due to psychologists’ lack of familiarity with
available technologies, or the idea that computers are impersonal,
impractical, and not cost-effective for many practices, especially solo or small
group practices. These are questions for which we do not yet have answers
35
to, but need to understand before training and practice guidelines can be
established for the use of technology in psychotherapy.
Current Study
This study measured current technology usage and attitude toward
usage among psychologists in independent practice. Technology usage was
measured via self-report, and attitudes toward technology usage was
assessed using The Attitudes Toward Computers Questionnaire (ATCQ) (Jay,
1989).
The three main hypotheses for this study stated that, (1) those who
are newer to the profession, as determined by number of years licensed,
would be more accepting and more likely to use available technology
applications; (2) those with more positive attitudes toward computers, as
determined by the total score on the Attitude Toward Computers
Questionnaire (ATCQ, Jay, 1989), would be more likely to use available
technology applications; and (3) those not in solo private practice would also
be more accepting and more likely to use available technology applications.
This initial recruitment for the present study was undertaken as part of
a larger project with the purpose of establishing the foundation for a research
database of participants for the Independent Practice Network (IP-Net).
Therefore, it was hoped that this project would not only look at technology
issues, but also provide demographic information on the composition of
participants and establish the degree of representativeness or
generalizability of the sample to practicing psychologists. This study was the
initial effort for IP-Net and therefore also served to work out methodological
issues.
36
Given the rapid and widespread technological advances taking place in
our society, it is important to determine current usage and related attitudes,
as well as the factors affecting adoption of technology by psychologists.
Otherwise, there is no basis for deciding which technology applications to
adopt or where to focus future training. Thus, the profession may be left
faced with uncertainty and a lack of preparation to incorporate these
technological advances, as well as allowing psychology as a field to lag
behind technologically.
It should be noted that this study concerns technology in a broad
sense, encompassing all technological advances, not just specific computer
hardware and software use. This is consistent with how the terms technology
and computer are referred to in the research literature in this area. For
example, the technology applications categorized as first-wave, include items
such as telephone voice-mail, fax machines, and computer software.
Technology applications listed in the second-and third waves include more
complex technologies such as the Internet, virtual reality programs, and
video equipment. However, various studies that include discussions of these
diverse forms of technology all list them as “computer use” or “technology
use” (i.e., Marks, 1998; McMinn, 1999; McMinn et al., 1998). Additionally,
these studies state that technology and/or computer use in relation to
practice, fall under the even broader categories of telemedicine and
telehealth. A telehealth system has been defined as including the use of
educational, administrative, clinical, and technological functions of
communications technology and computers in the delivery of health care
services (Stamm & Perednia, 2000). Therefore, the terms technology and
37
computer are often used interchangeably throughout the available research
literature as well as throughout this study.
38
Chapter 2
Method
This study employed a survey method in which participants recruited
for a research network were able to respond either via the Internet
(www.division42.org and clicking on the IP-Net link) or by mail, depending on
participant preference. Therefore, we examined two self-selected groups,
one of online participants and one of mail participants. The survey asked
participants to provide information about themselves, their professional
practices, characteristics about the communities where they practiced, and
technology use in practice. Participants also completed a measure on
attitudes toward technology.
Participants
A random sample of 2,000 psychologists who are members of Division
42 (Psychologists in Independent Practice) of the American Psychological
Association (APA) were invited by letter to participate in the study.
Inclusionary criteria included: primary employment providing clinical services,
being a United States resident, and practicing independently for a minimum
of two years. We required a minimum of two years of licensed practice to
ensure that the individual had time to adequately establish practice beliefs,
attitudes, procedures, and behaviors. We excluded from our sample those
who still practiced under the supervision of another licensed psychologist, as
this may significantly impact their attitudes toward and usage of available
technologies for practice. Once data were collected, we then further
excluded participants who worked in a practice setting where they had little
39
control over what equipment is purchased and used as determined by a
questionnaire item (Appendix B, question #26).
Issues of ethnicity and gender were not expected to be a factor since
the study involved a highly specific sample population that is basically
homogeneous in terms of education and socioeconomic status. Also,
previous research does not indicate strong conclusive differences based upon
either ethnicity or gender, especially in relation to the population of
psychologists used for this study. Although more recent graduates are likely
to be in a lower income category compared to well-established practitioners,
this should not greatly impact socioeconomic status as a variable because
even the lowest income reported is expected to be "middle class”.
Random Sample Profile. The composition of the random sample and
the entire Division 42 membership provided by the APA Research Office is
detailed in Appendix C, and includes information on participants’ gender,
race, age, geographic location, degree, number of years licensed, and
employment setting.
Study Sample Profile. Of the 2,000 Division 42 members who were
contacted to volunteer to participate in this Independent Practice Network
(IP-Net) study, 265 (13%) agreed. Of this number, 130 (49%) volunteered to
respond online and 135 (51%) by mail. These self-selected groups formed
the original IP-Net sample. It should be noted that this overall recruitment
rate (13%) is much lower compared to other studies conducted using Division
42 members, which tends to be between 30% and 40% (Michael J. Murphy,
Ph.D., personal communication June, 2002).
40
Questionnaires were mailed to the 265 volunteers and we received a
total of 161 (61%) responses, 75 (47%) online and 86 (53%) via mail over a
4-week period. Therefore, we ultimately ended up with only 161 participants
from the 2,000 contacted for a low response rate of 8%.
Eight respondents (6 from the online group and 2 from the mail group)
had to be eliminated from the study due to the exclusionary criterion that
they did not report even moderate control over what technology equipment
and applications were purchased or used in their place of employment. It is
interesting to note that more members of the online group reported less
control over what technology items were purchased and used in their
practice settings.
Measures
All participants were asked to complete a questionnaire addressing
personal information, practice characteristics, technology use, and attitudes
toward technology (Appendix B). Both the questionnaire instrument and the
Website were piloted to insure readability and that the Web Page loaded
correctly and without extensive delay. Ten local practicing psychologists,
who are Division 42 members, were asked to participate in the pilot session.
They did not participate in the actual study. Their feedback was incorporated
in terms of revising any grammatical or typographic errors and rewording
items to increase comprehension. It should be noted that several pilot
members commented on the “offensive” gender tone used in the Attitudes
Toward Computers Questionnaire (ATCQ, Jay, 1989, Appendix B #39).
However, since this is a standardized measure no changes were made.
41
Items addressing personal information included age, race, gender,
income, type of degree and graduate program, number of years licensed,
number of years at current setting, and theoretical orientation. The
Theoretical Orientation Profile Scale-Revised (TOPS-R; Worthington & Dillon,
2002) was used to assess participants’ identification with six different schools
of therapy: (1) psychodynamic/psychoanalytic, (2) humanistic/existential, (3)
cognitive-behavioral, (4) family systems, (5) multicultural, and (6) feminist
(see Appendix B question #16). This assessment tool was included for the
purposes of another research study affiliated with the Internet data collection
method used in this particular study. However, the TOPS-R itself has no
significance to the present study, and therefore it is not discussed in detail. It
is sufficient to state that the instrument was reported to have adequate
reliability and validity scores, and appropriately classifies therapists in their
approach to utilizing therapy techniques falling into one of the above listed
schools.
Items addressing practice characteristics included type of practice
setting, geographic location, community size where practice is located,
person responsible for various office tasks, level of control over office
equipment purchased, and the average number of sessions patients are
seen.
The questionnaire also included items addressing amount of current
use of technology in practice, reimbursement for use, and anticipated future
use of technology in practice. Finally, the Attitudes Toward Computers
Questionnaire (ATCQ, Jay, 1989) was included (Appendix B question #39).
42
The Attitudes Toward Computers Questionnaire (ATCQ, Jay, 1989) is a
multidimensional measure assessing seven dimensions of attitudes toward
computers, as identified by previous research with adult and student
populations: (1) comfort; (2) efficacy; (3) gender equality; (4) control; (5)
dehumanization; (6) interest; and (7) utility (i.e., Bear, Richards, & Lancaster,
1987; Elkins, 1985; Jay, 1989; Krauss & Hoyer, 1984; Richards, Johnson, &
Johnson, 1986).
The comfort dimension assesses feelings of comfort with the computer
and its use. The efficacy component assesses feelings of competence with
the computer. The gender equality dimension assesses the belief that
computers are important to both men and women. The control dimension
assesses the belief that people control computers. The interest component
assesses the extent to which participants are interested in learning about and
using computers. The dehumanization component assesses the belief that
computers are in some way dehumanizing to use or interact with. The utility
dimension assesses the belief that computers are useful. Each dimension or
component is assessed by five or six items scored on a five point Likert scale
format, with response options ranging from strongly disagree to strongly
agree. A higher score represents a more positive attitude, with the
dehumanization component being reverse scored. The total score across all
dimensions represents a person’s attitude in general (given the seven
dimensions identified by previous factor research) toward computers.
The author of the measure reported internal consistency coefficients of
0.66 to 0.84 for the seven factors (Jay, 1989). Previous research using the
measure also identified Cronbach alpha coefficients 0.63 for the comfort
43
dimension, 0.69 for gender equality, 0.54 for control, 0.82 for
dehumanization, 0.64 for interest, 0.67 for utility, and 0.78 for efficacy (Czaja
& Sharit, 1998).
Procedures
All participants were treated in accordance with the standards set forth
in the “Ethics in Research with Human Participants” (American Psychological
Association, 2000), which included maintaining confidentiality of participant
responses and providing informed consent (see Appendix A which contains a
copy of the informed consent letter).
Participants were mailed a letter on American Psychological
Association (APA) Division 42 (Psychologists in Independent Practice)
letterhead inviting them to take part in the study (Appendix A contains a
copy of this letter). Participants gave informed consent by (1) directly
logging on to the study Web site and submitting responses, or (2) sending the
enclosed postage-paid postcard indicating their agreement to participate, as
well as their preferred method of data collection (online or mail) and means
of contacting them. Those choosing the mail method were sent the study
materials. Those choosing the online method (1) had immediate access by
following detailed instructions provided in the invitation letter and on the
Website, or (2) had their initial username and password sent to the email
address they provided on their response postcard.
Those who chose to respond via the online method and experienced
difficulty accessing the Website or needed clarification on a particular
questionnaire item directed their questions to a “contact” link on the Web
page that sent an e-mail message to the researchers. All e-mail questions
44
were responded to immediately. Those choosing the mail method of
response did not have immediate contact information provided, and had to
refer back to the initial invitation letter that listed telephone, fax, and e-mail
contact information for the researchers.
Data collected online were automatically (via computer program)
placed into computer software programs that began the data analysis
procedure. Data collected by mail were hand entered to a spreadsheet
program, then transferred to statistical analysis software. All data,
regardless of method of entry, were checked for accuracy.
45
Chapter 3
Results
We first examined descriptive statistics for available demographic and
practice variables for the group from which the IP-Net sample was drawn as
well as the entire Division 42 membership, and then the descriptive statistics
drawn from the responses of participants responding online and by mail.
Statistics included measures of central tendency and measures of variability,
and are provided for all demographic and practice variables. These data
allowed assessment of the extent that the sample was similar to Division 42
members and provide a foundation for generalizing findings. These data also
allowed us to evaluate the extent that we were successful in recruiting
participants for the IP-Net and the usefulness of the sample in making
inferences about members of the Division and private practitioners in
general.
Comparison of the samples of participants who responded online and
by mail provided information about any systematic differences between
these self-selected groups and determined the extent that systematic
differences may affect generalizability of online data collection. The
descriptive statistics also clarified important aspects of clinical practice
assessed in the current study that will be built on in future studies employing
IP-Net. Finally, we examined the findings as they relate to the central focus
of the current study, which is factors related to the patterns of technology
use by psychologists, with particular emphasis on the effect of attitudes
toward technology.
46
Inferential statistics were utilized for determining relationships
between variables and examining group comparisons of the online versus
mail groups, to determine if the two groups varied significantly in their
attitudes toward computers and level of technology usage, as well as any
differences related to personal and practice demographic variables.
Specifically, chi-square analyses were utilized with categorical data, and
ANOVA or t-tests were utilized with continuous data and are discussed in
more detail below. These statistical methods were also utilized for
hypothesis testing to determine if predictions could be made regarding a
practitioner’s attitude toward computers or level of technology usage based
upon the following variables: (1) number of years licensed, (2) score on the
Attitude Toward Computers Questionnaire (ATCQ, Jay, 1989), and (3) practice
setting. Finally, we examined findings to determine if additional variables
might predict technology use, attitudes toward technology, or group
membership of online versus mail for response method. Chi-square analyses
were chosen because of a conservative judgment made to treat Likert
variables on the ATCQ as categorical data.
The study began with a random sample of 2,000 members of Division
42 (Psychologists in Independent Practice) of the American Psychological
Association (APA) obtained from the APA’s Research Office in the form of
mailing labels. Inclusion criteria specified by the APA Research Office for the
sample included United States residency, licensure to practice psychotherapy
as a psychologist, and a minimum of two-years in practice based upon a
special assessment fee levied the third year of licensure.
Personal Characteristics of Study Participants
47
Table 1 presents the composition of those who volunteered to
participate in our study. This composition is considered in terms of the data
presented in Appendix C. The composition of our study sample was very
similar to the random sample, as well as to the entire Division 42
membership, in terms of gender, race, age, geographic location, degree,
number of years licensed, and practice setting.
Table 1. Comparison of Participant Characteristics from Total Volunteer Sample, Random Sample and Entire Division 42 Membership
VariableTotal Volunteer
Sample Random SampleDivision 42
MembershipN: 153 2,000 6,166Gender: Male
65.0%60.0% 62.4%
Female 35.0% 40.0% 37.6%Race: Caucasian
98.0%95.0% 92.0%
Hispanic 1.3% 1.5% 1.4%American Indian 0.7% 0.5% 0.2%
Age: Mean
53.9not available 56.6
Median 54.5 52.7 not availableSD 6.2 6.7 10.6
Range 38.0-74.0 30.0-70.0+ not available*Region:
Middle Atlantic 27.0% 22.8% 25.2%South Atlantic 14.0% 17.1% 17.6%
Pacific 13.0% 16.9% 15.2%East North Central 15.0% 14.3% 14.0%
New England 8.0% 8.8% 8.2%West South Central 6.0% 6.1% 6.0%West North Central 7.0% 5.6% 4.6%
Mountain 5.0% 4.7% 5.2%East South Central 5.0% 3.9% 3.3%
Degree: Ph.D.
86.0%87.0% 83.2%
Psy.D 5.0% 7.0% 5.9%Ed.D 9.0% 5.0% 6.3%
Years Licensed:Mean 20.7 not available 23.5
Median 21.5 19.9 not availableSD 6.7 6.6 10.4
48
Range 8.0-45.0 3.0-25.0+ not availableEmployment
Setting:Independent Practice 89.0% 83.0% 75.5* Middle Atlantic (New Jersey, New York, Pennsylvania); South Atlantic (Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia); Pacific (Alaska, California, Hawaii, Oregon, Washington); East North Central (Illinois, Indiana, Michigan, Ohio, Wisconsin); New England (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont); West South Central (Arkansas, Louisiana, Oklahoma, Texas); West North Central (Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota); Mountain (Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, Wyoming); East South Central (Alabama, Kentucky, Mississippi, Tennessee)
49
Given that our study participants are very similar to both those in the
random sample and the entire membership in terms of gender
(approximately 60% males and 40% females across all three groups), age
(approximately mid-fifties across all three groups), race (over 90% Caucasian
in all three groups), degree (over 80% hold a Ph.D. in all three groups), years
licensed (around 20 years for all three groups), practice setting (on average
83% independent practice across the three groups) and geographic
distribution, it can be stated that our study sample is representative of not
only the random sample of Division 42 members provided by the APA
Research Office, but also the entire Division 42 membership. This is very
important given that one goal of our study was to recruit a representative
volunteer sample of independent practitioners from Division 42 who would
become the foundation of the IP-Net for future research studies, and the
collection of longitudinal data on patterns and trends of those in independent
practice.
Table 2 examined the composition of those who volunteered to
participate in our study in terms of their response method of online versus
mail, and compared the two groups on the same characteristics as those
presented in the previous table. Although there are no significant differences
between the two groups, it is interesting to note that the online group
reported a smaller percentage of individuals working primarily in independent
practice settings (85%), compared to the mail group (93%). This difference
fits with information discussed in chapter 1 stating that it may be cost-
prohibitive to incorporate technology applications into an independent
practice setting, whereas if one is at a larger group practice, hospital, or
50
academic setting, it is more likely that funding will be available to support the
incorporation of various technology applications.
51
Table 2. Participant Characteristics from Responses to Surveys for Online and Mail Groups
ONLINE GROUP MAIL GROUPVARIABLE Number Percent Number Percent
Gender: Male 43.0 64.0% 55.0 66.0%
Female 24.0 36.0% 29.0 34.0%Race: Caucasian 66.0 96.0% 84.0 100.0%
Hispanic 2.0 3.0% 0.0 0.0%American Indian 1.0 1.0% 0.0 0.0%
Age: Mean 53.5 54.4
Median 54.0 55.0 SD 6.0 6.4
Range40.0-66.0 38.0-74.0
*Region: Middle Atlantic 21.0 30.0% 21.0 25.0%
South Atlantic 8.0 12.0% 13.0 16.0%Pacific 12.0 17.0% 8.0 10.0%
East North Central 8.0 12.0% 14.0 17.0%New England 4.0 6.0% 9.0 11.0%
West South Central 6.0 9.0% 3.0 4.0%West North Central 5.0 7.0% 6.0 7.0%
Mountain 3.0 3.0% 4.0 5.0%East South Central 2.0 3.0% 5.0 6.0%
Degree: Ph.D. 59.0 87.0% 72.0 86.0%
Psy.D 6.0 9.0% 2.0 2.0%Ed.D 3.0 4.0% 10.0 12.0%
Years Licensed: Mean 20.0 21.4
Median 21.0 22.0 SD 7.0 6.3
Range 8.0-35.0 9.0-45.0 Employment Setting:
Independent Practice 58.0 85.0% 76.0 93.0%Academic 4.0 6.0% 2.0 2.0%
Hospital 4.0 4.0% 2.0 2.0%Clinic 1.0 1.0% 0.0 0.0%
Other Human Service 2.0 3.0% 2.0 2.0%* Same regional distribution as Table 1
52
Practice Characteristics of Study Participants
In addition to data on participant’s personal characteristics, we also
collected information related to their practice of psychology, which is
presented in Tables 3-5. Table 3 presents information about how and where
the individual works, including number of years at the current practice
setting, income, theoretical orientation toward practice, if they measure
patient satisfaction or perform outcome research, and their community
demographics such as socioeconomic status and population size of the city
where they work.
Socioeconomic and geographic (population size of community)
information was based upon demographic data obtained from the United
States Census Bureau (United States Census Bureau) and ESRI Business
Information Solutions (ESRI Business Information Solutions) according to the
zip code listed by participants (note that individual zip codes were examined
in terms of city demographics; for example, a city like Manhattan is
represented by many individual zip codes).
Results of a t-test indicated that there was a significant difference
between the online and mail groups in terms of average income t (129) = -
3.18, p <.05 (one-tailed), d = -0.56. The average income reported by the
mail group ($107,000, SD = $48,696) was significantly higher than the
average income reported by the online group ($81,388, SD = $40,292).
53
Table 3. Practice Characteristics from Responses to Surveys for Online, Mail, and Total Sample
VARIABLE ONLINE GROUP MAIL GROUP TotalYrs @ Current Setting:
Average 16.4 16.6 16.5 Median 17.0 17.0 17.0
SD 7.5 7.3 7.4 Range 1.0-31.0 0.5-35.0 0.5-35.0
*Income: Average 81,388 107,000 94,194Median 100,000 100,000 100,000
SD 40,292 48,696 44,494
Range30K-200K
16K-250K
16K-250K
Theoretical Orientation:
Psychodynamic 9.0 13% 15.0 18% 24.0 16%Humanistic 6.0 9% 4.0 5% 10.0 7%
CBT 24.0 36% 30.0 37% 54.0 36%Family Systems 9.0 13% 7.0 8% 16.0 11%
Feminist 3.0 4% 1.0 1% 4.0 3%Multicultural 3.0 4% 2.0 2% 5.0 3%
Eclectic 14.0 21% 24.0 29% 38.0 24%Measure Patient Satisfaction:
Yes 17.0 28% 16.0 21% 33.0 25%No 44.0 72% 59.0 79% 103.0 75%
Perform Outcome Research:
Yes 8.0 13% 7.0 10% 15.0 11%No 55.0 87% 66.0 90% 121.0 89%
SES of Community: High 31.0 45% 30.0 36% 61.0 40%
Middle 32.0 46% 47.0 57% 79.0 52%Low 6.0 9% 6.0 7% 12.0 8%
Population Size: Under 10000 –
50,000 29.0 44% 34.0 41% 63.0 42%50,001 – 500,000 26.0 37% 32.0 39% 58.0 38%500,001 – over 1
million 13.0 19% 17.0 20% 30.0 20%*Denotes significant difference (p <.05) between online and mail groups
Practice Structure and Organization
Data collected on how participants structure and organize their
practice are presented in Table 4. We inquired how the following
administrative tasks were managed: billing, scheduling, accounts payable,
54
answering the telephone, and word processing. Specifically, we asked
participants to rate who in their practice was primarily responsible for
managing these tasks. Participants had a choice of responding in the
following manner: self, employee, contracted out and significant other. There
were no significant between group differences for any of the tasks. However,
it can be noted that the online group reported performing scheduling,
accounts payable, phone, and word processing tasks themselves more often
compared to the mail group, who reported more often that an employee
handled the task. The mail group reported managing the billing tasks
themselves more often as compared to the online group, who reported more
often that an employee handled the billing tasks.
Table 4. Person Responsible for Various Administrative Tasks from Responses to Surveys for Online, Mail, and Total Sample
ONLINE GROUP MAIL GROUP TotalVARIABLE Number Percent Number Percent Number Percent
Billing: Self 32 48% 43 52% 75 50%
Employee 25 37% 24 29% 49 33%Contracted Out 7 11% 13 15% 20 13%
Significant Other 3 4% 3 4% 6 4%Scheduling:
Self 51 75% 56 68% 107 71%Employee 16 24% 25 30% 41 27%
Contracted Out 0 0% 0 0% 0 0%Significant Other 1 1% 1 1% 2 1%
Accts Payable: Self 47 70% 45 54% 92 61%
Employee 14 21% 28 34% 42 28%Contracted Out 2 3% 7 8% 9 6%
Significant Other 4 6% 3 4% 7 5%Phone:
Self 45 66% 44 54% 89 59%Employee 20 29% 34 41% 54 36%
Contracted Out 2 3% 3 4% 5 3%Significant Other 1 1% 1 1% 2 1%
Word Processing:
Self 44 65% 39 48% 83 55%
55
Employee 16 24% 29 35% 83 30%Contracted Out 6 9% 9 11% 15 10%
Significant Other 2 3% 5 6% 7 5%
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Average Number of Clinical Sessions per Patient
Data collected on the average number of sessions a patient was seen
by participants at their respective practices are in Table 5. Overall,
respondents reported that on average 6.5% of their caseload was seen for
only one session, 12.8% of their caseload was seen for 2-5 sessions, 23.5%
was seen for 6-10 sessions, 18.9% was seen for 12-15 sessions, 17.4% were
seen for 16-20 sessions, and 30.9% were seen for over 21 sessions. There
were no significant between group differences for average number of patient
sessions.
Table 5. Average Number of Clinical Sessions per Patient by Percent from Responses to Surveys for Online, Mail, and Total Sample
Avg Sessions ONLINE GROUP MAIL GROUP TOTAL
Per Patient Percent Percent Percent1
Average 6.70% 6.25% 6.48%Range 1.00-30.00% 1.00-20.00% 1.00-50.00%
2-5 Average 11.80% 13.74% 12.77%
Range 2.00-30.00% 1.00-35.00% 1.00-40.00%6-10
Average 23.30% 23.65% 23.48%Range 5.00-70.00% 4.00-64.00% 4.00-70.00%
11-15 Average 19.50% 18.30% 18.90%
Range 1.00-50.00% 1.00-40.00% 1.00-50.00%16-20
Average 17.02% 17.80% 17.41%Range 1.00-40.00% 1.00-45.00% 1.00-45.00%
21+ Average 29.59% 32.14% 30.87
Range 1.00-95.00% 1.00-100.00% 1.00-100.00%
57
Current and Future Technology Applications in Practice
Specific to this study and its hypotheses, data were collected on
participants’ use of technology applications in practice. Table 6 details data
collected from participants regarding the rates of current use and anticipated
future use of various technology applications in practice. For future use,
participants were asked to indicate the technology applications they thought
they might add to their practice, but not count continued use of applications
currently being employed in their practice. The technology applications
inquired about in this study were those most frequently reported in the
literature. Additionally, the present study inquired about the following
Internet categories that were absent from previous studies: Internet for
continuing education credits, Internet for marketing, and Internet for job
recruitment. The results reported in this study demonstrate increased use
compared to the most recent studies available in the literature.
Examination of Table 6 revealed that in terms of current technology
use in practice, respondents in the online group reported overall higher rates
compared to the mail group for billing, scheduling, maintaining files, outcome
research, recording patient homework, testing, word processing, e-mail with
other professionals, e-mail with patients, e-mail with supervisees, use of the
Internet to obtain information, use of the Internet for therapy, use of the
Internet for marketing and advertising, and use of the Internet for job
recruitment. The only technology application that the online and mail groups
reported equal rates of endorsement was use of the Internet for obtaining
continuing education credits. It should be noted that no participants
endorsed current or anticipated future use of technology applications for an
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intake interview, which is the only category with no endorsement across both
groups.
Chi-square analyses for between group comparisons on technology
use, as determined by participant’s yes or no response, revealed that the
online group was significantly more likely to use technology applications for
the following tasks: maintaining files X2(1, N = 46) = 8.02, p = .01), outcome
research X2(1, N = 13) = 5.60, p = .02), recording patient homework X2(1, N
= 12) = 7.44, p = .01), e-mail with professionals X2(1, N = 83) = 8.88, p =
<.01), e-mail with patients X2(1, N = 40) = 12.95, p = <.01), and use of the
Internet for information X2(1, N = 95) = 8.44, p = <.01).
Overall for both groups, in terms of anticipated future technology use
in practice, the only areas reporting a slight increase were an additional 6%
for billing, 6% for recording patient homework, 6% for testing, and 10% for
using the Internet to obtain continuing education credits. It should also be
noted that both groups reported no anticipated future use of e-mail with
patients, however, members of both the online and mail groups did report
current use of this technology application. There were no significant between
group differences related to anticipated future technology use. The question
for future technology use specifically asked for those individuals not currently
using a particular application, if they anticipated using it in the near future
(approximately 6 months). Therefore, the potential rates of future use were
limited by those already reporting current use.
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Table 6. Current and Anticipated Future Technology Use in Practice from Responses to Surveys for Online, Mail, and Total Sample
ONLINE GROUP MAIL GROUP TotalVARIABLE Number Percent Number Percent Number Percent
Current Tech Use: Billing 58 84% 63 75% 121 80%
Scheduling 21 30% 16 19% 37 25%*Maintaining Files 29 42% 17 20% 46 31%
*Outcome Research 11 15% 2 2% 13 8%*Recording Pt HW 12 17% 0 0% 12 7%
Testing 34 49% 36 43% 70 46%Intake Interview 0 0% 0 0% 0 0%Word Processing 58 84% 62 74% 120 79%
*E-mail Professionals 47 68% 36 43% 83 55%
*E-mail Patients 29 42% 11 13% 40 27%E-mail Supervisees 8 12% 3 4% 11 8%
*Internet for Info 52 75% 43 52% 95 63%Internet for Therapy 6 9% 3 4% 9 7%
Internet for CEUs 5 7% 6 7% 11 7%Internet for
Mktg/Ads 8 12% 6 7% 14 10%Internet for Job
Recruit 1 1% 1 1% 2 1%Future Tech Use:
Billing 5 7% 3 4% 8 6%Scheduling 1 1% 1 1% 2 1%
Maintaining Files 1 1% 2 2% 3 2%Outcome Research 3 4% 4 5% 7 5%
Recording Pt HW 4 6% 4 5% 8 6%Testing 2 3% 7 8% 9 6%
Intake Interview 0 0% 0 0% 0 0%Word Processing 0 0% 1 1% 1 1%
E-mail Professionals 3 4% 3 4% 6 4%E-mail Patients 0 0% 0 0% 0 0%
E-mail Supervisees 3 4% 1 1% 4 3%Internet for Info 0 0% 4 5% 4 3%
Internet for Therapy 3 4% 0 0% 3 2%Internet for CEUs 8 12% 7 8% 15 10%
Internet for Mktg/Ads 3 4% 5 6% 8 5%
Internet for Job Recruit 1 1% 1 1% 2 1%
*Denotes significant difference (p <.05) between online and mail groups
Average Time Spent per Week with Various Technology Applications
We also asked for detailed information on the average amount of time
per week participants spent using the telephone, e-mail, Internet, and video
60
applications, and if they were reimbursed for these services. Results detailed
in Tables 7 and 8 show the number of participants who stated they used an
application, as well as the average number of hours per week (broken down
into minute increments) they used the application.
Previous research studies reported in the literature have identified the
telephone as “universally accepted” in terms of its use in practice. This is
also the category for which the highest rates of average weekly use were
reported by our sample. The only significant difference noted between the
online and mail groups was in terms of the average amount of time per week
spent doing telephone referrals, with the online group reporting a higher
amount t (41) = 2.19, p <.05 (one-tailed), d = 0.68.
Table 7. Average Weekly Telephone Use and Reimbursement in Practice from Responses to Surveys for Online, Mail, and Total Sample
ONLINE GROUP MAIL GROUP TotalVARIABLE Number Percen
tNumber Percen
tNumber Percen
tTelephone Consultation:
N=31 45% N=32 38% N=63 41%
Hours Per Week Mean
1.30 1.30 1.30
Median 1.00 1.00 1.00SD 0.65 0.82 0.74
Range 0.10-3.00 0.10-3.50 0.10-3.50Reimbursed N=14 41% N=17 51% N=21 33%
Telephone Therapy: N=23 33% N=33 39% N=56 37%Hours Per Week
Mean 1.30 1.25 1.23
Median 1.00 1.00 1.00SD 0.94 0.72 0.83
Range 0.05-2.00 0.25-3.00 0.05-3.00Reimbursed N=22 85% N=13 38% N=35 63%
Telephone Supervision:
N=4 6% N=7 8% N=11 7%
Hours Per Week Mean
0.90 1.00 0.95
Median 1.00 1.00 1.00SD 0.25 0.50 0.38
Range 0.50-1.00 0.50-2.00 0.50-2.00
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Reimbursed N=4 100% N=3 43% N=7 64%
* Telephone Referrals:
N=22 32% N=21 25% N=43 28%
Hours Per Week Mean
1.30 0.98 1.14
Median 1.00 1.00 1.00SD 0.52 0.43 0.48
Range 0.25-4.00 0.25-2.00 0.25-4.00Reimbursed N=2 9% N=1 3% N=3 7%
*Denotes significant difference (p <.05) between online and mail groups
Table 8. Average Weekly E-mail Use and Reimbursement in Practice from Responses to Surveys for Online, Mail, and Total Sample
VARIABLE ONLINE GROUP MAIL GROUP TOTALE-mail
Consultation:N=7 10.0% N=7 8.0% N=14 0.9%
Hours Per Week Mean
0.75 0.80 0.78
Median 1.00 1.00 1.00SD 0.32 0.31 0.31
Range 0.25-1.00 0.25-1.00 0.25-1.00Reimbursed N=2 29.0% 1.00 14.0% N=3 21.0%
E-mail Therapy: N=2 3.0% N=1 1.0% N=3 0.2%Hours Per Week Mean
0.75 0.50 0.63
Median 0.75 0.50SD 0.35
Range 0.50-1.00 0.50-1.00Reimbursed N=0 0.0% N=00 0.0% N=0 0.0%
E-mail Supervision: N=2 3.0% N=0 N=2 3.0%Hours Per Week Mean
0.55 0.55
Median 0.55 0.55SD 0.63 0.63
Range 0.10-1.00 0.10-1.00Reimbursed N=2 100.0
%N=2 100.0%
E-mail Referrals: N=4 6.0% N=3 4.0% N=7 0.5%Hours Per Week Mean
0.75 0.50 0.63
Median 1.00 0.25 0.63SD 0.43 0.43 0.43
Range 0.25-1.00 0.25-1.00 0.25-1.00Reimbursed N=0 N=0 N=0 0.0%
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Although reporting some endorsement, the other categories of e-mail,
use of the Internet, and video technologies in clinical practice were still low in
comparison to results reported for the use of the telephone in practice.
Reported use for Internet and video applications were near zero, and
therefore are not presented in table format. Additionally, it should be noted
that analyses were not run for the e-mail category due to the low rate of
endorsement by participants.
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Attitudes Toward Technology
Also specific to this study and its hypotheses are the results from the
Attitudes Toward Computers Questionnaire (Jay, 1989) with its seven
dimensions of (1) comfort, (2) efficacy, (3) gender equality, (4) control, (5)
dehumanization, (6) interest, (7) utility, and a total score. Fifty-four out of 69
people from the online group (78%) and 76 out of 84 people from the mail
group (90%) responded to the measure. It should be noted that the ATCQ
measure appeared as the last item on the questionnaire. It is likely that the
lower response rate from online group participants is due to the placement of
this item, since the questionnaire had to be answered in one sitting for the
online group with data submitted thru the Web site, and the online session
could not be saved for completion at a later time. Given the overall long
length of our questionnaire (an issue noted by many respondents in terms of
feedback), it is probable that members in the online group may have tired or
not had the extra time to respond to this last item, but also did not want to
wait to complete the questionnaire at a later time and lose all of their current
data responses. Not allowing participants to save responses to complete at a
later time was done as a security measure to protect participant
confidentiality. However, it appears that this may have been done at the
expense of an increased response rate. A shorter length questionnaire would
have likely remedied this issue and should be considered for future studies
using the Internet for data collection.
As predicted, results of analyses indicated that the online group
reported significantly more positive attitudes as determined by higher scores
on the ATCQ in all areas, with the exception of gender equality, where there
64
was no significant difference between the online and mail groups. See Table
9 below for a summary of statistical results.
65
Table 9. Attitudes Toward Computer Questionnaire Scores from Responses to Surveys for Online, Mail, and Total Sample
ONLINE GROUP
MAIL GROUP TOTAL STATISTICAL
VARIABLE N=54 N=76 N=130 Results
(df=128)*Comfort:
Mean 3.9 3.3 3.6 t = 3.92Median 4.0 3.0 3.5 d = 0.69
SD 0.8 0.9 0.9*Efficacy:
Mean 4.4 4.1 4.3 t = 3.01Median 5.0 4.0 4.5 d = 0.53
SD 0.5 0.6 0.6Gender Equality:
Mean 4.5 4.3 4.4 t = 1.80Median 5.0 4.0 4.5 d = 0.32
SD 0.5 0.7 0.6*Control:
Mean 4.3 4.0 4.2 t = 3.37Median 4.0 4.0 4.0 d = 0.60
SD 0.5 0.5 0.5*Dehumanization:
Mean 1.9 2.3 2.1 t = -3.21Median 2.0 2.0 2.0 d = -0.57
SD 0.7 0.7 0.7*Interest:
Mean 4.3 3.9 4.1 t = 3.75Median 4.0 4.0 4.0 d = 0.66
SD 0.6 0.6 0.6*Utility:
Mean 4.2 4.0 4.1 t = 2.07Median 4.0 4.0 4.0 d = 0.37
SD 0.6 0.5 0.6*Total:
Mean 4.3 3.9 4.1 t = 4.87Median 4.0 4.0 4.0 d = 0.86
SD 0.4 0.5 0.5*Denotes significant difference (p <.05) between online and mail groups
Note: Range of scores = 1 to 5 (1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, and 5 = Strongly Agree). The Dehumanization dimension is reverse scored. Higher scores indicate increased levels of comfort using computers, increased feelings of efficacy using computers, increased feelings that computers are important for both genders, increased belief that people are in control of computers, increased belief that computers cannot operate without human interaction, increased interest in using computers, and increased belief that computers are useful. The total score is the overall average of the other seven dimensions.
66
Hypotheses Testing and Predictor Variables
The three main hypotheses for this study were that, (1) those who are
newer to the profession, as determined by number of years licensed, would
be more accepting and more likely to use available technology applications;
(2) those with more positive attitudes toward computers, as determined by a
total score of 4 or above on the Attitude Toward Computers Questionnaire
(ATCQ, Jay, 1989), would be more likely to use available technology
applications; and (3) those not in solo private practice would also be more
accepting and more likely to use available technology applications.
Technology use was examined in terms of overall reported use, taken as the
sum total of the number of categories endorsed as presented in Table 6.
First Hypothesis. ANOVA revealed that number of years licensed was
found to be unrelated to amount of technology use reported F (17, 133) =
0.95, p=0.51). Attitudes toward technology were also found to be unrelated
to number of years licensed F (3, 149) = 2.04, p = 0.11. Therefore, we must
reject the alternative hypothesis and accept the null hypothesis that number
of years licensed is independent of technology use and attitudes toward
technology.
ANOVA measures were also performed to determine if age would have
better predicted amount of technology use and attitudes toward technology.
Age was also found to be unrelated to amount of technology use F (17, 133)
= 1.55, p=.09) or attitudes toward technology F (3, 149) = 1.10, p=.35.
Third Hypothesis. Chi-square analyses were used to examine
differences in technology use and attitudes based upon practice setting
(independent practice, academic, hospital, clinic, and other). Practice setting
67
was found to be unrelated to amount of technology use X2(10, N = 128) =
7.30, p = .70) or attitudes toward technology X2(33, N = 153) = 35.32, p
= .36). Therefore, we must reject the alternative hypothesis and accept the
null hypothesis that practice setting is independent of technology use and
attitudes toward technology.
Second Hypothesis. Our second hypothesis concerning attitudes
towards technology and use of technology applications, tested using chi-
square analyses, was partly supported in terms of certain technology
applications. Those with more positive attitudes toward technology (as
measured by their total score on the ATCQ of 4 or higher, given that a score
of 3 or below represented neutral or negative attitudes), reported
significantly higher levels of current technology use (measured by the total
number of technology applications endorsed as being used by participants) in
the following areas: scheduling X2(4, N = 130) = 23.92, p = <.01),
maintaining patient files X2(4, N = 130) = 13.06, p = .01), performing
outcome research X2(4, N = 130) = 9.99, p = .04), testing X2(4, N = 130) =
13.41, p = .01), using the Internet to obtain information X2(4, N = 130) =
22.19, p = <.01), using the Internet for therapy X2(4, N = 130) = 12.85, p
= .01), using the Internet to obtain continuing education credits X2(4, N =
130) = 9.36, p = .05), using the Internet for marketing/advertising X2(4, N =
130) = 10.64, p = .03), and using the Internet for job recruitment X2(4, N =
130) = 82.86, p = <.01). It should be noted that use of the Internet for job
recruitment had an overall very low reported rate of use (1%). Therefore, we
can reject the null hypothesis and accept the alternative hypothesis that use
68
of the technology applications listed above is related to attitudes toward
technology.
Chi-square analyses also revealed that no significant differences were
noted for billing X2(4, N = 130) = 8.61, p = .07), recording patient homework
X2(4, N = 130) = 4.13, p = .39), word processing X2(4, N = 130) = 4.70, p
= .32), e-mail with other professionals X2(4, N = 130) = 1.58, p = .81), e-mail
with patients X2(4, N = 130) = 2.14, p = .71), and e-mail with supervisees
X2(4, N = 130) = 3.32, p = .51). Therefore, we must reject the alternative
hypothesis and accept the null hypothesis that use of the technology
applications listed above is independent of attitudes toward technology. It
should be noted that billing and word processing were the two technology
applications with the highest total rates of reported use in this study (80%
and 79%, respectively), which may be related to the absence of significant
findings. Additional chi-square analyses determined that gender, degree,
theoretical orientation, geographic location, nor population size were related
to technology use or attitudes toward technology.
Additional Between Group Differences for Online and Mail Responders
In looking at between group differences, results of chi-square analyses
determined that type of graduate degree and theoretical orientation were
both independent of choice of response mode (online versus mail). Results of
ANOVA tests determined that number of years licensed and age were also
independent of response group (online versus mail). Therefore none of these
variables can be used as predictor variables for response method group
categorization.
Possible Subgroup Differences
69
In looking at the possibility of various subgroups emerging from our
sample, chi-square analyses determined that neither population size nor
geographic location were related to gender, technology use, attitudes toward
technology, and the office tasks reported in Table 4 above (billing,
scheduling, accounts payable, phone, and word processing). ANOVA
determined that neither population size nor geographic location was related
to income or the average number of sessions per patient. It should be noted
that the relationship between population size and income approached
statistical significance F (9, 143) = 1.85, p=.06, with those practicing in
locations with larger populations reporting larger incomes, but we cannot
reject the null hypothesis that the two are independent. In terms of gender
differences, results of chi-square analyses determined that there is no
relationship between gender and amount of technology use or attitudes
toward technology.
Use of the Internet for Data Collection
For those who responded via the Internet, 23% reported that this was
their first Web survey, 29% reported that our Web survey was easier to use
compared to past Web surveys, 44% rated the difficulty level to be the same,
and 4% rated it as more difficult to use compared to other Web surveys.
Forty-two percent of those responding stated that the option to participate
via the Web increased their desire to participate, and 62% reported that had
the survey only been available via the Web, they still would have
participated. This is an important consideration for future IP-Net studies
employing the same methods of data collection.
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Chapter Four
Discussion
The primary focus of the current study was the investigation of
technology use and related attitudes toward technology by psychologists in
independent practice. In addition, this study served as the initial step in a
larger effort to develop a database, IP-Net, which will allow for on-going
investigation of patterns and trends in independent practice. While this
paper does not go into detail discussing practice research networks, as stated
earlier, it should be noted that these are becoming a popular new method for
collecting real-time data with high internal and external validity, embraced by
state organizations as well as the American Psychological Association, and
other health related associations (Borkovec, Echemendia, Ragusea, & Ruiz,
2001).
In this chapter we will first discuss the methodological factors related
to the present study and the overall IP-Net project. We will then turn to an
examination of the two response groups and the characteristics of
independent practitioners and their practices. Next, we look at the findings
related to technology use in practice and the relationships between
participants’ attitudes toward technology and the use of technology
applications in the administrative and clinical aspects of practice, as related
to the study’s hypotheses. Finally, we end with a discussion of conclusions
and future directions based upon the findings of the present study.
Findings Related to Survey Method
Collection of data by online surveys offers many potential advantages
to investigators and is discussed below. In relation to using the Internet to
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collect data for a practice research network, online data collection facilitates
repeatedly surveying the same participants. However, research has not yet
provided conclusive information about important dimensions of this approach
to data collection. Therefore, we do not know if there are systematic
differences between respondents who respond online and those who respond
by mail. We also do not know if the approach we have taken to repeatedly
survey the same participants through IP-Net will yield usable data. This study
provides initial findings to help clarify these issues. In the course of our study
we encountered some practical and procedural issues that arise from the use
of this fairly new methodology, which are also addressed below.
Using the Internet in Research. A study by Mehta and Sivadas (1995)
compared response rates and response content in mail versus electronic mail
surveys. Study results indicated that (1) e-mail survey responses were
received more quickly (2-3 days) compared to mail surveys (3 weeks); (2) e-
mail surveys were much less expensive (free) compared to mail surveys
(minimum cost of $0.58 each piece); (3) these first two findings become even
more important when considering contacting international respondents (i.e.,
Mehta & Sivadas, 1995 had 150 respondents from outside the USA); (4) e-
mail survey allowed for quick clarification (respondents could email the
researchers questions regarding the survey as they were working on it (i.e.,
some European respondents did not know what the term “significant other”
meant and were able to question the researchers via e-mail before
responding incorrectly to the question); and (5) e-mail responses to open-
ended questions were judged to be qualitatively more informative and
detailed compared to mail responses.
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Similar results were found with the present study in certain areas. For
example, Internet responses were logged quicker than receipt of mail
response, however we were unable to do a true comparison test due to the
fact the mail materials were mailed out from APA Division 42’s office in
Arizona without keeping record of exact dates of mailing. The cost savings
were substantial compared to the mail survey. For those who did not directly
log on to the Website, we incurred the cost of their reply postcard
(approximately $0.20), as well as the cost of the mailing of the actual study
materials (approximately $0.90) plus the cost of printing the mail materials
and the envelopes.
The online method in this study also allowed for a quick response time
for questions e-mailed through the Web page by participants, versus those
who wrote in the margins of the mail instruments and never received a
response. The online method created a natural “paper trail” which allowed
for automatic tracking of who had responded to the survey and who needed
to receive a follow-up reminder e-mail, versus having to manually track the
mail method.
Results reported by Mehta and Sivadas (1995) are similar to results
reported in related studies (i.e., Stanton, 1998; Schmidt, 1997; Schaefer &
Dillman, 1998). Studies incorporating data collection via the Internet are
becoming popular for those in health professions, as evidenced by the
increasing number of practice research networks (i.e., Zarin, Pincus, West, &
McIntyre, 1997; Zarin et al., 1998; Pincus et al., 1999; Wasserman, Croft, &
Brotherton, 1992; Green et al., 1984; Barlow, 1996).
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Additional Advantages to Internet Research. Other advantages to
using a Web-based survey method of data collection include supply of a wider
diversity of participants, reduction of the influence of demand characteristics,
and efficient administration of survey protocols (Hewson, Laurent, & Vogel,
1996). Surveys that employ the Internet for data collection provide access to
a wider diversity of participants, and also allows for targeting of specific
groups in a more efficient way than mail surveys.
Internet surveys also provide greater anonymity than mail surveys,
which has been found to reduce the effects of confounding factors due to
demand characteristics, different treatment due to biopsychosocial
attributes, and social conformity, thus encouraging greater honesty and
cooperation from participants (Esposito, Agard, & Rosnow, 1984; Rosenthal,
1967). To ensure confidentiality, responses submitted via the Internet or e-
mail must have any identifying information removed and replaced with a
random subject identification number. This is how online data were managed
in our study, and participants were informed of this in the informed consent
letter (Appendix A). Additionally, password information should be stored in a
separate database to protect participant’s confidentiality. This particular
study also used password protections, and protected participant
confidentiality by storing any identifying information in a separate database
and assigning random subject identification numbers to participants.
Another advantage with online research is that survey data that are
directly entered via the Web by participants eliminates the data entry step
for the researcher. Data entered this way can also eliminate the potential for
unwanted responses, by forcing a choice for participants (i.e., only allowing a
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numerical response to be entered thus avoiding participants from providing
unwanted information). These types of checks that avoid unwanted response
types, duplicate submissions, and other potential problems must be put in
place by a computer programmer, which can significantly add to the cost of a
research study, and therefore is not always a viable option. This particular
study was fortunate to have had a professional computer programmer that
worked on the project at no cost. Therefore many of these checks were
employed, but not all possible checks, due to the fact that the programmer
designed the Website on a voluntary basis in his spare time.
Disadvantages to Internet Research. In terms of negative aspects to
collecting data via this method, study results from Mehta and Sivadas (1995)
indicated that (1) not everyone has access to the Internet or e-mail or uses
it; (2) it may be more appropriate to use Internet or e-mail surveys with
middle to upper-middle class respondents, or respondents that belong to a
targeted population with narrowly defined interests; (3) Internet and e-mail
users are sensitive about their accounts and receiving unsolicited messages;
(4) most Internet and e-mail users have to pay to receive their messages
(e.g., monthly fees for having an Internet service provider) unlike getting
their mail for “free” from their mailbox; (5) because of the annoyance
associated with receiving unsolicited e-mail messages, the researchers in the
Mehta and Sivadas (1995) study had to eliminate their “unsolicited group”
from data analyses, because so many of the members of this group
requested to be removed from the mailing list (therefore it is a good idea to
obtain permission from respondents to send an e-mail survey, but this may
also leave the researcher with a self-selected sample); and (6) cannot provide
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the same type of incentives as with a mail survey (i.e., cannot send money
via e-mail) therefore you may have lower response rates but those who do
respond will be more motivated (a possible issue of sample bias). Another
consideration to keep in mind when designing a Web-based survey is that not
all browsers have the same functional capacities nor do all Internet service
providers allow for similar speed connections. Therefore, having minimal
graphics and testing on various browsers will help to eliminate potential
problems. This consideration was taken into account when designing the
Web page for our study.
Issues Related to Participating in IP-Net. Of the 2,000 Division 42
members who were contacted to volunteer to participate in this IP-Net study,
265 (13%) agreed to be part of the study. This is much lower compared to
other studies conducted using Division 42 members, which tends to be
between 30% and 40% (Michael J. Murphy, Ph.D., personal communication
June, 2002). Of those who agreed to participate, ultimately only 161 actually
participated, resulting in a low response rate of only 8%.
A potential reason for the overall low response rate may be the result
of budgetary constraints, which did not allow for an incentive to participate
(such as reduced membership fees, etc.) to be offered. Also, we were asking
respondents to sign up to participate in a series of future studies, in addition
to the present study involved, which may have been more of a commitment
than participants were willing to make at this time, especially without extra
incentive.
It is possible that given our small sample size we may not have been
able to detect differences or support our hypotheses. Additionally, our
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sample was restricted in range in terms of age, race, practice setting, and
number of years licensed, which also may have detracted from our ability to
detect differences and support our hypotheses. However, given that our
sample is very similar to the membership of Division 42, it is much more
likely that our findings are accurate and representative of this population.
Issues Related to Online Response Rates. A procedural issue that
directly impacted online responders was related to the placement of the “IP-
Net” research link on the Division 42 Homepage (means by which the survey
was made available to participants as stated in their invitation letter). The
link was not prominently placed on the page, and initially could only be seen
via Microsoft’s Internet Explorer, but not Netscape/Mozilla. This problem was
immediately corrected once the researchers were contacted via e-mail by
several study participants, but may have led to the loss of participants willing
to answer the survey online or subsequently request a mail version of the
survey. Additionally, related to online participation, it may be that seeing the
visual mail materials on one’s desk is more motivating than trying to
remember to log on to complete a survey.
Issues Related to Mail Response Rates. A procedural issue that may
have affected mail participants is the fact that some of the response
envelopes were received by the researchers as postage due. This only
happened from certain areas of the country, despite the envelopes all
containing the same number of pages and therefore being the same weight.
Some participants actually put an additional stamp on the envelope, whereas
others may have been discouraged by this and simply not returned the
envelope, despite having completed the survey.
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Ultimately the two response groups were very similar and yielded few
significant between group differences in terms of personal and practice
characteristics, with both composed of participants representative of Division
42. However, it should also be noted that 62% of those who responded
reported that had the survey only been available via the Web, they still would
have participated, and 42% actually stated that the option to participate on
the Web increased their desire to respond. Also, the majority (73%) of those
who responded online indicated that our Web survey was easier or the same
level of difficulty as compared to previous Web surveys. Only 4% indicated
that they found our Web survey to be more difficult compared to others.
Therefore, it appears that by incorporating what was learned from this initial
Web effort, utilizing the Internet for future IP-Net studies would be a viable
and efficient option.
Issues for Investigation in Subsequent Surveys. We received feedback
from a few non-respondents that the survey simply appeared too long for
them to even consider completing. A few participants also gave feedback at
the end of the survey stating that the instrument had taken them longer than
anticipated to complete. As the second stage of this larger IP-Net project is
implemented, the length of the questionnaire will be considerably shortened.
Feedback from both participants and non-participants is important at this
stage in the development of IP-Net to ensure that we are able to retain a
foundation sample, as well as increase the membership with newly recruited
volunteers. The ability to retain and recruit a representative pool of
volunteer participants will ultimately determine the effectiveness of IP-Net as
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a research tool to study patterns and trends among independent
practitioners.
As with most survey method studies, issues arose related to omissions
and errors with the questionnaire instrument. However, a strong advantage
to longitudinal research such as IP-Net is that these issues can be corrected
through later studies if needed. Issues related to the present study that
require additional clarification include a question about full versus part-time
employment status, which impacted other data interpretations such as
income differences among subgroups. Another point of clarification related
to income is whether reported income was based upon total annual income or
total household income versus income solely from what was earned in clinical
practice, which again impacts the understanding of other personal and
practice characteristics. Due to the omission of these clarification questions,
we were unable to make conclusive statements regarding the income
differences of various subgroups (such as by gender, population size of
community, etc.). We also must view our finding of significant between
group differences for online and mail responders related to income level
cautiously, since it is possible that this difference could be accounted for by
factors such as part time employment and income from sources outside of
clinical practice.
Related to the practice characteristic of the average number of
sessions a patient was seen, future studies should clarify if those included in
the one session only category were seen exclusively for assessment
purposes, versus those who did not follow through with therapy. Another
point of clarification would be to inquire if those patients who were seen for
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over 21 sessions were private pay versus third party payment. Finally,
further clarification regarding the reasoning behind the average number of
sessions reported (such as restrictions by managed care, theoretical
orientation, etc.) should be investigated.
Related to technology use, this study also attempted to examine
reasons why participants did not endorse certain technology applications for
various practice tasks. However, the method in which the question was
phrased (Appendix B, last column of #34) did not produce meaningful data.
Specifically, participants tended to respond with “yes” to the open-ended
question rather than specifying their reasons for not using the various
technology applications. Therefore, we were unable to answer if people were
either not familiar with technology, believed it to be unethical, dehumanizing,
not cost-effective, the opportunity never presented, or additional factors. If
additional IP-Net studies continue to examine adoption of technology
applications in practice, then this will be an important issue to address.
Findings Related to Comparability of Response Groups
Group Differences. The two response method groups, online and mail,
were very similar in terms of number of participants, gender, race, age,
geographic region, degree, years licensed, and employment setting.
Although the online group contained more individuals who reported their
primary work setting to be academic (6%) compared to the mail group (2%),
the mail group contained more individuals who reported their primary work
setting to be independent practice (93%) compared to the online group
(85%). It should be noted that the category of independent practice was
composed of individuals reporting a primary work setting of: sole practicing
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alone, sole practicing in a group, employee of a group, partner in a limited
liability partnership, and part of a limited liability corporation. Future
research should address if working in an academic setting contributed to the
choice to respond online versus an independent practice setting contributing
to responding via mail. However statistical tests ultimately determined that
group (online versus mail) category was unrelated to practice setting. It is
possible that a sample with a less restricted range in terms of practice setting
might reveal different results.
The online and mail groups were also very similar in terms of years at
current setting, theoretical orientation, size of communities where they
worked, and the socioeconomic status of the communities where they
worked. The only significant between group difference in terms of personal
and practice characteristics was that of income, with the mail group reporting
significantly higher income compared to the online group. Future research
needs to address this difference. However, as noted earlier in this chapter,
these results must be viewed cautiously due to the lack of clarification
related to reported compensation in terms of full versus part-time
employment and household versus clinical income.
Statistical analyses determined that with the exception of income, the
personal and practice characteristics listed above were independent of group.
Therefore these characteristics cannot be used as predictor variables for
response method group categorization, and our groups can be viewed as
equivalent. This is an important consideration for future IP-Net studies that
wish to continue to recruit and survey participants via the Internet as well as
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through the mail. This is also important in terms of our initial recruitment
sample being considered representative of the overall Division 42.
Generalizability of Sample. The absence of group differences could
possibly be related to a lower than expected response rate or to a restricted
range of variables in terms of age, race, degree, number of years licensed,
and practice setting. While the present study examined patterns among
those in independent practice, perhaps future studies should seek to include
a wider diversity of participants, which would likely increase the range of
variables.
However, given that our study sample was very similar to those in the
random sample, as well as the entire membership of Division 42, in terms of
gender (approximately 60% males and 40% females across all three groups),
age (approximately mid-fifties across all three groups), race (over 90%
Caucasian in all three groups), degree (over 80% hold a Ph.D. in all three
groups), years licensed (around 20 years for all three groups), practice
setting (on average 83% independent practice across the three groups) and
geographic distribution, it can be stated that our study sample is
representative of not only the random sample of Division 42 members
provided by the APA Research Office, but also the entire Division 42
membership. As stated previously, one goal of our study was to recruit a
volunteer sample of independent practitioners from Division 42 who would
provide data that would allow for generalizations of findings based upon the
representativeness of the sample. This was an important first step in
establishing the foundation of the IP-Net for future research studies, which
will attempt to increase the number of participants.
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Findings Related to Attitudes Toward Technology and Technology Use by
Independent Practitioners
Findings Related to Attitudes Toward Technology as a Function of
Response Group. A specific goal of this study was to examine results from
the Attitudes Toward Computers Questionnaire (Jay, 1989) with its seven
dimensions of (1) comfort, (2) efficacy, (3) gender equality, (4) control, (5)
dehumanization, (6) interest, (7) utility, and a total score, as it related to
group differences and technology use. As predicted, the online group
reported significantly more positive attitudes in all areas, with the exception
of gender equality, where there was no significant difference between the
online and mail groups. This indicated that neither the online nor mail group
endorsed sexist attitudes related to computers being more important for
males to understand and use. It is interesting to note that the ATCQ used
strong “anti-female” language (i.e., “Working with computers is more for men
than for women.”; “More men than women have the ability to become
computer scientists.”).
In addition to the between group differences related to attitude, those
with more positive attitudes toward technology reported significantly higher
levels of current technology use for scheduling, maintaining patient files,
performing outcome research, testing, using the Internet to obtain
information, using the Internet for therapy, using the Internet for
marketing/advertising, and using the Internet for job recruitment. Using the
Internet for obtaining continuing education credits and billing approached
significance.
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These findings are consistent with social psychology research that
states attitudes are likely to guide behavior (Regan & Fazzio, 1977). Amount
of direct computer experience has been found to be the most consistent
correlate of computer attitudes, with increased experience leading to more
positive attitudes (Jay, 1989). The research literature has also suggested that
user attitudes have important implications with respect to the acceptance
and use of technological innovations (Grudin & Markus, 1997). This is an
important consideration given that a literature review conducted in June,
2002 determined that this is the first study to specifically measure
psychologist’s attitudes toward technology, and then make comparisons to
reported technology use.
Findings Related to Technology Use as a Function of Response Group.
Another specific goal of this study was to determine factors related to levels
of adoption of technology in practice, as well as rates of adoption. Our
results detailing current and anticipated future use of the technology
applications were consistent with those reported in previous studies, with the
addition of Internet categories. As predicted, participants in the online group
reported higher rates of use compared to those in the mail group. The only
category with zero current or future endorsement across both groups was the
use of technology applications for intake interview procedures. Reasons for
the lack of current or future use in this specific category should be
investigated in subsequent studies addressing technology use in practice. It
may be that the initial intake appointment is considered too important in
terms of diagnosing and establishing rapport, and that introducing
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technology applications would sacrifice the ability to effectively establish a
therapeutic relationship and treatment plan.
Data were also collected on the average amount of time per week
participants spent using the telephone, e-mail, Internet, and video
applications for provision of clinical services, and if they were reimbursed for
these services. Previous research identified the telephone as “universally
accepted” in terms of its use in practice, and this was the category that
reported the highest rates of average weekly use in our study. The
remaining categories of e-mail, Internet, and video, reported very low rates in
comparison. Overall, the data collected yielded only one significant group
difference, with the online group reporting a greater amount of time spent
per week making telephone referrals. Future research should look to clarify if
this is significant in terms of how the two groups differ in their approaches to
practice issues. Overall, there were few differences between the two groups,
which may suggest that method of data collection, online or via the mail,
yields similar results. Future studies can continue to address this question.
Additional statistical analyses determined that various personal and
practice variables such as age, gender, degree, theoretical orientation,
geographic location, population size of city, number of years licensed, or
practice setting were not related to amount of technology use. Further
discussion of the various categories of technology and their reported use will
be presented in subsections below.
Findings Related to Use of Technology in Practice Administration. The
mail group reported handling billings tasks themselves more often when
compared to the online group. However, the online group reported that they
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handled the scheduling, accounts payable, phone, and word processing tasks
themselves more often when compared to the mail group. The fact that the
online group reported performing the majority of office tasks themselves
more often compared to the mail group, who reported more often that an
employee handled these tasks, could be due to several factors and needs to
be addressed by future research. For example, the online group may
perform more of the tasks themselves due to being more comfortable with
the technology applications involved or enjoying the work more (i.e. using the
computer to type documents or using the computer to run a scheduling
program). Therefore, the online group may not have the need to hire an
employee to serve in the type of clerical role. On the other hand, since the
mail group reported significantly higher income compared to the online
group, it may not be financially possible for the online group to hire an
employee to do these tasks or to contract them out. Again, future research
should clarify the issue related to income differences between groups, as well
as the differences in how these administrative tasks are performed.
In terms of current technology use in practice, billing and word
processing were the two tasks most frequently reported by participants, with
overall rates of 80% and 79%, respectively. This is consistent with other
studies reported in the literature (i.e., McMinn et al., 1999). Future research
needs to address if technology-based billing was done on a voluntary basis,
or as a result of reimbursement practices by third party payers.
Thirty-one percent of participants reported that they utilize technology
applications to maintain patient files. Future research needs to clarify to
what extent a computer is actually used to maintain patient files (i.e.,
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paperless files versus typed progress notes). Twenty-five percent of the
participants reported using technology applications for scheduling. Future
research should clarify if this rate of use is accounted for by calendar
programs on a desktop computer versus hand-held personal digital assistants
(PDAs) or some other type of software program. Finally, 10% of participants
reported that they utilized the Internet for marketing or advertising, and 1%
for recruiting job applicants. It will be interesting to note if these rates
increase as the Internet becomes a more popular method for reaching
potential consumers and employees. These two categories have not been
assessed by previous studies found in the literature.
Findings Related to Use of Technology for Assessment. Forty-six
percent of participants reported the use of technology applications for
assessment purposes. This rate is higher than that reported by McMinn et al.
(1999), but still lower than expected given the time efficiency offered by
computerized test programs. Future research needs to address whether this
is due to the fact that many practices are operating without performing
testing services, hand scoring, contracting out for scoring, or other factors,
such as the rates of reimbursement for psychological testing.
Findings Related to Use of Technology for Treatment. The use of the
Internet for therapy was reported by 7% of participants. However, the survey
instrument did not clarify exactly what was meant by Internet therapy (i.e.,
chat room discussions, accepting fees for services, live exchanges, or
questions submitted over an Website that were answered by a psychologist,
etc.). Future research needs to clarify these points to better understand how
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the application is being utilized by practitioners, as was done in the study by
Maheu and Gordon (2000).
Recording patient homework was reported at a frequency of 5%.
Future research needs to determine if what is being reported as technology
use to record patient homework is the simple word processing of patient
assignments, or if it is the interactive use of technology either through the
Internet or computer programs and e-mail to actively engage the patient and
therapist in monitoring behaviors.
Measuring patient satisfaction and performing outcome research had
overall low rates (25% and 11%, respectively). Of those performing outcome
research, 8% reported that they used technology applications as part of this
task. Perhaps in the future as practice research networks in psychology
grow, these rates will increase. This may also be an area where software
developers can look to build packages that combine tools for maintaining
files, schedules, patient accounts, treatment plans, homework assignments,
as well as patient satisfaction scales and outcome measures.
Once we can clarify the exact manner in which practitioners are
incorporating the various technology applications endorsed in this study, we
can then determine a more useful classification system of technology use in
practice than the system presented by McMinn (1999), which is discussed in
more detail later in this chapter. This is a benefit of a research method such
as IP-Net, which has easy access to a database of participants who can be
contacted in the future for follow-up studies.
In terms of reported weekly use of various technology applications, the
only significant between group difference was in terms of telephone referrals
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with the online group reporting a higher amount compared to the mail group.
Future research needs to address the reason for this difference. Perhaps
online participants follow a different screening method, and therefore have
more potential patients to refer out.
Future research also needs to clarify whether the amount of weekly
telephone therapy reported was done in response to a crisis situation, or if it
was scheduled in place of an office therapy appointment. And if it was
scheduled, was it due to geographic restrictions or patient disability, etc.
versus preferred by the therapist and patient?
Findings Related to Use of Technology for Communication and
Information. The third and fourth most frequently reported technology
applications were the use of the Internet to obtain information (64%) and e-
mail with other professionals (57%), which corresponds with the number of
“online” individuals in the US today. Even with the dramatic increase in the
number of individuals “online” in the US, it was still notable that 29% of
participants reported using e-mail with patients, especially given the
significantly lower rates reported in previous studies. By mid-2001, the
Telecommunications Report International (CyberAtlas Staff) reported that
there were 70.7 million online subscribers in the United States, up 16 million
from 2000. Future research needs to clarify exactly what is meant by e-
mailing patients (i.e., for the purpose of appointment times or containing
clinical content). For example, a local community mental health center puts
the e-mail addresses of its psychologists on their business cards, which are
handed out to patients at the end of each appointment because they list
future appointment dates on the back. This has been taken, whether
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mistakenly or otherwise, as an invitation by many patients to use the e-mail
address as a means of contact. Also, the present study did not clarify if e-
mail was used to discuss clinical or treatment content, or just to verify
appointment times and other administrative issues.
Discussion of Hypotheses Regarding Technology Use and Related
Attitudes. In terms of looking at number of years licensed, our original
hypothesis stated that the number of years licensed would be related to
attitudes toward technology, with newer practitioners having more positive
attitudes and reporting greater amounts of technology use. Analyses were
also performed to determine if age would have better predicted amount of
technology use and attitudes toward technology. Both hypotheses were
unsupported; the variables were found to be unrelated to attitudes toward
technology and amount of technology use. It may be that research studies
need to wait for a new cohort of individuals who were part of the “digital age”
to detect differences. Additionally, our sample was restricted in terms of age
range, with two-thirds between the ages of 47 and 60 years; and none below
age 40 in the online group.
In terms of looking at practice setting, it was hypothesized that those
not in independent practice would be greater users of technology
applications and have more positive attitudes. This was also unsupported,
but may be related to the fact that we had a very restricted range in terms of
practice setting, with 88% reporting independent practice. Future research
needs to address this question by looking at a sample with a greater diversity
of practice settings. Future research also needs to clarify the practical and
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economic constraints involved with a private practice, and how these would
affect the decision or desire to incorporate technology applications.
Our second hypothesis, which predicted that those with more positive
attitudes toward technology, as measured by the ATCQ (Jay, 1989), would
report using technology applications to a greater extent, was supported for
several areas of technology use. This corresponds with data from social
psychology studies related to attitudes being directly impacted by amount
and level of experience, as discussed earlier. Amount of direct computer
experience has been found to be the most consistent correlate of computer
attitudes, with increased experience leading to more positive attitudes (Jay,
1989). Future research should inquire about participant’s experience with
technology applications in order to determine the fit with Mackie and Wylie’s
model (1988), which states that attitudes are determined by: (1) the user’s
awareness of the technology and its purpose; (2) the extent to which the
features of the technology are consistent with the user’s needs; (3) the user’s
experience with the technology; and (4) the availability of support when
using the technology.
Trends in Technology Use and the Need for Reclassification. The
results obtained in our present study demonstrate higher rates of technology
usage than those reported by McMinn et al. (1999) who reported 57% use for
billing (versus 80% in this study), 23% use for testing (versus 46% in this
study), and 22% use for maintaining patient files (versus 31% in this study).
Results of this survey also showed a higher rate of reported use of the
Internet for therapy (7%), compared to the 2% use reported by VandenBos
and Williams (2000).
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As stated earlier, the wave classification system proposed by McMinn
(1999) does not appear to adequately and efficiently categorize available
technologies. At best, it is suggested that this system be reevaluated in
terms of what is listed in the first-wave classification to determine if this so
called first-wave should be eliminated entirely, since it is doubtful that any
modern office can exist without those particular technologies (Jerome,
DeLeon, James, Folen, Earles, & Gedney, 2000). This would reduce the three-
wave system to two waves by moving what is currently listed as second-wave
technologies to the first-wave, and third-wave technologies to second-wave.
However, this suggestion only attempts to clarify a system that we do not
believe to be parsimonious and comprehensive. Instead, we would propose a
system of classification based upon the presentation of our results in chapter
3, with the addition of a category for education and training purposes. Such
a classification system would appear as follows:
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I. Use of Technology in Practice AdministrationII. Use of Technology in for AssessmentIII. Use of Technology for TreatmentIV. Use of Technology for Communication and InformationV. Use of Technology for Education and Training
It is our belief that this five-tier system that labels the specific use of
the application and not merely the type of technology, would offer greater
parsimony and better account for the different modes of technology
utilization in practice. For example, with this system the use of e-mail could
potentially be listed under any and all of the five tiers, but its function would
be clearly defined, thus eliminating the confusion inherent in McMinn’s (1999)
proposed system as discussed earlier in this paper. Therefore, if e-mail was
used strictly to remind patients of an upcoming appointment, this could be
classified under the first tier, as use of technology in practice administration
similar to how a reminder telephone call might be labeled. However, if e-mail
were utilized to discuss clinical content with a patient, this would be classified
as use of technology in treatment. Therefore, we have a clear understanding
of the function of the technology application in treatment, rather than a mere
listing of the wave of technology based upon expected rates of use and
assumptions about its impact on therapy.
Conclusions and Future Directions
This study was undertaken for two purposes. The first was to examine
factors associated with technology adoption in clinical practice, since others
have argued that there are many technologies now available to enhance and
simplify the work of practicing psychologists (i.e., Marks, Shaw, & Parkin,
1998; McMinn et al., 1999), yet there has been little movement in the field to
incorporate these advances. This study measured current technology usage
93
and attitude toward usage among psychologists in independent practice.
Two of the hypotheses regarding factors associated with attitudes and
technology use were unsupported. Thus, the number of years in practice and
practice setting did not predict technology use. However, a third hypothesis
was supported in that attitudes toward technology did impact technology
use. As reported earlier, this is consistent with both social psychology
research on attitudes and behaviors in general, as well as with other studies
reported in the literature specific to attitudes and technology. Based upon a
literature review conducted in June, 2002, this is the first study to specifically
measure psychologist’s attitudes toward technology and compare with
reported technology use. It was also interesting to note that our sample
reported higher levels of technology use for e-mail and Internet therapy
compared to previous research found in the available literature. It is not
clear if this is simply related to the passage of two years since the last
reported survey found in the available literature and the continued
technology boom, or if it is true movement within the field to consciously
increase technology usage.
However, it may be that the increased usage found on the present
study may be more related to practical factors as discussed by Murphy
(2000). It may be that the areas with the greatest increase in use are those
that provide the greatest savings in cost and time, or are activities that
generate revenue. Furthermore, there would need to be incentives for
application developers. The argument presented by Murphy (2000) was that
ultimately, in order for technology applications to become more widely
adopted in psychotherapy practice, the technology must offer a clear benefit
94
over simpler and less expensive alternatives, as well as provide significant
economic benefit to users and developers. Additionally, it should be noted
that very few participants in our study reported that they anticipated an
increase in future use of technology applications in practice (based upon
responses of those not currently using a particular application, and
anticipating use of that application in the near future). It may be that areas
where those in clinical practice intend to use technology applications are
saturated, and therefore manufacturers of technology applications will have
to carefully aim at marketing new products that specifically match the needs
of those in clinical practice.
The second purpose of this study was to perform an initial recruitment,
as part of a larger project, and establish a research database of participants
for the IP-Net (Independent Practice Network). Therefore, it was hoped that
this project would not only look at technology issues, but also provide
demographic information on the composition of participants and establish the
degree of representativeness or generalizability for the sample to practicing
psychologists, as described by our descriptive statistics. This study was the
initial effort for IP-Net, and therefore also served to workout methodological
issues. The present study did in fact meet this second purpose.
In closing, I think that an important future direction for this line of
research will be to look at the question raised by Stamm and Perednia
(2000), as well as some other researchers, as to what we really know about
the meaning of technology in mental health. Again, we are reminded that
the best piece of computer equipment is only as good as its trained and
willing human user. Researchers and practitioners still do not fully
95
understand what aspects of treatment make therapy “work,” therefore how
can we successfully begin to incorporate aspects of technology. Thus far,
research in the area of telehealth typically addresses the technology aspects
of the care provided and not the psychosocial implications of the technology
driven care. Most likely this is in part due to recent rapid technological
growth paired with financial pressures on the healthcare industry to be more
cost-effective. Also, if research continues to support the argument that the
therapeutic relationship itself is the most important factor in terms of
treatment success (Stiles, Agnew-Davies, Hardy, Barkham, & Shapiro, 1998),
then technology may not have a place in actual treatment, but it can still find
a place in the management of an office, the Internet for information and
continuing education, as well as in graduate training.
Another important future direction will be the adoption of a more
precise system of classification supported by on-going research tracking
patterns and trends in practice, such as what can be done through IP-Net.
Future IP-Net studies can also incorporate what was learned from this initial
effort in terms of procedural issues, and clarify points still unanswered by the
present study, which is a real strength and benefit of a system such as IP-Net.
Reed, McLaughlin, and Milholand (2000) warn that if we continue to let
the technology market drive the development of applications, rather than
being developed in response to the needs of its users, we could end up with
costly technology systems that are useless to practitioners and patients.
Therefore, it is up to practitioners and patients to request what is needed,
and to evaluate, and advocate for new technologies in keeping with already
existing standards and ethics. If we as psychologists leave this task up to
96
technology companies, health care systems, or government agencies, we run
the risk of products and guidelines that we neither want nor need. Again, this
leads us to consider the more practical issues related to the widespread
adoption of technology applications in practice, such as that the technology
must offer a clear benefit over simpler and less expensive alternatives, as
well as help to generate income (Murphy, 2000).
These issues can be addressed through the continued development of
practice research networks and the collection of real time data, such as the
one that the present study helped to lay the foundation for, the Independent
Practice Network (IP-Net).
97
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Appendix A: Invitation Letter/Informed Consent
Dear Division 42 Member:
I am writing to ask you to assist Division 42 conduct research on independent practice by participating in the Division 42 Independent Practice Network (IP-Net). The simple fact is there is little systematic data available to psychologists about important dimensions of independent practice. We regularly provide data about ourselves and our practices to managed care organizations for credentialing and re-credentialing. We provide information even more frequently when we submit billing and utilization review material. The fact is that these organizations have much more information about individual practices than the psychologists themselves and a better grasp of important aspects of practice than is available to us. In addition, research into effectiveness of psychological services seldom focuses on experienced psychologists working in independent practice settings. We have developed IP-Net to conduct research on psychologists in independent practice.
Participants in IP-Net will provide information on: Practice organization and management Service delivery and payment systems Local practice and market conditions Career paths Services Attitudes about practice and public policy issues
With additional development the system will allow process and outcome research with experienced professionals in private practice settings.
As an initial participant you will be in the reference sample and may respond by Internet or by postage-paid mail. Later participants will respond only to IP-Net’s Website. All participants will be asked to respond to no more than eight surveys each year. Each survey will be designed to be completed in 15-minutes. Responses are confidential and all information identifying individual participants is kept in a separate database and the only interaction between databases is to identify non-respondents to a survey. Participants will receive feedback on the results of each survey.
The questionnaires can be completed through our Website or by mail method. Internet response is preferred but the mail option is offered to insure that all can participate. After the initial registration, Internet based participants will receive emails instructing them how to access the Website and respond to the survey. Reminders will be sent to those who do not respond. Mail based participants receive a packet with the survey
107
and a postage-paid envelope. There will be follow-up of those who do not respond in a two-week period. More detailed information is included below.
If you wish to participate, you can either
Complete the enclosed postage-paid cardor
Access the Division 42 Website (http://www.division42.org/) and click on the IP-Net button. This will take you to the IP-NET Website and follow the instructions.
Mailing the postcard or responding on the Website indicates your consent to participate in the surveys. You can withdraw your consent at any time by informing IP-Net at any of the contacts below.
The APA Practice Directorate is developing a similar program with a different focus. We have coordinated our efforts with their project and will continue to consult with Practice Directorate staff. We believe that that participation in one network does not preclude participating in the other.
In the next months the IP-Net will be recruiting volunteer participants for the research network. The data for volunteers will be examined separately from that of the random sample and you will serve a key role in insuring the representativeness of the volunteer sample.
I am confident that your participation in the Practice Research Network will provide important information about trends in private practice and will lay the foundation for a system that can investigate the effectiveness of services provided in independent practice. I hope you will lend us your voice.
Cordially,
Michael J. Murphy, Ph.D.Division Secretary and Chair,Emerging Patterns of Practice Committee
108
Appendix B: Questionnaire
109
110
111
112
113
114
115
116
117
118
119
120
121
122
Appendix C: Characteristics of the Random Sample and Division 42 Membership Provided by the APA Research Office on Variables Available from APA’s Database
VARIABLERandom Sample
Number PercentDivision 42
MembershipNumber Percent
Gender: Male Female
1,201799
60%40%
3,8462,320
62.0%38.0%
Race: Caucasian
Hispanic African American
Asian American Indian
1,8913317169
95.0%1.5%1.0%0.5%0.5%
5,67187694115
92.0%1.4%1.1%0.7%0.2%
Age: Mean
Median SD
Range
not available
52.76.7
30-70+
56.6not available
10.6not available
*Region: Middle Atlantic
South Atlantic Pacific
East North Central New England
West South Central
West North Central
Mountain East South
Central
456341338285175122111
9478
22.8%17.1%16.9%14.3%
8.8%6.1%5.6%4.7%3.9%
1,5511,086
935865504367286319203
25.2%17.6%15.2%14.0%
8.2%6.0%4.6%5.2%3.3%
Degree: Ph.D.
Psy.D. Ed.D
1,743140
98
87%7%5%
5,133387366
83.2%6.3%5.9%
Years Licensed: Mean
Median SD
Range
not available
19.96.6
3-25+
23.5not available
10.4not available
Employment Setting: Independent Practice
Academic Hospital
Clinic Other Human Service
School Government
Business
1,0786656262423215
83.0%5.0%4.0%2.0%2.0%2.0%2.0%
>1.0%
1,942160109
706751439
75.5%6.2%4.2%2.7%2.6%2.0%1.7%0.3%
* Middle Atlantic (New Jersey, New York, Pennsylvania); South Atlantic (Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia); Pacific (Alaska, California, Hawaii, Oregon, Washington); East North Central (Illinois, Indiana,
123
Michigan, Ohio, Wisconsin); New England (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont); West South Central (Arkansas, Louisiana, Oklahoma, Texas); West North Central (Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota); Mountain (Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, Wyoming); East South Central (Alabama, Kentucky, Mississippi, Tennessee)
124