Advance Nursing Research Mixed Method Research

Jester B Rafols RN Ma. Lenore G. Pasol RN DNMAt the end of my presentation, MAN students will be able to: Recognized the advantages of utilizing the mixed method type of researchOutlines the different application, strategies and obstacles in using multimethod research design Identify and be familiarized with different multimethod research design

Mixed Method Research

Before, nursing research is dominated with quantitative research.

1980s Qualitative nursing research starts to be evident.

Some people argue that qualitative and quantitative research are based on totally incompatible paradigms.Multimethod (or mixed-method) Research is the judicious blending of qualitative and quantitative data.

One argument for blending qualitative and quantitative data in a study is that they are complementary; they represent words and numbers, the two fundamental languages of human communication.

By integrating different methods and modes of analysis, the weaknesses of a single approach may be diminished or overcome.Quantitative has strong in generalizability, precision, and control over extraneous variable but, sometimes the validity of such research is called into question. By introducing tight controls, quantitative studies may fail to capture situational context. By reducing complex human experiences, behavior, and characteristics to numbers, such studies sometimes seem superficial.

The use of tightly structured methods can sometimes lead to biases in capturing constructs under study. All these weaknesses are aspects of the studys ability to yield valid, meaningful answers to research questions. Qualitative research has strengths and weaknesses that are opposite.

The strength of qualitative research lies in its flexibility and its potential to yield insights into the true nature of complex phenomena through in-depth scrutiny.

However, qualitative research is almost always based on small, unrepresentative samples.

It is often undertaken by a single researcher or small research team, using data collection and analytic procedures that rely on subjective judgments. Thus, qualitative research is sometimes criticized for problems with reliability and generalizability.Neither of the two styles of research can fully deliver on its promise to establish the truth about phenomena of interest to nurse researchers. However, the strengths and weaknesses of quantitative and qualitative data are complementary.

Combined shrewdly in a single study, qualitative and quantitative data can supply each others lack. By using multiple methods, researchers can allow each method to do what it does best, with the possibility of avoiding the limitations of a single approach. Why Use Multi Method?

Enhanced Theoretical Insights

Qualitative and quantitative research constitute alternative ways of viewing and interpreting the world.

These alternatives are not necessarily correct or incorrect; rather, they reflect and reveal different aspects of reality.

Denzin (1989)coined the term triangulation to refer to the use of multiple sources to converge on the truth. He expressed the value of triangulation eloquently.

Incrementality

Qualitative methods are well suited to exploratory or hypothesis-generating research early in the development of a problem area. Quantitative methods are needed as the problem area matures for the purposes of verification.

However, the evolution of a theory or problem area is rarely linear and unidirectional.

The need for exploration and in-depth insights is rarely confined to the beginning of an area of research inquiry, and subjective insights may need to be evaluated early and continually.Progress in developing a body of evidence for nursing practice tends to be incremental and to rely on multiple feedback loops.

It can be productive to build a loop into the design of a single study, potentially speeding the progress toward understanding.

Bargagliotti and Trygstad (1987) conducted two separate studies of job stress among nurses, on nursing quantitative procedures and the other using qualitative procedures.

The quantitative study identified discrete events as sources of stress, and the qualitative study revealed stress-related processes over time.

The discrepant findings, because they were derived from different samples of nurses working in different settings, could not be easily integrated and reconciled.

The investigators noted, Comparison of findings from the two studies suggests that the questions raised by the findings in each study might have been more fully addressed by using a combined quantitative/qualitative methodology

Enhanced Validity

When researchers hypotheses or models are supported by multiple and complementary types of data, they can be more confident about the validity of the results. Brewer and Hunter (1989), Although each type of method is relatively stronger than the others in certain respects, none of the methods is so perfect even in its area of greatest strength that it cannot benefit from corroboration by other methods findings.The integration of qualitative and quantitative data can provide better opportunities for testing alternative interpretations of the data, for examining the extent to which the context helped to shape the results, and for arriving at convergence in tapping a construct.For example, Ersek, Ferrell, Dow, and Melancon (1997), in their study of quality of life in women with ovarian cancer, used qualitative data to validate their quantitative quality-of-life measures.

Creating New Frontiers

This lack of congruity can lead to insights that can push a line of inquiry further that would otherwise have been possible.When separate investigations yield inconsistent results, the differences are difficult to reconcile and interpret By probing into the reasons for any observed incongruities, researchers can help to rethink the constructs under investigation and possibly to redirect the research process.

The incongruent findings, in other words, can be used as a springboard for exploring reasons for discrepancies and for a thoughtful analysis of the studys methodologic and theoretical underpinnings.

APPLICATIONS OF MULTIMETHOD RESEARCH

Instrument Development

Qualitative data are sometimes collected for the development and validation of formal, quantitative instruments for research or clinical purposes.

When researchers become aware of the need for a new measuring tool, they sometimes derive the questions for a formal instrument from clinical experience, theory, or prior research. When a construct is new, however, these mechanisms may be inadequate to capture its full complexity and dimensionality. Thus, many nurse researchers have begun to use data obtained from qualitative inquiries as the basis for generating questions for quantitative instruments that are subsequently subjected to rigorous quantitative assessment.

Example of qualitative inquiry on a quantitative instrument:

Barroso and Sandelowski (2001) recorded qualitatively the problems experienced in administering the widely-used Beck Depression Inventory (BDI) to a sample of human immunodeficiency virusinfected patients. The researchers concluded that their experiences with the BDI show the importance of incorporating qualitative techniques of interviewing and observation in all phases of the process of instrument utilization

Explicating and Validating Constructs

Multimethod research is often used to develop a comprehensive understanding of a construct, or to validate the constructs dimensions.

Such research may be undertaken when a little-researched phenomenon has been identified as worthy of further scrutiny (usually in an in-depth qualitative study), or when there is a body of existing research in which some serious gaps have been identified or doubts have been raised about the prevailing conceptualization.

Example of validating constructs:

Reece and Harkless (1996) conducted a multimethod study to examine the maternal experiences of women older than 35 years. The researchers administered an existing quantitative measure of maternal experience, the revised What Being the Parent of a Baby is Like (WPL-R) scale, which involves three subscales: Self-Evaluation in Parenting, Centrality, and Life Change. The researchers also asked respondents broad, probing questions about their motherhood experience and qualitatively analyzed the themes that emerged. The investigators found that several new dimensions arose in the qualitative portion of the research, including loss of control, fatigue and the need to heal, and the sense of mortality and the passage of time.

Hypothesis GenerationIn-depth qualitative studies are often fertile with insights about constructs or relationships among them. These insights then can be tested and confirmed in quantitative studies, and the generalizability of the insights can be assessed. This most often happens in the context of discrete investigations. One problem, however, is that it usually takes years to do a study and publish the results, which means that considerable time may elapse between the qualitative insights and the formal quantitative testing of hypotheses based on those insights. A research team interested in a phenomenon might wish to collaborate in a research program that has hypothesis generation and testing as an explicit goal.

Example of hypothesis generation:

Wendler (2001) described how the use of a meta-matrix can be used to facilitate pattern recognition across data from different sources, including qualitative and quantitative sources, and to generate hypotheses and new research questions. In Wendlers example of a mixed-method study of Tellington touch (t-touch), use of a meta-matrix led to a discovery of the relationship between the administration of t-touch and the practitioners physical state (e.g., caffeine intake).

Illustration, Clarification, and AmplificationQualitative data are sometimes combined with quantitative data to illustrate the meaning of constructs or relationships.

Such illustrations often help to clarify important results or to corroborate the understandings gleaned from the statistical analysis.

In this sense, these illustrations often help to illuminate the analyses and give guidance to the interpretation of results.Qualitative materials can be used to illustrate specific statistical findings or can also be used to provide more global and dynamic views of the phenomena under study, often in the form of illustrative case studies.

Understanding Relationships and Causal Processes

Quantitative methods often demonstrate that variables are systematically related to one another, but they often fail to provide insights about why variables are related. This situation is especially likely to occur with correlational research.The discussion section of research reports typically is devoted to an interpretation of the findings. In quantitative studies, interpretations are often speculative, representing researchers best guess (a guess that may, of course, be built on solid theory or prior research) about what the findings mean. In essence, the interpretations represent a new set of hypotheses that could be tested in another study.When a study integrates both qualitative and quantitative data, however, researchers may be in a much stronger position to derive meaning immediately from the statistical findings through the analysis of qualitative material.

Theory Building, Testing, and Refinement

The most ambitious application of multimethod research is in the area of theory development.

The use of multiple methods provides greater opportunity for potential disconfirmation of the theory.

If the theory can survive these assaults, it can provide a substantially stronger context for the organization of our clinical and intellectual work. Brewer and Hunter (1989), in their discussion of the role of multimethod research in theory development, made the following observation:Theory building and theory testing clearly require variety. In building theories, the more varied the empirical generalizations to be explained, the easier it will be to discriminate between the many possible theories that might explain any one of the generalizations. And in testing theories, the more varied the predictions, the more sharply the ensuing research will discriminate among competing theoriesMULTIMETHOD RESEARCH DESIGNS

Green and Caracelli (1997) have identified several types of research designs that involve a multimethod approach. The designs cluster into two broad categories that they label component designs and integrated designs.Multimethod Component DesignsComponent design- the qualitative and quantitative aspects are implemented as discrete components of the overall inquiry, and remain distinct during data collection and analysis. Combining the qualitative and quantitative components occurs during the interpretation and reporting phases of the project.Complementarity designs, the results from one method type are enhanced or clarified by results from the other type. Polit and her colleagues (2000) used a complementarity design in their previously described study of food insecurity. Triangulated design, both qualitative and quantitative methods are used to capture the same phenomenon, with a focus on convergence and increased validity. This design fits the application described in the previous section as explicating and validating constructs. Expansion design, in which different methods are used for distinct inquiry componentsas might be the case in an evaluation that involved both a process and impact analysis. The results from such studies are often presented in a side-by-side fashion, rather than woven together into a single story.

2. Multimethod Integrated Designs

Integrated design, there is greater integration of the method types at all phases of the project, from the development of research questions, through data collection and analysis, to the interpretation of the results. The blending of data occurs in ways that integrate the elements from the different paradigms and offers the possibility of yielding more insightful understandings of the phenomenon under study.

Four Types of Integrated Designs Iterative designs involve a dynamic in which the findings from one method are used as a basis for moving forward with further research using the alternative method (as is typically the case with instrument development and refinement). Embedded designs (or nested designs), one methodologic approach is embedded in the other, interlocking contrasting inquiry characteristics in a framework of creative tensionHolistic designs feature the essential interdependence of alternative methods for gaining a full understanding of complex phenomena. In holistic designs, the methods are integrated simultaneously rather than hierarchically.Transformative designs, the emphasis is on blending the value commitments of different research traditions to arrive at a better representation of the multiple interests in the larger social context.In general, integrated designs are better suited to theory building and testing than are component designs.

Timing and Design

Sandelowski (2000) has offered an alternative typology of multimethod designs. Her scheme focuses on which approach (qualitative or quantitative) has priority, and how the approaches are ordered in a study.

She developed a useful matrix that indicates the kinds of objectives that can be addressed with alternative design configurations. For example, in her Template Design #1, the qualitative approach is the dominant one and quantitative data are viewed as an adjunct. The quantitative data, which are collected concurrently with or after the qualitative data, are used to provide measured description, validation, and formal generalizations.

Template Design #4, by contrast, involves qualitative data occurring before (and as an adjunct to) the quantitative portion of the study. Such a design is used when the aim is to generate questions for a quantitative instrument, or to generate hypotheses to be tested formally.Sandelowskis scheme makes clear that most multimethod studies involve decisions about how to order data collection. In some cases (especially in component studies), data collection for the two approaches occurs more or less simultaneously.

In others, however, there are important advantages to timing the approaches so that the second phase builds on knowledge gained in the first.TIP: Many multimethod studies are conducted in two or more phases, such as conducting in-depth interviews with a subsample of patients from whom biophysiologic data were obtained after analysis of those data has been done. If there is a possibility that you might go back to study participants to obtain more data, be sure to structure your consent form in such a way that they are aware of any potential future demands on their time. Also, be sure to obtain contact information to facilitate finding them at a later date.STRATEGIES FOR MULTIMETHOD RESEARCH

The ways in which researchers might choose to combine qualitative and quantitative methods in a single study are almost limitlessor rather, are limited only by the researchers ingenuity, and by their views about the value of multimethod research. Researchers who do primarily quantitative research tend to be more likely to see the value of incorporating qualitative approaches into their designs than vice versa.

Phenomenological researchers, in particular, seldom build a quantitative component into their studies. Indeed, a number of qualitative researchers argue that true integration is not even possible.Mass (2000), for example, believes that the quest for meaning and the quest for measurement are incommensurable Nevertheless, examples of multimethod research abound. Although it is not possible to develop a catalog of multimethod strategies,

Clinical TrialsAlthough phase III clinical trials almost always use an experimental design with structured quantitative outcome measures, qualitative inquiries embedded in the trials can prove valuable in all phases. For example, in phase I, when the intervention is being fine-tuned, in-depth discussions with clinical staff and with patients can provide critical insights into how to develop the best possible intervention.

Sandelowski (1996) has argued that qualitative methods used as a component of quantitative research can increase the meaningfulness of experimental studies by placing them more firmly in the real world (Sandelowski, 1996). Even in a formal phase III evaluation of a clinical trial, many questions can be addressed qualitatively. Why did some patients drop out of the study? How did staff and patients feel about the intervention? Why didnt certain patients improve as a result of the intervention? What contextual factors constrained (or enabled) the interventions success?

Example of a multimethod clinical trial:

Whittemore, Rankin, Callhan, Leder, and Carroll (2000) were involved in a clinical trial of alternative social support interventions, administered by nurse versus peer advisors, for patients who have had a myocardial infarction. Subjects, who were randomly assigned to three groups (nurse advisors, peer advisors, or control group), were compared in terms of health outcomes. The qualitative part of the study, which was designed to understand better the experiences of the peer advisors, was based on written logs and individual and group interviews.Evaluation Research

Evaluation research often involves both quantitative components (e.g., impact analyses and cost analyses) and qualitative components (e.g., process analyses). In some cases, the components are stand-alone features of the study and are not linked in a systematic fashion. However, the most powerful and useful evaluations do use data from one component to inform findings in other components.Qualitative data collection methods are especially useful when the researcher is evaluating complex interventions. When a new treatment is straightforward (e.g., a new drug), it is usually easy to interpret the results: post-treatment group differences usually can be attributed to the intervention.However, many nursing interventions are not so straightforward. They may involve new ways of interacting with patients or new approaches to organizing the delivery of care. Sometimes, the intervention is multidimensional, involving several distinct features. At the end of the evaluation, even when hypothesized results are obtained, people may ask, What was it that really caused the group differences? (If there were no group differences, then the important question would be, Why was the intervention unsuccessful?) In-depth qualitative interviews with subjects could help to address these questions. In other words, qualitative data may help researchers to address the black box question understanding what it is about the complex intervention that drove observed effects.

Example of a multimethod evaluation:

Hecker (2000) collected both qualitative and quantitative data in an evaluation of a communitywide health fair held in a suburb of Mexico City. A collaborative research team gathered qualitative information about the planning and implementation of the health fair, and quantitative data about the outcomes of the fair. The researchers used both types of data to develop recommendations for program replication and modification.

SurveysThe most common data collection method currently used by nurse researchers is structured self-reports,

The qualitative portion might involve such approaches as in-depth individual or group interviews or unstructured observations in a naturalistic environment such as a hospital or nursing home. From a practical point of view,

it is efficient to collect both types of data simultaneously. For example, researchers could administer a structured questionnaire and then conduct an in-depth interview on the same day to a subsample of survey respondents. In some studies, this procedure is likely to work well, but a two-stage (iterative) approach has two distinct advantages. First, if the second-stage data collection can be postponed until after the quantitative data have been collected and analyzed, researchers will have greater opportunity to probe deeply into reason for any obtained results. A second reason for using an iterative approach is that researchers can use information from the first stage to select a useful subsample for the second.

Example of a qualitative study after a survey:

Wilson and Williams (2000) were involved in a three-phase study on telephone consultation among community nurses in England. The first phase involved a national survey of community nurses by mailed questionnaire. In the second phase, which involved in-depth interviews with a subset of 14 survey respondents, nurses were probed about their experiences with telephone consultations. The third phase involved a survey of clients from the interviewees caseload who had used telephone services.

EthnographiesThe methods used in ethnographic field studies usually yield a rich array of data amenable to qualitative analysis, such as notes from qualitative observations, indepth interviews, and narrative documents such as diaries and letters.

Ethnographers can, in some cases, profit from the collection of more structured information from a larger or more representative sample than is possible in collecting the qualitative data. The secondary data might be in the form of structured self-reports from a survey, or quantifiable records. As field work progresses, ethnographers typically gain considerable insight into the cultures under study.

Alternatively, the quantitative portion of the study could be used to gather descriptive information about the characteristics of the community or organization so that qualitative findings could be understood in a broader context. In either case, having already gained entre into the community and the trust and cooperation of its members, ethnographers may be in an ideal position to pursue a survey or record-extraction activity.

Example of a multimethod ethnography:

Clark (2002) conducted a focused ethnography of Mexican-origin mothers experiences of obtaining and using health services for their children in an urban Latino community in the United States. In addition to gathering in-depth ethnographic data through multiple interviews and participant observation, Clark gathered and analyzed quantitative information from the childrens medical records (e.g., number of emergency department visits, number of well-child visits).

OBSTACLES TO MULTIMETHOD RESEARCH

Epistemologic biasesCosts. Researcher training. Analytic challenges. Publication biases. References:

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