The term mixed methods refers to an emerging research methodology that promotes the systematic integration, or mixing, of quantitative and qualitative data within a single research or sustained program of inquiry. The basic premise of this methodology is that such integration allows for a more complete and synergistic use of data than the collection and analysis of quantitative and qualitative data separately.
Mixed-method research originated in the social sciences and has recently expanded into the medical and health sciences. It includes fields such as nursing, family medicine, social work, mental health, pharmacy and allied health, among others. Over the past decade, its procedures have been developed and refined to suit a wide variety of research questions (Creswell and Plano Clark, 2011).
These procedures include advancing rigor, offering alternative mixed-method designs, specifying a shorthand notation system to describe designs in order to increase communication between fields. It includes visualizing procedures through diagrams, observing research questions that may especially benefit from integration, and developing justifications for conducting various forms of mixed-method studies.
Characteristics of Mixed Methods
The main features of a well-designed mixed-method study in research are as follows:
- Collect and analyze quantitative (closed) and qualitative (open) data.
- Use rigorous procedures in the collection and analysis of data appropriate to the tradition of each method, such as ensuring adequate sample size for quantitative and qualitative analysis.
- Integrate the data during the collection, analysis or discussion of the same.
- Use procedures that apply qualitative and quantitative components simultaneously or sequentially, with the same sample or with different samples.
- Frame the procedures within philosophical/theoretical models of research, such as within a social constructionist model that seeks to understand multiple perspectives on the same topic, for example, what patients, caregivers, clinicians and consultation staff would characterize as "high quality treatment".
Uses of Mixed Methods Research Designs
Mixed methods can be an ideal technique for evaluating complex interventions (Homer, Klatka, Romm, et al., 2008; Nutting, Miller, Crabtree, et al., 2009). Evaluators can choose from five primary mixed-method designs based on the research questions they want to answer and the resources available for evaluation.
Validate results using quantitative and qualitative data sources
Evaluators can use a convergent design to compare the results of qualitative and quantitative data sources. This involves:
- The collection of both types of data at approximately the same time.
- Evaluating information using parallel constructs for both types of data
- Separate analysis of both types of data; and comparing results using procedures such as side-by-side comparison in a debate, transforming the qualitative data set into quantitative scores.
- The joint presentation of both forms of data.
For example, the researcher may collect qualitative data to assess patients' personal experiences. At the same time, collect data from survey instruments that measure the quality of care. The two types of data can validate each other and also create a solid basis for drawing conclusions about the intervention.
Use qualitative data to explore quantitative results
This explanatory sequential design usually includes two phases:
(1) an initial phase of the quantitative instrument, followed by
(2) a phase of qualitative data collection, in which the qualitative phase is directly based on the results of the quantitative phase.
In this way, the quantitative results are explained in more detail through the qualitative data. For example, the conclusions of the cost instrument data can be further explored with qualitative focus groups to better understand how individuals' personal experiences coincide with the results of the instruments. This type of study illustrates the use of mixed methods to qualitatively explain how quantitative mechanisms can work.
Develop survey tools
Another mixed-method study design could support the development of appropriate quantitative instruments that provide accurate measurements. This exploratory sequential design involves, in the first place, the collection of qualitative exploratory data, the analysis of the information and the use of the results to develop a psychometric instrument well adapted to the sample under study.
This instrument is then administered to a sample of the population. For example, a study on PCMH could begin with a qualitative exploration through interviews with primary care providers to assess which constructs should be measured to better understand improved quality of care. From this exploration, an instrument could be developed using rigorous scale development procedures that are then tested with a sample. In this way, researchers can use a mixed-method approach to develop and test a psychometric instrument that enhances existing measures.
Use qualitative data to augment a quantitative outcome study
A results study, such as a randomized, controlled trial, to which qualitative data collection and analysis is added, is called an integrated design. In this type of outcome study, the researcher collects and analyzes quantitative and qualitative data. Qualitative data can be incorporated into the study at first (for example, to help design the intervention); during the intervention and after the intervention (for example, to help explain the results). In this way, qualitative data increase the study of results, which is a popular approach within implementation and dissemination research (Palinkas, Aarons, Horwitz, et al., 2011).
Engaging community stakeholders
A participatory community-based approach is an example of multiphase design. This advanced mixed-method approach involves community participants in many quantitative and qualitative phases of research to bring about change (Mertens, 2009). All multiple phases address a common objective of model evaluation and refinement. Key stakeholders participate as co-researchers in a project, providing feedback on their needs, ways to address them and ways to implement the changes.
Using a mixed-method study has several advantages, which we discuss below.
Compares quantitative and qualitative data
Mixed methods are particularly useful for understanding the contradictions between quantitative and qualitative results.
Reflects the point of view of the participants
Mixed methods give voice to study participants and ensure that study conclusions are based on participants' experiences.
Fosters academic interaction
This type of study expands the research of multidisciplinary teams by encouraging the interaction of specialists in quantitative, qualitative and mixed methods.
Provides methodological flexibility
Mixed methods have great flexibility and are adapted to many study designs, such as observational studies and randomised trials, to elucidate more information than can be obtained in quantitative-only research.
Collects rich and complete data
Mixed methods also reflect the way individuals collect information naturally, integrating quantitative and qualitative data. For example, sports stories often integrate quantitative data (scores or number of errors) with qualitative data (descriptions and images of highlights) to provide a more complete story than either method would offer separately.
Mixed-method studies are difficult to implement, especially when used to evaluate complex interventions. Several challenges are discussed below.
Increases the complexity of assessments
Mixed-method studies are complex to plan and conduct and require careful planning to describe all aspects of the research, including the study sample for the qualitative and quantitative parts (identical, integrated, or parallel), the timing (the sequence of the qualitative and quantitative parts), and the plan for integrating the data. Integrating qualitative and quantitative data during analysis is often a difficult phase for many researchers.
It depends on a multidisciplinary team of researchers
Conducting high-quality mixed-method studies requires a multidisciplinary team of researchers who, in the service of the larger study, should be open to methods that may not be their area of expertise. Finding qualitative experts who are also comfortable discussing quantitative analyses and vice versa can be a challenge in many settings. Since each method must adhere to its own standards of rigor, ensuring the proper quality of each component of a mixed-method study can be difficult.
For example, quantitative analyses require much larger sample sizes for statistical significance than qualitative analyses, which require meeting the objectives of saturation (not discovering new information by conducting more interviews) and relevance. Embedded samples, in which a qualitative subsample is embedded within a larger quantitative sample, can be useful in cases of inadequate statistical power.
Requires more resources
Finally, mixed-method studies are labor-intensive and require greater resources and time than are required to conduct a single-method study.
The integration of quantitative and qualitative data in the form of a mixed-method study has great potential to reinforce the rigour and enrich the analysis and conclusions of any evaluation. By carefully selecting the mixed-method design that best suits the assessment questions and meets your resource limitations, evaluators can facilitate deeper and more meaningful learning regarding the effectiveness and implementation of the models.
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Creswell JW, Plano Clark VL. Designing and conducting mixed methods research. 2nd ed. ThousandOaks, CA: Sage; 2011.
Homer CJ, Klatka K, Romm D, et al. A review of the evidence for the medical home for children with special health care needs. Pediatrics 2008;122:e922–e937.
Mertens DM. Transformative research and evaluation. New York: Guilford; 2009.
Nutting PA, Miller WL, Crabtree BF, et al. Initial lessons from the first national demonstration project on practice transformation to a patient-centered medical home. Ann Fam Med 2009;7(3):254–60.
Palinkas LA, Aarons GA, Horwitz S, et al. Mixed methods designs in implementation research. Adm Policy Ment Health 2011;38(1):44–53.
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