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What are mixed methods?
Mixed methods research integrates bothquantitative and qualitative research methodswithin a single study or across multiple related studies.
Mixed methods research is particularly useful when a research question requires a multifaceted approach that can simultaneously explore trends in data and the nuances of individual experiences.
Integration, a key concept in mixed methods research, is the intentional combining of quantitative and qualitative research in such a way that they become interdependent and work together to achieve a common research goal.
For example, examining changes in school funding (quantitative) alongside teacher and student narratives (qualitative) about educational quality in a school district can provide a more comprehensive understanding of the relationship between funding and the actual experiences of those within the school system.
Several factors make mixed methods research distinct from conducting separate quantitative and qualitative studies. A few of these defining factors are:
Examples
Here are some examples of how people use mixed methods research in real life:
Mixed methods research is a powerful tool that can be used to answer complex research questions in a way that neither quantitative nor qualitative research can do alone:
When to use mixed methods research
Researchers should clearly articulate their reasons for using a mixed methods research design. This rationale helps reviewers and other researchers understand why this design is the most appropriate for addressing the research questions.
Mixed methods research designs
Mixed methods research designs provide researchers with a structured approach to combining qualitative and qualitative data. Creswell and Plano Clark (2018) identify three core mixed methods designs:
Convergent Parallel Design
Convergent parallel design involves simultaneously collecting quantitative and qualitative data, analyzing these datasets separately, and then merging the results for interpretation.
Explanatory Sequential Design
An explanatory sequential design is used in research when you want to use one type of data to help explain the findings of another type.
For example, this design can be used to learn more about why students stayed enrolled in online education programs. The researchers could first look at survey data and then followed up with interviews to get a deeper understanding of the factors involved.
Exploratory Sequential Design
An exploratory sequential design is a type of research that involves two phases of data collection and analysis, with the qualitative phase coming first.
The exploratory sequential design is most effective when researchers have a clear rationale for using a mixed methods approach and when the research questions lend themselves to both qualitative and quantitative exploration.
Researchers were interested in understanding the factors that influence brain donation decisions among older minorities.
The themes and insights from these interviews were then used to develop a survey instrument to measure the factors identified as potentially influencing donation decisions.
Embedded (or nested) Design
Embedded or Nested Designs in Health Sciences
Embedded designs use quantitative and qualitative approaches together, with one embedded in the other, to yield greater insight. This might look like supplemental qualitative data embedded in a larger quantitative study design, such as an experimental trial. These types of designs may be a variation of convergent or sequential designs.
Embedded design is a method for linking qualitative and quantitative data collection and analysis at multiple points, particularly useful in intervention research.
Integration
Integration is the intentional combination of quantitative and qualitative research, resulting in a synergistic and interdependent relationship between the two approaches. It is a multifaceted concept that manifests across various stages of the research process, from design to reporting.
Integration Trilogy: Design, Methods, and Interpretation & Reporting
Integration in mixed methods research operates at three distinct but interconnected levels, often referred to as the integration trilogy:
Narrative Integration
Integrating through narrativein mixed methods research involves describing qualitative and quantitative findings within a single report or a series of reports. The manner in which these findings are presented can take on three distinct approaches: weaving, contiguous, or staged.
Data Transformation
Mixed methods analysis encompasses the entire process of analyzing and interpreting both quantitative and qualitative data within a single study or a program of research.
This involves selecting appropriate analytic techniques for each strand and implementing integration strategies to merge, connect, or build upon the findings.
Mixed methods data transformationinvolves converting data from one form to another. This can involve:
Data transformation facilitates merging data and conducting analyses that cut across the quantitative-qualitative divide.
By adhering to these principles and employing these strategies, researchers can leverage the strengths of mixed methods research to address complex research questions and generate rich, insightful, and impactful findings.
Joint Displays: Visual Aid for Integration
Joint displays are visual representations, such as tables, matrices, figures, or graphs, that bring together quantitative and qualitative data to facilitate interpretation and draw new insights beyond what each strand could achieve independently.
They are particularly helpful in merging data, comparing results, and representing meta-inferences, the novel insights that emerge from integrating the two strands.
Assessment of Fit and Integrated Interpretation
Assessment of fit of integration involves evaluating the coherence and consistency between the quantitative and qualitative findings. This assessment can reveal three potential outcomes:
Integrated interpretation involves synthesizing the quantitative and qualitative findings to develop a holistic understanding of the research problem, acknowledging both points of convergence and divergence.
This process requires integrated thinking, a mindset that values both approaches equally and seeks a synergistic understanding that transcends the limitations of either method in isolation.
Steps for conducting mixed methods research
Remember that mixed methods research is an iterative process. Researchers should remain flexible and adaptable throughout the study, adjusting plans as needed based on emerging findings or unexpected challenges.
The dynamic interplay between quantitative and qualitative approaches is a hallmark of mixed methods research, and embracing this fluidity contributes to the richness and depth of the findings.
Step1:Formulating the Research Problem
Step 2:Designing the Study
Step3:Implementing the Study
Step 4:Integrating and Interpreting Findings
The quality of a mixed methods study hinges on several factors:
Mixed methods publications often employ a weaving approach, integrating findings throughout the manuscript, or a contiguous approach, presenting quantitative and qualitative results in separate sections but linking them through cross-referencing and discussion.
A staged approach involves publishing multiple papers, each focusing on a specific aspect of the mixed methods study.
Benefits of mixed methods research
Disadvantages of mixed methods research
References
Bazeley, P. (2018). Integrating analyses in mixed methods esearch. SAGE.
Brown, K. M., Elliott, S. J., Leatherdale, S. T., & Robertson-Wilson, J. (2015).Searching for rigour in the reporting of mixed methods population health research: a methodological review.Health Education Research,30(6), 811-839.
Caracelli, V. J., & Greene, J. C. (1997). Crafting mixed-method evaluation designs.New directions for evaluation,74, 19-32.
Collins, K. M., Onwuegbuzie, A. J., & Sutton, I. L. (2006).A model incorporating the rationale and purpose for conducting mixed-methods research in special education and beyond.Learning disabilities: a contemporary journal,4(1), 67-100.
Creamer, E. G. (2018).Striving for methodological integrity in mixed methods research: The difference between mixed methods and mixed‐up methods.Journal of Engineering Education,107(4), 526-530.
Creswell, J. W., & Plano Clark, V. L. (2018).Designing and conducting mixed methods research(3rd ed.). SAGE.
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Bacchus, L. J., Buller, A. M., Ferrari, G., Brzank, P., & Feder, G. (2018). “It’s always good to ask”:A mixed methods study on the perceived role of sexual health practitioners asking gay and bisexual men about experiences of domestic violence and abuse. Journal of Mixed Methods Research, 12(2), 221–243.
Campbell, R., Fehler-Cabral, G., Bybee, D., & Shaw, J. (2017).Forgotten evidence: A mixed methods study of why sexual assault kits (SAKs) are not submitted for DNA forensic testing.Law and human behavior,41(5), 454.
Clark, R. S., & Plano Clark, V. L. (2019).Grit within the context of career success: A mixed methods study.International Journal of Applied Positive Psychology,4(3), 91-111.
Clark, R. S., & Stubbeman, B. L. (2021). “I had hope. I loved this city once.”: A mixed methods study of hope within the context of poverty.Journal of Community Psychology,49(5), 1044-1062.
O’Keeffe, S., Martin, P., Target, M., & Midgley, N. (2019). ‘I just stopped going’:A mixed methods investigation into types of therapy dropout in adolescents with depression.Frontiers in psychology,10, 423542.
Roques, M., Laimou, D., Camps, F. D., Mazoyer, A. V., & El Husseini, M. (2020).Using a mixed-methods approach to analyze traumatic experiences and factors of vulnerability among adolescent victims of bullying.Frontiers in psychiatry,10, 890.
Roysircar, G., Thompson, A., & Geisinger, K. F. (2019). Trauma coping of mothers and children among poor people in Haiti: Mixed methods study of community-level research.American Psychologist,74(9), 1189.
Journals
Olivia Guy-Evans, MSc
BSc (Hons) Psychology, MSc Psychology of Education
Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.
Saul McLeod, PhD
BSc (Hons) Psychology, MRes, PhD, University of Manchester
Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.
