Mixed Methods Research Examples

In this article, we will showcase different mixed-methods research studies that have applied different designs as well as key articles in mixed-methods research.

Introduction

Mixed methods research integrates quantitative and qualitative data to provide a more complete understanding of a research problem. This approach acknowledges that numerical data and descriptive insights contribute valuable perspectives. By combining quantitative data collection with qualitative analysis, researchers can explore patterns while capturing the experiences, behaviors, and motivations behind them.

Different mixed methods research designs allow researchers to structure their studies based on their objectives and the nature of their research questions. Some studies prioritize quantitative research methods, using qualitative insights to explain statistical trends, while others emphasize qualitative exploration, supported by quantitative findings for validation. Regardless of the design, mixed methods research provides a balanced approach that enhances the depth and credibility of study results.

This article showcases real-world mixed methods studies that illustrate different research designs, providing practical examples of how mixed methods research can be structured. By exploring these cases, researchers can gain insights into various approaches and strategies for integrating qualitative and quantitative data. Additionally, the studies presented in this article can be worthwhile resources for researchers to read if they wish to explore any example in more detail.

Convergent parallel design example

Convergent parallel design involves collecting quantitative and qualitative data simultaneously and analyzing them separately before merging the results. This approach allows researchers to compare and integrate findings, providing a comprehensive understanding of the research problem.

In a study by Hendrix, Fournier, and Briggs (2001), researchers used a convergent mixed methods design to examine how co-therapy teams impact client outcomes and therapist training in marriage and family therapy. They collected quantitative data from 402 therapy cases, analyzing session attendance, dropout rates, and completion outcomes, along with Global Assessment of Functioning (GAF) scores, relationship satisfaction, and communication measures. At the same time, they conducted qualitative data collection through focus groups with therapists and supervisors, exploring co-therapy’s benefits, challenges, and role in clinical training. By integrating quantitative findings with therapist perspectives, the study provided a comprehensive understanding of co-therapy’s effectiveness in training and practice.

In a study of teacher candidates’ multicultural attitudes and knowledge, Capella-Santana (2003) gathered quantitative questionnaire data from 90 undergraduate elementary education teacher candidates. She also invited all 90 participants to be interviewed “to corroborate the information obtained through the questionnaires”. Padgett’s (2004) study recounts how a team of researchers returned to their initial database as a springboard for more insights. This emerged during the Harlem Mammogram Study, which was funded by the National Cancer Institute to examine factors that influenced delay in response to an abnormal mammogram among African American women living in New York City. The research team Padgett was on had collected both structured quantitative data and open-ended interview data. After data analyses, the team concluded that the women’s decisions to delay were not driven by factors in their quantitative model. The researchers then turned to their qualitative data, highlighted two qualitative themes, and reexamined their quantitative database for support for the themes. To their surprise, the quantitative data confirmed what the participants had said. This new information, in turn, led to a further exploration of the literature, in which they found some confirmation for the new findings.

Explanatory sequential design examples

Explanatory mixed methods research design is a two-phase approach that begins with collecting and analyzing quantitative data, followed by a qualitative phase to help explain or expand on the initial findings. This design is useful for gaining deeper insights into statistical results by exploring participants' experiences, perceptions, or contextual factors. It is commonly used when researchers want to understand the "why" behind numerical trends.

Real-world studies showcase diverse ways in which qualitative data can be collected after developing insights from quantitative data. In a study by Miller, McKenna, and McKenna (1998), the authors collected data from the same pairs of alternatively and traditionally prepared teachers in both the quantitative and qualitative phases of the study. In their study of depression and substance use in high schools, Way et al. (1994) followed up in the qualitative stage of their research with a subset of students who had participated in the quantitative question- naire used in the initial data collection stage of the study.

In a study of adoptive fathers and birthfathers, Baumann (1999) simply asked the fathers completing the questionnaire whether they would be interested in being interviewed.

The study conducted by Way et al. (1994) illustrates how the different stages of an explanatory mixed methods study can play out. The statistical results were used to direct the follow-up procedures. These researchers determined in the first stage of their study that depression differed among suburban and urban high school students. Thus, in the second stage of their study, they decided to use this quantitative result as a basis for studying students in the top 10% of depression scores from different schools in qual- itative follow-up interviews, which comprised the third stage of their research.

Exploratory sequential design examples

Exploratory mixed methods research design begins with a qualitative phase to explore a topic in depth, followed by a quantitative phase to test or generalize the initial findings. This design is useful when little is known about a phenomenon, allowing researchers to develop theories, identify key variables, or create survey instruments based on qualitative insights. It helps bridge exploratory insights with broader statistical validation.

Examples of these designs can be seen in diverse areas, such as educational research on the teaching of reading comprehension (Meijer, Verloop & Beijaard, 2001), a social work study of leaders and coalition building (Mizrahi & Rosenthal, 2001), an organizational study about creating a measure of organizational assimilation in diverse industries (Myers & Oetzel, 2003), the psychological study of the tendency to see oneself as significant to a romantic partner (Mak & Marshall, 2004), and a cross-cultural study of the lifestyle behaviors of Japanese college women (Tashiro, 2002).

For instance, in the research conducted by Tashiro (2002), the author began by collecting focus group data. She developed a questionnaire using data from the focus groups, as well as from other unpublished sources. The focus group participants were then asked to evaluate the clarity of the questions, and the resulting questionnaire was used in a pilot test with new participants who were similar to those from the first phase of the study. The questionnaire’s con-tent was validated by a number of research experts and checked for interitem reliability and test-retest reliability.

Embedded design examples

Embedded mixed methods research design integrates qualitative and quantitative data within a single study, where one type of data plays a supportive role to the primary method. This design is useful when researchers need additional insights to complement the main analysis, such as embedding qualitative interviews within a large-scale survey or including quantitative measures in a primarily qualitative study. It allows for a deeper understanding of complex research questions without requiring separate phases for data collection.

An example of this design can be seen in a study of breath ing therapy for patients with chronic low-back pain (Meling, Hamel, Acree, Byl, & Hecht, 2005). In this randomized, controlled trial, the investigators examined the outcomes of reduced pain, physical and emotional roles, and vitality. The investigators were also curious about how the patients experienced the treatments from breathing therapists, and they asked the patients to report qualitative data in diary entries about their treatment experiences.

In another intervention study, Whittemore, Rankin, Callahan, Leder, and Carroll (2000) studied how social support from peer advisors decreased complications following myocardial infarction. They conducted a randomized controlled trial and had peer advisors provide social support to the patients. Their qualitative data collection within this trial involved collecting data from the peer advisors during the trial.

Victor et al. (2004) conducted an intervention study among individuals with osteoarthritis of the knee. They asked participants in the intervention group to maintain diaries during the intervention to reflect on their symptoms, use of medication, and goals for treatment during the trial. The investigators then collected these diaries after the intervention and analyzed them. Another approach is to equally distribute the qualitative data collection across all treatment and control groups. Finally, investigators might postpone the qualitative data collection until after the intervention and employ a sequential design of data collection.

Conclusion

Mixed methods research offers a powerful way to gain a deeper, more comprehensive understanding of complex research questions. By integrating quantitative and qualitative approaches, researchers can uncover both broad patterns and the underlying reasons behind them. The examples discussed in this article highlight the flexibility and value of different mixed methods designs, demonstrating how they can be applied in various contexts. Whether researchers are looking for inspiration or practical guidance, these studies can serve as useful starting points for structuring one’s own research. Ultimately, mixed methods research enhances the richness and credibility of findings, making it a valuable approach for tackling multifaceted problems.

References

1. Victor, C., Ross, F., & Axford, J. (2004). Capturing lay perspectives in a randomized control trial of a health promotion intervention for people with osteoarthritis of the knee. Journal of Evaluation in Clinical Practice, 10(1), 63–70.
2. Whittemore, R., Rankin, S. H., Callahan, C. D., Leder, M. C., & Carroll, D. L. (2000). The peer advisor experience providing social support. Qualitative Health Research, 10(2), 260–276.
3. Meling, G. L., Hamel, K. A., Acree, L. S., Byl, N. N., & Hecht, F. M. (2005). The effects of breath therapy on patients with chronic low-back pain. Alternative Therapies in Health and Medicine, 11(4), 44–52.
4. Tashiro, J. (2002). Exploring health promoting lifestyle behaviors of Japanese college women: Perceptions, practices, and issues. Health Care for Women International, 23(1), 59–70.
5. Meijer, P. C., Verloop, N., & Beijaard, D. (2001). Similarities and differences in teachers' practical knowledge about teaching reading comprehension. Journal of Educational Research, 94(3), 171–184.
6. Mizrahi, T., & Rosenthal, B. B. (2001). Complexities of coalition building: Leaders' successes, strategies, struggles, and solutions. Social Work, 46(1), 63–78.
7. Myers, K. K., & Oetzel, J. G. (2003). Exploring the dimensions of organizational assimilation: Creating and validating a measure. Communication Quarterly, 51(4), 438–457.
8. Mak, W. W. S., & Marshall, S. K. (2004). Perceived mattering in family and school contexts: Implications for depressive symptoms in early adolescents. Journal of Research on Adolescence, 14(4), 347–366.
9. Miller, L. D., McKenna, M. C., & McKenna, B. A. (1998). A comparison of alternatively and traditionally prepared teachers: Similar beliefs about teaching and learning but different views on collaboration. Teaching and Teacher Education, 14(5), 579–595.
10. Way, N., Stauber, H. Y., Nakkula, M. J., & London, P. (1994). Depressive symptoms, suicidal ideation, and substance use among urban minority adolescents: Exploring the role of family factors. Journal of Youth and Adolescence, 23(6), 655–667.
11. Baumann, C. (1999). Adoptive fathers and birthfathers: A study of attitudes. Child and Adolescent Social Work Journal, 16(5), 373–391.
12. Hendrix, K. G., Fournier, K., & Briggs, S. (2001). Students' perceptions of the influence of race on professor credibility. Journal of Black Studies, 32(2), 259–283.
13. Capella-Santana, N. (2003). Voices of teacher candidates: Positive changes in multicultural attitudes and knowledge. The Journal of Educational Research, 96(3), 182–190.
14. Padgett, D. K. (2004). The qualitative research experience. Wadsworth/Thomson Learning.