In mixed methods research, your design would be called a sequential explanatory design (QUAN --> qual). Further, the problem you are facing is how to "integrate" the quantitative and qualitative results from your analyses, or in your case, how to analyze the qualitative data in ways that will integrate well with the questions raised by your original quantitative findings.

One way to help you think about this is to consider the ultimate product that you want to produce from your analyses, and the current recommendation from mixed methods research is to generate a "joint display" of the two sets of results. I have attached the best-known article on this subject. Another good source on this topic is a chapter in: Fetters, M. D. (2019). The Mixed Methods Research Workbook: Activities for Designing, Implementing, and Publishing Projects. Sage.

Simon Stephens The problem that I find in reading many examples of mixed methods that rely on thematic analysis is a lack of integration. In particular, too many papers simply run statistical tests with on the quantitative data and thematic analysis of the qualitative data, generating two sets separate results.

Dear Morgan

Don't you think the thematic analysis of the transcribed data would be a good method for analyzing your qualitative data?

Your plan assumes that what you need will appear in your themes, which is optimistic. But if you already know that from what you heard in your interviews then it will work.

Typo, just eliminate "car."

A lot depends on the questions you ask in your qualitative interviews. Have you collected that data yet?

In general, for a sequential explanatory design you should be asking about the elements of your quantitative data that need the most clarification.

The pre-knowledge you have identified in your literature review, which drives your questions in a qualitative review, is critical. Mayring (2014, p. 104) suggests two steps of qualitative analysis. In the first (deductive) step, you select theoretical categories and principles of interpretation from previous research (your preknowledge) as the guides in both gathering and analyzing data in the current study.

Mayring Ph (2014) Qualitative content analysis: theoretical foundation, basic procedures and software solution. Klagenfurt. URN, Available at: http://nbn-resolving.de/urn:nbn:de:0168-ssoar-395173

Interpreting your interview data depends on your theoretical framework/interpretive approach. If you approach your data phenomenologically, you should avoid framing or coding your data. Instead, you should capture the essence/core of interview accounts based on rapport and shared understandings (Silverman, 2014). According to Lune and Berge (2017), such an approach could enable you to interpret the content with a practical grasp of meanings and actions.

Lune, H. & Berg, B. L. (2017). Qualitative research methods for the social sciences (9th ed.). Pearson Higher Ed.

Silverman, D. (2014). Interpreting qualitative data (5th ed.). SAGE.

Good luck,

In the explanatory sequential mixed methods design, you should use your qualitative data to expatiate on the quantitative findings (Creswell & Creswell, 2018). Simply put, you could use your interview findings to shed light on unexpected or contradictory survey responses. I would recommend that you go through the illustrations provided by Creswell and Creswell (2018), fully cited below.

Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications. https://us.sagepub.com/en-us/nam/research-design/book255675

Good luck,

I don't think you need to do a thorough thematic analysis since your design dictates that the qualitative data acts to clarify some aspects of your main quantitative findings. You could stick with Silverman's (2014) phenomenalogical interpretation suggestion, focusing on the core of communicated messages, which could be enough to clarify any doubts in some aspects of your quantitative findings, which should be the main drive of your study according to your design.

Good luck,

H.P

Oxford Brookes University

The first thing is that Ph.D. is going deep in Well not wandering around the Ocean.

secondly, you have done a study. you have adopted fixed and emergent design (Explanatory Sequential). then synergistic approach, then independent level of interaction. I think the best stage is Merging-mixing during interpretation instead of Connecting- mixing during data collection, Embedding- mixing during data analysis and Mixing at the level of design. In the discussion section, you will have to align your study results with earlier research studies, either your findings are favored or disfavored by previous research works.

I think Clarke and Braun (2021) thematic analysis is appropriate for qualitative data

I you don't get answers to your hypothesis, you need more groups or interviews as there is not minimum or maximum amount of groups, it depends on the discourse. The number of participants does not obey a statistical representation, but in semiological terms.

Hope it helps you.

I would suggest you go back to your research question and objectives, what are you trying to answer and achieve. I would suggest keep it simple as the more complexity you enter into the more you can get away from the question you are trying to answer. It is difficult to suggest suitable a suitable methodology without seeing you research questions.

H. P.

You don't really have a mixed-methods study because there was no qualitative design that guided your study. What you have is a quantitative study that used interviews ex post facto to explain some of the results. Check with your Chair, but I'd suggest not framing it as a mixed-methods study because there were no specific qualitative methods or designs used other than the interviews.

For efficiency, if your Chair agrees, I'd suggest that you might add to your discussion section content on the problematic variables, the rationale for conducting the interviews, and what you learned from them. You can then include quotes that illustrate this.

Susan P Robbins I disagree because the sequential explanatory pairing of surveys followed by qualitative interviews is one of the best known designs in mixed methods. As the notation suggests (QUAN --> qual), the qualitative study is not intended to be a stand alone piece of research; instead, it is specifically intended to learn more about the quantitative results.

David L Morgan Is that accurate even if there is no specific qualitative design other than simply conducting interviews? I've mentored students who have done sequential mixed-methods studies (both QUAL--> quan and QUAN-->qual), but they have always had a specific methodology spelled out in their proposals.

The content of the interviews should address the research goals but that is about it.