Qualitative Study

In short:  Qualitative studies often have smaller sample sizes, which makes them a practical option for researchers at the Masters level. But they may require you to assemble a team to assist with the coding of data such as interview transcripts. They also require approval from TC’s Institutional Review Board (IRB) for human subjects research.

Key Components

• Literature review
• Theory-informed research question
• Non-numerical data source
• IRB approval
• Data collection
• Appropriate sample size
• Coding analysis 
• Findings & Discussion

The whole story:  A qualitative study involves collecting and analyzing non-numerical data (e.g., interviews, focus groups, fieldwork with in vivo behavioral observations) to explore complex questions about meaning, experience, process, or context. Qualitative studies apply systematic, theory-informed methods to code data in order to identify and label patterns, themes, or key ideas so as to gain insights into patterns, meanings, or social processes, grounded in support by multiple examples (e.g., quotes, behavioral observations). 

Students conducting a qualitative study must begin with an appropriately comprehensive review of existing empirical literature on their chosen topic, which should conclude with a description of gaps in the literature and/or future directions still needed. This initial empirical literature review should be written in a manner that serves to justify the value of the current qualitative study, either as a valuable addition to the existing empirical knowledge base or as data that could potentially inform future targets for clinical intervention via the exploration of complex questions about meaning, experience, process, or context. 

The student must next pose a specific set of systematic, theory-informed open-ended questions. These open-ended questions should be aligned with a research design that follows recognized qualitative approaches (e.g., grounded theory, thematic analysis, case study, discourse analysis, CQR), with methods that are logically aligned with their chosen research question. A high-quality qualitative research question explores how meaning or experience is shaped within a narrow set of clearly-defined concepts that can be examined through open-ended methods such as interviews, focus groups, or naturalistic observations.

The student should next identify the non-numerical data sources (e.g., interview transcripts, observations, texts) and the qualitative data-gathering methods (e.g., interviews, focus groups, fieldwork with in-vivo observations) that can be used to answer their open-ended questions. Students can secondarily analyze existing documents or qualitative datasets for additional themes that add new, meaningful insights beyond that of an original qualitative study. 

The student must next obtain approval of an IRB protocol that clearly describes their qualitative study, their approach to collecting data and handling data, and demonstrates appropriate management of any and all potential risks of qualitative study participation. It is expected that students will design their proposed qualitative study in the lowest risk manner possible to feasibly answer their research questions. 

Next, the student must collect and handle data adhering fully to the methods described in their IRB protocol. The resulting dataset should have a sample size large and robust enough to support meaningful thematic analysis.

Once data is collected, students should engage in “coding” the data by identifying and labeling patterns, themes, or key ideas. Coding analysis should be systematic, well-documented, and clearly explained, with all codes and their interpretations being traceable and supported by excerpts or examples from the data. In most cases, you cannot code alone: Students should recruit peers to form a coding team. The frequency of agreement between members of the coding team (inter-rater reliability) should be tested with statistics such as Krippendorf’s Alpha. This is a key measure of the validity of your study. A qualitative coding tool, such as NVivo software, may be used to conduct qualitative coding analyses in a systematic manner. 

Results should go beyond description and should be thoughtfully interpreted, showing insight into patterns, meanings, or social processes, with each finding having numerous examples (e.g., quotes, behavioral observations) to support it. Findings must be clearly explained and linked back to the research question.

The Discussion should provide a nuanced account of how results add to the existing empirical knowledge base or inform future targets for clinical intervention, or otherwise add value to the field of clinical psychology. Limitations should be acknowledged and possible future directions for follow-up research should be delineated. The final integrative project should follow a clear structure (e.g., abstract, introduction, methods, results, discussion, references) and provide well-organized tables or figures as applicable. All references should be properly listed and all writing should be in APA style.

To learn more:  APA’s Journal Article Standards for Qualitative Research (https://apastyle.apa.org/jars/qualitative), including a very detailed and useful outline (https://apastyle.apa.org/jars/qual-table-1.pdf).

Relevant Courses at TC:   

• Research Methods in Clinical Psychology (CCPX)
• Introduction to Qualitative Research Methods (MSTC)
• Practicing Qualitative Research Methods (MSTC)
• Qualitative Methods (ITSF)
• Introductory Methods of Ethnography and Participant-Observation (ITSF)
• Ethnography and Participant-Observation (ITSF)

 Please see our Research Methods Concentration for a full list of courses