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Sample Lecture
- 2. Topics Qualitative Research • Definition • Research Design • Preparation for a project • Data Collection Methods • Data Analysis • Rigor
- 3. Objectives After a lecture on qualitative research, students will be able to: • Name and the 2 types of qualitative data tools. • Describe 1 quality of qualitative data collection that increases rigor.
- 4. Qualitative Research - Definition Stories Experience Words Inductive process Companion to quantitative statistics Understand how interventions work Generates theories/hypotheses
- 5. Qualitative Research - Design • Begin with problem • Ask open-ended questions • Use natural setting • Remember – researchers are key! • Listen to the meanings
- 8. Qualitative Research – Data Collection Tools Observations Physical setting Activities, discussions, and interactions People present Researcher behaviors in the environment Documents: Questions Guides Visual Aides Considerations: date of creation, key information, time commitment
- 9. Qualitative Research – Preparation Pilot your tools (i.e. focus group guides) Content validity: experts on content confirm accuracy Face validity: representatives of the population confirm clarity and understanding
- 10. Qualitative Research – Data Analysis • Qual is iterative: simultaneous data collection & analysis • Note: continuous process but appears linear
- 11. Qualitative Research – Data Analysis • Coding: chunking data into smaller parts • Code: title of segment/part • Codebook: list of codes • Saturation: no new information collected; no new codes • Note: additional coding occurs until the codebook is fully developed
- 12. Qualitative Research – Creating Themes • Theme: emerging pattern • Multiple themes common • Goal: chunk data into manageable parts • Themes are: • Relate to question • Explain part of outcome
- 13. Qualitative Research – Data Analysis
- 14. Qualitative Research – Rigor • Adopt research methods • Descriptions are detailed • Member checking • Triangulation • Frequent debriefing (memos)
- 15. EXAMPLE: Dietetic Preceptor Perceptions of Requirement for Graduate Level Interns Focus Groups with Dietetic Preceptors • Pilot: Mock focus group (FG) with dietetic preceptors • Tool: FG guide (via Zoom) • Coding: Session transcribed verbatim, coded into themes • Methodology: Two researchers coded separately, reconciled; tie breaker available • Themes: Expectations of GLS and COVID
Editor's Notes
- In this lecture, we will discuss an overview of qualitative research. You won’t be an expert in it after this session, but you will have a better understanding of what qualitative research is and how it is conducted.
- The objectives of this session will allow you to describe qualitative research data collection methods as well as how to increase the rigor of a qualitative study.
- Qualitative research focuses on words and stories and experiences. It is inductive, so the researcher moves from detailed facts to broader ideas and theories. Qualitative research is not the opposite of quantitative research. It is its companion – they complement and support each other. It can help us understand how interventions work. It also help us to to generate theories and research questions to keep the research cycle going.
- Just like quantitative research – qualitative research begins with a problem. Usually, this problem is identified through literature review along with personal knowledge and interest in the topic. The qualitative nature has researchers ask open ended questions to remain open to the participants experiences – other topics or details may emerge to increase the overall understanding of the problem. Using a natural setting allows researchers and participants to be in the setting where the problem being studied occurred. Because qualitative research is very relational, the researchers are a key instrument in the project. Finally, it’s important to listen to participant meanings – final reporting of the data should represent the interpretation of both the participants and the researcher – giving multiple vantage points.
- Here is a great image depicting the differences in qualitative and quantitative research. The circles are the same size because there is not one that is better than the other. Qualitative is inductive, generates hypotheses, and is iterative. Quantitative research is deductive and tests hypotheses. Where they overlap is another type of research called mixed methods, which is a combination of qualitative and quantitative research.
- Here is a graphic of the two styles of research. The left shows quantitative research, which is deductive. It starts with a hypothesis to test, it produces facts through statistical measures and models, and it narrows down to a conclusion. Qualitative research on the other hand is inductive, it starts with small facts (found in the literature and researcher experiences). Then those facts are organized into patterns to form hypotheses and broadened to theories.
- Observational tools include where you are, or your physical setting and the activities or things you do within that setting. It also depends on the people or participants that have attended the session. This also includes the researcher. How the researcher behaves can impact the observations. Imagine you are a participant in a study where the researcher was stressed, nervous, or indifferent. How would that impact your participation? Documents include the guides that help you conduct your research. This includes a focus group or interview guide that serves as a roadmap through the conversation. These are carefully formulated to capture the purpose of the project and to embed a theory, when used. Visual aides are also important in guiding your research. Keep these considerations in mind with your documents: when was it created, where is the key information, how long does it take
- No that we have discussed some of the tools used in qualitative research. It’s important to point out that these tools need to be “tried on for size” first. Much like a pipette needs to be calibrated, your tools need to be tested before conducting your research. You can confirm content through content validity – asking content experts to review your tool for accuracy. You can confirm face validity through a representative of the population confirming understanding and clarity in your tool
- So up to this point, you may have only read qualitative data. Is it clear that there is a start and an end? That may be how it appears… Qualitative research is an iterative process – meaning that the data collection and analysis are happening at the same time. It’s important to remember while there chicken or egg during the data collection, when you go to report and publish your data, it does have a more linear appearance.
- Coding is the process of taking your information and chunking it into smaller parts. A code is simply the title of that segment or part. The collection of these codes develops your codebook. It’s important to note that the coding process continues according to the methodological process that the researchers are following. Sometimes multiple researchers coding the same content and coming together for agreement. You know you have reached the end of data collection, or saturation, when you aren’t getting any new information from your participants (no new codes).
- A theme is a pattern that emerges from the data you are analyzing. It is common to have multiple themes (think of it as different chapters in a textbook, different modules in a course, or different objectives within a lecture. They are all joined by a common overarching connection but they each serve a unique purpose).
- 1st – read the data and label the parts Next chunk the information into segments Label these segments with codes Combine codes that end up being redundant Make the codes into themes (it is good practice to use the data to name the themes – in other words, use the words of your participants – this increases rigor by reducing research bias)
- There are some practices that may not make it into publication but will help you to interpret your data from a more holistic and objective perspective. Research by Creswell recommends that at least two of the following are recommended: Adoption of research methods (remember qual is quants friend not foe), detailed descriptions (qual is known for being verbose, it also makes it stronger), member checking (after you write up the analysis, check with the participants – are you representing them in the way they had intended?), triangulation (get data from multiple sources – observations, focus groups, etc), and frequent peer review/debriefing and keep memos. Meaning, when you read the data for the first time, memo your thoughts as you code it. Do this each time you encounter the data (whether that is through individual coding, reconciliation, or team conversation).
- for example – I conducted a research study using focus groups with dietetic preceptors, before I began my data collection, I asked a group of dietetic preceptors that were not in my study sample to join a mock focus group. From this, I was able to make critical edits that ultimately helped my project gain a deeper understanding through clear and concise communication). The tool I used in the focus groups was a script that had the questions I was most interested in (which also directly focused on my outcome). These included: how did COVID impact your job, what do you consider to be best practices of a dietetic preceptor, and what are your perceived facilitators and barriers to the move to graduate level requirement for interns We transcribed the Zoom sessions and coded them separately. When we came together we discussed what the best fit would be, taking memos along the way. A third researcher was available for any decisions where reconciliation could not be reached or further deliberation was needed. Themes that emerged from this project included: Expectations of graduate level students, Motivations to be a Preceptor, and Preceptor Training (among others)