Questions: Qualitative Research: Interview Methods and Phenomenology

Question 1

A researcher wants to study the lived experience of grief following sudden job loss. Which design is most appropriate, and why?

• A. A randomized controlled trial comparing grief interventions, because causal claims require experimental control
• B. A large survey measuring grief symptom severity across thousands of participants, because larger samples provide more reliable data
• C. A phenomenological study using semi-structured interviews, because the goal is to understand the structure and meaning of the experience itself
• D. A correlational study measuring the statistical relationship between job loss duration and depression scores

Answer: (C)

Phenomenology is designed for exactly this question: understanding lived experience from the inside. The goal is not to measure how often people grieve or to test whether an intervention reduces symptoms — it is to describe what grieving feels like, what its essential features are, and how people make sense of it. Semi-structured interviews allow the researcher to follow the participant's own categories and meanings, which is what phenomenological inquiry requires. The other designs would all quantify the experience in ways that don't address the meaning question.

Question 2

A critic challenges a qualitative study with 12 participants, arguing it is invalid because the sample is too small. What is the most accurate response?

• A. The critic is correct — any study with fewer than 30 participants cannot produce valid conclusions
• B. Qualitative validity rests on saturation, thick description, and transparency rather than sample size — large samples answer different questions than this study was designed to address
• C. The researcher should have collected quantitative data alongside the interviews to establish validity
• D. The study is valid because 12 participants is sufficient for any type of research design

Answer: (B)

Sample size logic applies to quantitative research seeking to estimate population parameters or test hypotheses. Qualitative research seeks to describe the conceptual landscape of an experience until saturation is reached — new interviews stop producing new themes. A study with 12 deeply interviewed participants producing rich, saturated data can be more valid for its question than a survey of 1,000 respondents giving thin answers. Qualitative standards are different, not absent.

Question 3

In qualitative research, 'saturation' refers to the point at which new interviews no longer produce new themes — this replaces sample size logic as the stopping criterion.

• T. True
• F. False

Answer: True

Saturation is the qualitative equivalent of statistical power: you continue collecting data until the conceptual map is stable, not until you reach a preset number of participants. This is epistemically appropriate because qualitative research is not estimating a population statistic — it is building a conceptual description. When new participants are no longer adding new dimensions to that description, you have reached the stopping point regardless of absolute sample size.

Question 4

A semi-structured interview follows a rigid script so that most participants answer exactly the same questions, ensuring consistent and comparable data.

• T. True
• F. False

Answer: False

The 'semi' in semi-structured is crucial. A semi-structured interview has a guide — open-ended questions and prompts — but the interviewer can probe, follow unexpected threads, and ask follow-up questions based on what participants actually say. This flexibility is the method's strength: the goal is to understand the participant's own categories and meanings, not to fit their experience into a predetermined framework. Full rigidity (structured interviewing) prevents the exploratory depth that qualitative research requires.

Question 5

How does 'member checking' function as a validity check in qualitative research, and what makes it different from reliability checks in quantitative research?

Model answer: Member checking involves returning findings — themes, interpretations, or summaries — to the participants and asking whether the account accurately captures their experience. If participants recognize their experience in the researcher's description, this provides evidence that the analysis reflects what was actually meant rather than the researcher's projections. It has no direct parallel in quantitative research, where validity is assessed through statistical procedures, measurement precision, and sampling methods.

Member checking reflects the underlying epistemology of qualitative research: since the goal is understanding meaning from the participant's perspective, the participant is a legitimate authority on whether the description is accurate. This is one of several qualitative validity strategies (alongside thick description, saturation, and audit trails) that together constitute rigor appropriate to the research goals — not absent rigor.