Qualitative Research Methods Guide | Sampling, Interview Protocols, Coding, Nvivo, and Trustworthiness

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A cross-discipline qualitative research methods guide for sampling logic, semi-structured interview protocols, case selection, coding systems, Nvivo use, triangulation, reflexivity, and trustworthiness checks.

• Works across management, sociology, education, nursing, and public-policy studies
• Covers sampling, interview protocols, coding, Nvivo, triangulation, and reflexivity
• Use discipline pages for field-specific evidence such as classroom observation
• This page explains qualitative research as a cross-discipline method: how to sample participants or cases, design interview protocols, collect text or observation data, code evidence, use software, and report trustworthiness.

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What this page helps you do first

• Works across management, sociology, education, nursing, and public-policy studies
• Covers sampling, interview protocols, coding, Nvivo, triangulation, and reflexivity
• Use discipline pages for field-specific evidence such as classroom observation

What this general methods guide covers

This page explains qualitative research as a cross-discipline method: how to sample participants or cases, design interview protocols, collect text or observation data, code evidence, use software, and report trustworthiness.

It is intentionally broader than the education-specific qualitative page. For classroom observation, teacher interviews, school ethnography, and learning narratives, use the education guide.

Semi-structured interview design and execution

• Interview guide design: preset 5-10 core questions; questions should be open-ended (e.g., "Please describe...," "What do you think are the reasons for..."), avoid closed questions
• Participant selection: use purposive sampling based on research questions to select information-rich respondents. Sample size determined by theoretical saturation (typically 15-30)
• Interview process recording: with participant consent, record interviews; transcribe verbatim afterward. Mark non-verbal information like pauses, laughter, silence
• Interview ethics: obtain informed consent, inform about data usage, protect participant privacy (anonymization)

Case study design types and selection criteria

• Case study types: exploratory case (discovering new phenomena), explanatory case (revealing causal mechanisms), descriptive case (presenting phenomena)
• Single vs multiple cases: single case suits unique or typical cases (e.g., disruptive innovation companies); multiple cases enhance conclusion generalizability through replication logic
• Case selection criteria: cases should be highly relevant to research questions, information-rich, and researchers should have access to sufficient data
• Case report structure: background → data collection methods → case description → cross-case analysis → discussion and conclusions

Grounded theory coding process and theory building

• Open coding: break down text line by line, label with conceptual names; through constant comparison, group similar concepts into categories
• Axial coding: discover relationships between categories, such as causal conditions, context, intervening conditions, strategies, consequences
• Selective coding: identify core category, construct story line, integrate other categories with core category to form theoretical framework
• Theoretical saturation test: when new data no longer generates new categories or relationships, theory has reached saturation

Nvivo software operation and text coding techniques

• Project creation: new project, import interview transcripts, images, audio/video materials
• Node creation: establish parent nodes (like core categories) and child nodes (like subcategories), forming coding system
• Coding operations: select text segments and drag to corresponding nodes, or use "code at new node" function
• Queries and analysis: use Nvivo functions like word frequency queries, coding comparisons, matrix queries to discover patterns in data
• Notes: software is just a tool; coding depth depends on researcher analytical ability; avoid over-relying on auto-coding functions

Qualitative research paper writing framework

• Introduction: explain research background, questions, significance
• Literature review: critically review existing qualitative research traditions and methodological foundations (phenomenology, grounded theory, ethnography, etc.)
• Research methods: detail research design, case/interview selection, data collection process, data analysis methods
• Results: present themes/categories and supporting evidence (interview quotes, case descriptions); indicate participant numbers when quoting
• Discussion: explain theoretical implications of findings, dialogue with existing theory, limitation explanations

Frequently asked questions

What is the appropriate sample size for qualitative research?

Qualitative research does not have a specific sample size formula like quantitative research. Instead, "theoretical saturation" is the standard—when new interviewees or cases no longer provide new information, sampling can stop. Typically 15-30 for interview research, 3-8 cases for case studies.

Must interview data be analyzed with software?

Not necessarily. NVivo, Atlas.ti and similar software improve coding efficiency but are not required. For small numbers of interviews (5-10), manual coding is equally feasible. Software advantages are handling large data volumes, easy traceability, and team collaboration.

How to judge grounded theory quality?

Use these criteria: 1) Groundedness—is theory from data; 2) Credibility—are coding procedures standard and data sufficient; 3) Theoretical sensitivity—does researcher have relevant theoretical literacy; 4) Transferability—does theory have explanatory power for similar situations.

Can case studies mix quantitative data?

Yes. Case studies often use mixed methods, such as questionnaire surveys (quantitative) + interviews (qualitative) within cases. Mixed methods provide richer evidence chains but also increase research complexity.

How to handle researcher bias in qualitative research?

Researcher bias is an important challenge in qualitative research. Coping strategies include: 1) reflection journal recording researcher assumptions and emotions; 2) peer debriefing (discuss coding with colleagues); 3) member checking (feedback findings to some participants for confirmation); 4) multi-data source triangulation.