SMU RHM411: Research in Health and Society — Qualitative Methods Guide

SMU RHM411: Research in Health and Society is the kind of module where method matters just as much as topic. Qualitative research helps you understand how people experience health, how communities interpret care, and how social structures shape outcomes. This guide focuses on the practical qualitative toolset you need to plan, conduct, analyse, and report research in the South African health and society context—especially as encountered in Sefako Makgatho Health Sciences University (SMU) Medical Sociology.

Qualitative methods in RHM411 are not just “interviews.” They include designing research questions, selecting participants, collecting data ethically, managing trust and rigour, analysing meaning, and producing findings that hold up to scrutiny. You will also learn how to justify qualitative choices in ways that align with health research expectations (credibility, reflexivity, dependability, and transferability), while remaining sensitive to South Africa’s linguistic, cultural, and structural realities.

1) Positioning Qualitative Research in Health and Society (RHM411 Context)

Qualitative methods aim to understand meanings, processes, and social mechanisms. In health and society, that might mean exploring how individuals make sense of illness, how families negotiate caregiving responsibilities, or how clinics’ routines affect patient dignity and adherence. In RHM411, the core value is that qualitative data reveals what cannot be captured by survey numbers alone—particularly in areas such as stigma, power relations, and lived experience.

1.1 What “qualitative” means in health research

Qualitative research usually focuses on:

• Experience: how people experience illness, treatment, waiting, side effects, or institutional interactions.
• Perception and interpretation: how health services are understood, trusted, or distrusted.
• Interaction: how people communicate with providers and how institutions behave in practice.
• Social context: how poverty, gender norms, migration, violence, religion, or disability shape health behaviour.
• Process over time: how care pathways unfold and how decisions are made step-by-step.

A key idea is that qualitative research treats reality as socially constructed—not “false,” but interpreted through human experience. This matters because in RHM411 you are not merely collecting opinions; you are studying meaning and social practice.

1.2 Why qualitative methods are especially relevant in South African health settings

South Africa’s health landscape includes:

• High levels of historical and ongoing inequality (economic, spatial, and racial).
• Multiple languages and communication needs, including isiZulu, isiXhosa, Sesotho, Setswana, Afrikaans, and English.
• Diverse health systems: public sector, private sector, and traditional/community health practices.
• Migration and informal employment patterns, which influence continuity of care.
• Persistent structural barriers: transport costs, documentation issues, stigma, gendered constraints, and uneven service quality.

Qualitative methods help you document how these forces operate at the level of everyday life. For example:

• Quantitative data might show low appointment adherence; qualitative research can explain why—such as fear of judgement, clinic crowding, inability to take time off work, or the breakdown of trust due to past mistreatment.
• Surveys might report “low knowledge of HIV prevention”; qualitative work can explore how cultural beliefs shape what counts as knowledge, and how misinformation travels through peer networks.

1.3 Types of qualitative research designs you’ll encounter

RHM411 commonly draws from major qualitative traditions. You should be able to identify what design fits a proposed question:

1. Phenomenology

   • Goal: understand lived experience (e.g., lived experience of chronic pain in a specific clinic).
   • Typical outputs: rich descriptions of common structures of experience.

2. Grounded Theory

   • Goal: generate or refine a theory about a process (e.g., how young adults decide to initiate ART).
   • Typical outputs: conceptual categories and a model of relationships.

3. Ethnography / focused ethnography

   • Goal: understand cultural practices and routines within a social setting (e.g., patient flow and informal interactions in a primary healthcare facility).
   • Typical outputs: thick description of a setting and cultural rules of behaviour.

4. Case study

   • Goal: explore a bounded system (e.g., a community-based adherence programme in one township, or a mental health referral pathway in one district).
   • Typical outputs: integrated account across multiple data sources.

5. Narrative inquiry

   • Goal: understand stories and how identity is shaped through illness narratives (e.g., how caregivers narrate disability and care decisions).
   • Typical outputs: narrative themes and story structures.

In exam responses, it often helps to state:

• which design is best aligned with your research question,
• what kind of knowledge claim the design supports,
• and how that design fits ethical and practical realities.

1.4 Qualitative research is not “less rigorous”—rigour looks different

A common misconception is that qualitative research is “subjective.” In health research, the expectation is not objectivity in the positivist sense; rather it is rigour through transparency and reflexivity.

Rigour in qualitative studies typically involves:

• Credibility (do findings reflect participants’ realities?)
• Transferability (can others assess relevance to their context?)
• Dependability (are methods consistent and traceable?)
• Confirmability (are interpretations grounded and not merely the researcher’s bias?)

You achieve this through practices like:

• clear sampling decisions and documentation,
• interview guides and pilot testing,
• consistent coding processes,
• reflexive journaling,
• audit trails,
• and triangulation (when appropriate).

1.5 Example: deciding whether qualitative is needed (with a mini scenario)

Suppose a clinic reports low uptake of cervical cancer screening among women aged 25–45. A mixed-methods team might start with quantitative trends. But if the research aim is to understand how women interpret screening, trust clinicians, navigate cultural beliefs, and manage costs/time, qualitative methods are the best fit.

Possible qualitative question:

• “How do women in Mamelodi understand cervical cancer and interpret barriers to screening?”

Here, qualitative design could be:

• phenomenology (lived experience of fear and meaning-making),
• grounded theory (process of decision-making and care pathway navigation),
• or case study (screening programme routines and community context).

2) Research Design, Sampling, and Fieldwork Planning for RHM411

Strong qualitative research starts long before data collection. In RHM411, designing a coherent plan is essential: your research question must align with your design, which must align with sampling, which must align with data collection and analysis. When these elements fit together, your study becomes defensible.

2.1 Developing a qualitative research question (and sub-questions)

Qualitative questions usually start broadly and become more focused as you learn. They often include:

• participants’ perspectives,
• a social process or meaning system,
• and a context (clinic, community, hospital department, or programme).

A useful structure:

1. Who (population or group)
2. What phenomenon (experience, meaning, process)
3. Where/within what system (clinic type, community, service pathway)
4. From whose standpoint (participants’ perspectives)
5. Under what condition (stigma, access barriers, institutional routines)

Example set (women’s screening):

• Broad: “How do women experience cervical cancer screening access in a public primary healthcare setting?”
• Sub-questions:
  • “How do women describe their first exposure to information about screening?”
  • “What meanings do women attach to screening procedures and results?”
  • “How do service routines (waiting times, provider communication) shape decisions?”

In an exam, you should also mention what the question is not aiming for:

• It is not primarily to measure prevalence or test causality.
• It is to understand meaning and process, which may later inform interventions or policy.

2.2 Choosing an appropriate qualitative design for the question

Continuing the cervical screening example:

• If the focus is on shared lived experience:
  Choose phenomenology.
• If the focus is on a decision-making process and its stages:
  Choose grounded theory.
• If the focus is on how a service system works in practice (staff routines, patient flow, informal behaviours):
  Choose ethnography or case study.

A defensible answer in RHM411 often uses alignment language:

• “The design is chosen because it produces data that directly addresses the phenomenon described.”

2.3 Sampling strategies: purposive, theoretical, and practical realities

Qualitative sampling is typically purposive rather than random. The logic is to select information-rich cases, not to represent the population statistically.

Common sampling approaches:

1. Purposive sampling
   • Choose participants who have direct experience relevant to the question.
2. Maximum variation sampling
   • Include participants with different characteristics (age, language, employment status) to capture a wide range of perspectives.
3. Homogeneous sampling
   • Select one relatively consistent group to explore deeper within-case patterns (useful for sensitive topics).
4. Criterion sampling
   • Include cases that meet a specific criterion (e.g., women who have never screened vs women who have screened regularly).
5. Snowball sampling
   • Useful for hard-to-reach communities or stigmatised groups.
6. Theoretical sampling (grounded theory)
   • Sample iteratively based on emerging categories until theoretical saturation.

Saturation (and what exam markers want you to understand)

• Data saturation: you repeatedly see no new themes or information.
• Code saturation: new codes stop emerging.
• Meaning saturation: you understand variations of themes sufficiently.

Importantly, saturation is not a magic number. It depends on complexity, heterogeneity, and the focus of your question. Still, in practical planning, students often propose approximate sample sizes to be realistic (e.g., 12–25 interviews), then justify how that number supports depth and saturation within their specific context.

2.4 Sample selection example with coherent categories

Assume the study aims to explore experiences of cervical cancer screening among women in a specific Gauteng community.

A purposive sample plan might include:

• Women who never screened
• Women who screened once but discontinued
• Women who screened regularly (e.g., within recommended intervals)
• Different age bands (e.g., 25–34; 35–45)

You might also incorporate diversity in:

• language preference,
• marital status,
• employment type (formal vs informal),
• and prior contact with health services.

In qualitative studies, you should show:

• why each group is needed,
• and how that helps answer the research question.

2.5 Recruitment and consent logistics in South Africa

Recruitment can be approached through:

• clinic support staff (with permissions),
• community health workers,
• NGOs working in health,
• community leaders (where appropriate, and without compromising voluntariness),
• or direct invitation after clinic attendance.

Consent must be:

• informed (participants understand purpose, procedures, risks, and benefits),
• voluntary (no coercion),
• and documented appropriately (written consent when possible, or verbal consent with witness if literacy barriers exist—depending on ethics guidance).

For multilingual contexts:

• provide consent forms in relevant languages,
• allow time for explanation,
• and use interpreters carefully.

Ethical risk examples that matter in health research

• Emotional distress when discussing traumatic experiences.
• Fear of stigma when discussing sexual and reproductive health.
• Confidentiality risks when interviews happen near clinics or in community spaces.

Your field plan should include mitigations:

• privacy arrangements,
• referral options if distress arises,
• and clear confidentiality practices.

2.6 Building fieldwork feasibility: scheduling, venue, and recording

Your data collection plan must show feasibility:

• Where interviews occur (private room in clinic, community hall room, participant home only if safe and ethical).
• Time length (often 45–90 minutes for in-depth interviews; focus groups can vary).
• Recording plan (audio recording with consent; backup notes).
• Translation plan (if interviews are not in English).
• Data security plan (password protection, secure storage, anonymisation).

Example of fieldwork planning details:

• First interviews used to test the interview guide.
• Adjustments made to wording for clarity in participants’ preferred language.
• Scheduling aligned with participants’ work patterns (evenings or weekends).

2.7 Pilot testing qualitative instruments

Pilot testing is not only a quantitative concept. In qualitative research, pilots help you:

• check if questions are understandable,
• test whether the order of questions produces smooth conversation,
• identify confusing terminology,
• and check whether the interview length feels acceptable.

A strong RHM411 answer describes:

• what you pilot (interview guide),
• how you pilot (with similar participants),
• what you change (rewording prompts, adding clarifying probes),
• and how those changes strengthen validity.

2.8 Fieldwork diary and reflexivity as planning tools

Qualitative rigour uses reflexivity:

• tracking your assumptions,
• recording your reactions during interviews,
• monitoring how your identity and interaction style might shape responses.

A reflexive diary might include:

• power dynamics observations (e.g., participants appear hesitant when clinic staff are nearby),
• how your language choice affects openness,
• unexpected themes that require guide adjustment.

This becomes part of your audit trail and supports confirmability.

2.9 Example: aligning design, sampling, and data collection

If the design is grounded theory:

• start with purposive sampling,
• conduct interviews,
• code data early,
• then use theoretical sampling to follow emerging categories.

If the design is phenomenological:

• you might use homogeneous sampling (participants sharing similar experience),
• conduct deep interviews focusing on lived experience,
• and analyse for meaning structures.

RHM411 exam questions often test your ability to show this logic rather than listing methods disconnectedly.

3) Data Collection Techniques in Qualitative Health Research (Interviews, Focus Groups, and Beyond)

Data collection is where methodological commitments become real. For RHM411, your key responsibility is to produce data that is ethically collected, contextually rich, and suitable for systematic analysis. This section covers interviews, focus groups, observation, and documentation strategies, with practical detail for health and society research in South Africa.

3.1 In-depth interviews: purpose and craft

In-depth interviews (IDIs) aim to explore participants’ meanings, experiences, and interpretations.

Interview types you should recognise

1. Semi-structured interviews
   • Core questions + flexible probes.
   • Common in health and society research.
2. Unstructured interviews
   • Few pre-set questions; conversation-led.
   • Useful for exploratory work, but harder to compare across participants.
3. Structured qualitative interviews
   • More consistent wording and ordering.
   • May be used with coding frameworks, but reduces flexibility.

For RHM411, semi-structured interviews are often the best balance of depth and comparability.

3.2 Designing an interview guide that works in real clinics and communities

A strong interview guide usually includes:

• Opening questions to build rapport.
• Experience questions about the phenomenon.
• Meaning questions about interpretation and beliefs.
• Context questions about social and structural barriers/facilitators.
• Process questions that explore sequences (e.g., “How did you decide next steps?”).
• Concluding questions for recommendations (“What would improve services?”).

Probing strategies (examples)

• Clarification: “Can you tell me what you mean by…?”
• Elaboration: “What happened next?”
• Contrast: “Was that experience different from others you’ve had?”
• Specificity: “How often did it occur?”
• Emotional meaning: “How did that make you feel?”
• Sensitivity: “Would you prefer not to answer that part? If not, we can skip it.”

In exam settings, markers reward the ability to show you understand probes, not just question topics.

3.3 Rapport-building and managing power relations

Health research often involves asymmetrical power:

• participants may fear judgement,
• may interpret researchers as linked to institutions,
• or may be constrained by time and waiting pressures.

To reduce power imbalance:

• conduct interviews in private spaces,
• emphasise voluntary participation,
• explain there are no “right or wrong” answers,
• and clarify confidentiality.

You must also recognise that your identity (age, gender, language proficiency, institutional affiliation) influences the interview relationship. Reflexive documentation helps you interpret this impact during analysis.

3.4 Conducting interviews with multilingual participants

In South Africa, language choice affects data quality and participant comfort.

Options:

1. Interview in participant-preferred language with you (if fluent).
2. Use a trained interpreter.
3. Use a bilingual assistant not necessarily trained in interpretation—ethics may require training; follow institutional guidance.

If an interpreter is used:

• brief interpreter before interview,
• ensure confidentiality agreement,
• discuss how to handle translation of emotion and idioms,
• and consider transcription translation decisions early.

3.5 Recording, transcription, and data management

Rigor requires careful data handling:

• audio recording with consent,
• immediate field notes after interviews,
• secure storage of recordings and transcripts,
• pseudonyms and removal of identifying details.

Transcription decisions:

• verbatim transcription vs selective transcription (often verbatim for analysis),
• language of transcript (original language vs translated into English),
• handling non-verbal cues (laughter, pauses, crying).

For analysis, consistency matters: decide early whether coding will be done on original-language transcripts or translated versions. Translation can change nuance; therefore in RHM411 responses, it is good practice to mention:

• why you choose a route,
• how you maintain meaning during translation.

3.6 Focus group discussions (FGDs): when and why to use them

Focus groups gather interaction among participants, allowing researchers to observe:

• shared norms,
• disagreement and consensus formation,
• social persuasion,
• group identity boundaries.

FGDs are particularly useful for topics like:

• community beliefs about health services,
• stigma narratives,
• gendered expectations,
• or collective understanding of policy.

However, FGDs require extra attention to confidentiality and group dynamics. Participants may fear exposure of sensitive stories.

Typical FGD structure

1. introduction and consent,
2. warm-up questions,
3. key topic questions with guided discussion,
4. closing and opportunity to add anything else.

Managing domination and silence

• Invite quieter participants: “I’d like to hear from you as well.”
• Limit dominant speakers: “Let’s make space for others.”
• Use structured turns if needed.

3.7 Observation and ethnographic elements: “what people do” vs “what people say”

Observation can be:

• participant observation (researcher interacts within setting),
• non-participant observation (researcher observes with limited engagement),
• structured observation using checklists,
• or “thick description” style notes.

In health settings, observation might capture:

• patient flow and waiting practices,
• how staff communicate (tone, clarity, interruptions),
• physical accessibility (signage, privacy screens),
• how confidentiality is maintained or compromised.

Ethics is critical: if observation includes identifying private interactions, consent and permissions are needed. If observation is non-invasive and within public/approved research spaces, it still requires ethics approval and careful handling.

3.8 Document analysis: adding context beyond interviews

Qualitative research often benefits from document review, such as:

• policy documents (e.g., screening guidelines),
• programme reports,
• clinic posters and health education materials,
• referral forms,
• training manuals.

Document analysis can be:

• to understand organisational intent,
• to compare with participant accounts,
• or to identify the language of health systems (what is emphasised, omitted, or framed).

In RHM411, this supports triangulation: not to “prove” but to deepen interpretive context.

3.9 Triangulation: types and use in qualitative health studies

Triangulation aims to strengthen credibility by using multiple perspectives or data sources.

Common triangulation types:

• Data triangulation: multiple participants, settings, or time points.
• Method triangulation: interviews + observation + document analysis.
• Investigator triangulation: multiple researchers coding or discussing interpretations.
• Theory triangulation: interpreting data through more than one theoretical lens (used carefully).

In exams, it’s important not to claim triangulation means “more truth.” It means richer understanding and more checks against single-source interpretation.

3.10 Worked example: mapping data collection to a specific RHM411 scenario

Imagine a study question:

• “How do community health workers (CHWs) describe their role in supporting HIV adherence among patients in a primary healthcare ward?”

A coherent data collection plan could include:

• Semi-structured interviews with CHWs (experience and meanings).
• Interviews with a small group of patients (care pathway and support).
• Observation of CHW–patient interactions during routine follow-up (communication practices).
• Document analysis of adherence guidelines used by the ward.

This triangulated design allows the researcher to explore both:

• what CHWs believe they do and why,
• what patients experience and interpret,
• and what the formal system encourages.

4) Qualitative Data Analysis and Trustworthiness (Coding, Themes, and Rigour)

Qualitative analysis turns raw data into interpretive findings. RHM411 requires you to demonstrate analysis competence: not only “themes,” but systematic coding logic, transparent interpretive steps, and defensible trustworthiness practices.

4.1 The overall analysis workflow (practical steps)

A common analysis workflow includes:

1. Preparing data
   • transcripts, field notes, documents.
2. Initial reading
   • understanding overall meaning.
3. Coding
   • generating categories and labels for meaningful segments.
4. Developing themes
   • grouping codes into patterns that answer the research question.
5. Refining and checking
   • returning to data for consistency.
6. Interpretation
   • relating themes to social context and theoretical framing.
7. Writing up findings
   • using excerpts to support interpretations.

Your exam answers should show you understand this sequence and where quality checks occur.

4.2 Coding: what it is and how to do it

Coding is assigning labels to segments of data to capture meaning. Coding can be:

• inductive (arising from data),
• deductive (driven by theoretical framework or research question),
• or hybrid.

Code types you might describe

• Descriptive codes: summarise what is happening (“clinic waiting is too long”).
• In vivo codes: use participants’ own words (“they treat us like we are criminals”).
• Process codes: capture actions and sequences (“I asked for help,” “I stopped going,” “I returned when…”).
• Attribute codes: participant characteristics or conditions that matter (“unemployed,” “has transport difficulties”).
• Analytical codes: interpretive labels (“loss of dignity,” “fear of exposure,” “structural barrier”).

A strong RHM411 response may include a mini coding example. For instance, in a screening context:

• Segment: “When I got there, the nurse spoke fast and I felt stupid.”
• Possible codes: “fear of judgement,” “communication barrier,” “loss of confidence,” “shame”.

4.3 Developing themes: from codes to patterned meaning

Themes are higher-level ideas that integrate multiple codes. A theme should:

• address a part of the research question,
• be grounded in evidence,
• and show internal coherence.

A helpful way to explain theme development:

1. create a list of codes,
2. identify which codes repeatedly appear together or relate conceptually,
3. group them into candidate themes,
4. review themes against data,
5. define theme boundaries (what is inside vs outside a theme).

Example theme set (illustrative)

For cervical screening, candidate themes might include:

• “Trust and respectful communication” (codes: “nurses dismiss me,” “they don’t explain,” “I feel ashamed”)
• “Costs, time, and practical constraints” (codes: “transport money,” “taking leave,” “childcare”)
• “Understanding risk and consequences” (codes: “I thought it’s for older women,” “I didn’t know symptoms”)
• “Stigma and social influence” (codes: “people will talk,” “husband approval,” “privacy concerns”)

In exams, you should also include negative cases (data that challenge your theme). This supports credibility.

4.4 Thematic analysis: common approach in health and society

Thematic analysis is flexible and widely used in qualitative health research. You can describe:

• familiarisation with data,
• coding,
• generating themes,
• reviewing themes,
• defining and naming themes,
• producing the report.

Even when your course teaches specific variants, exam answers can use the thematic analysis logic as a clear structure.

4.5 Grounded theory analysis: constant comparison and memoing

If RHM411 expects grounded theory skills, you should describe:

• open coding (initial categories),
• constant comparison (compare incident to incident, code to code),
• axial coding (link categories and conditions),
• selective coding (identify a core category and integrate the model),
• theoretical sampling (collect more data to develop categories),
• and memo writing (conceptual notes).

Memoing is crucial because it captures the reasoning chain that later becomes analysis transparency. In an exam, you can mention that memos help:

• track category development,
• preserve analytic decisions,
• and reduce “theme drift.”

4.6 Handling translation and meaning during analysis

If analysis uses translated transcripts, you need strategies:

• maintain a log of translation decisions,
• keep some excerpts in original language if possible for nuance,
• involve a bilingual researcher or language expert for review,
• and document how idioms were translated.

In South African health research, certain concepts may not translate cleanly. For example, terms related to respect, shame, fear, or spiritual beliefs may require careful handling to preserve nuance.

4.7 Reflexivity during analysis (not only during fieldwork)

Reflexivity should continue during analysis:

• how your initial interpretations change,
• how your position influences what you notice,
• and how you respond when a participant challenges your assumptions.

A reflexive analytic note example:

• “Initially I coded this as ‘lack of knowledge.’ After revisiting the transcript and field notes, the participant emphasised ‘fear of being judged’ and ‘lack of respectful communication.’ I revised coding accordingly.”

This shows interpretive growth—very valued for rigour.

4.8 Trustworthiness criteria: how to demonstrate them convincingly in an exam

Credibility

How to demonstrate:

• prolonged engagement (if relevant),
• member checking (where ethical and feasible),
• triangulation,
• negative case analysis,
• clear documentation of coding and theme development.

Member checking in health research must be done thoughtfully:

• participants may have changed circumstances,
• confidentiality and emotional safety must be respected.

If member checking is not feasible, explain alternative credibility steps.

Transferability

Demonstrate by:

• providing detailed contextual description,
• including participant characteristics,
• describing the setting and boundaries of the study.

Transferability means other researchers can assess whether findings fit their contexts.

Dependability

Demonstrate by:

• audit trail (how you coded and modified),
• consistent use of interview guide,
• documenting changes in sampling or fieldwork.

Confirmability

Demonstrate by:

• reflexive journal,
• audit trail,
• showing how findings are grounded in data excerpts,
• involving peer debriefing or independent code reviews.

4.9 Peer debriefing and inter-coder agreement (when appropriate)

Qualitative studies sometimes involve multiple coders. If RHM411 introduces “coding reliability,” you can discuss:

• calibration sessions,
• codebook development,
• discussion of ambiguous excerpts,
• and resolving differences by returning to the data.

However, strict inter-coder agreement metrics are more common in quantitative or specific qualitative frameworks. In many qualitative courses, the key is transparent coding consensus and justification, not necessarily statistical agreement.

4.10 Building an audit trail: what to write down

An audit trail includes:

• sampling decisions and rationale,
• recruitment changes,
• consent and data handling procedures,
• codebook versions,
• theme revisions,
• and analytic memos.

In exams, if you mention audit trails, ensure your narrative shows you understand:

• what decisions were made,
• when they were made,
• why they were made,
• and how they influenced findings.

4.11 Worked example: from transcript snippet to theme claim

Consider a transcript excerpt (illustrative, but consistent with common health research logic):

• Participant: “I didn’t go back because the nurse asked me loudly, ‘Are you still not taking the pills?’ Everyone heard. I felt small.”
• Codes:
  • “public questioning,”
  • “loss of dignity,”
  • “fear of disclosure,”
  • “communication disrespect.”
• Related codes across interviews might include:
  • “shame after clinic visit,”
  • “avoidance to protect privacy,”
  • “stigma in waiting area.”

Theme synthesis:

• “Fear and avoidance driven by privacy-threatening interactions.”

Evidence use:

• You present short excerpts that show the theme’s meaning.
• You may also include a negative case where someone continued despite discomfort and explain what protected them (e.g., supportive counsellor, private consultation room, strong social support).

This approach demonstrates how qualitative analysis should function: interpretively grounded and systematically developed.

5) Ethics, Reporting, and Methodological Writing for RHM411 (Exam-Ready Outputs)

Qualitative research in health and society carries ethical responsibility and academic communication requirements. In RHM411, you must show competence in ethics, confidentiality, and writing up findings in a way that demonstrates rigour and clarity.

5.1 Ethical frameworks relevant to health research students

In South Africa, ethics approval typically follows research ethics principles consistent with global norms:

• respect for persons,
• beneficence (do no harm),
• justice (fair selection of participants),
• and transparency.

For health research, ethics issues are heightened because topics may include:

• stigma (HIV, TB, mental health),
• reproductive health,
• trauma and violence,
• illness and end-of-life experiences.

A qualitative study should anticipate these ethically sensitive areas in:

• consent materials,
• interview guide wording,
• referral and support pathways,
• and confidentiality plans.

5.2 Risk assessment and mitigation in qualitative fieldwork

Even if qualitative research does not involve medical intervention, it can still present risks.

Common qualitative risks

• Emotional distress when discussing illness experiences.
• Psychological discomfort when recalling trauma.
• Social risk if confidentiality is threatened.
• Practical risk if participation affects employment or caregiving responsibilities.
• Power risks if participants feel compelled due to relationship with clinics.

Mitigation strategies (examples)

• Provide participants with breaks and the option to skip questions.
• Use careful wording (avoid interrogative tones).
• Conduct interviews in private settings.
• Schedule interviews at times that do not harm participant wellbeing.
• Provide contact details for support services if distress arises.

5.3 Confidentiality and anonymisation: detailed practical steps

Confidentiality is more than removing names. You must consider:

• where recordings are stored,
• who can access transcripts,
• whether unique combinations of demographics make participants identifiable,
• and whether stories contain identifying details.

Common anonymisation steps:

• use pseudonyms (e.g., “Participant A” or “Thandi” consistently),
• remove facility names or blur them if necessary (depending on ethics guidance),
• avoid reporting exact dates that could identify participants,
• and generalise small community characteristics carefully.

5.4 Informed consent: what “informed” means in qualitative contexts

Informed consent should address:

• purpose of study,
• voluntary nature,
• procedures (interview length, recording, transcription),
• risks and discomforts,
• benefits (often indirect),
• confidentiality and its limits,
• right to withdraw without penalty,
• and how data will be stored.

In qualitative health research, consent processes should also:

• assess comprehension (confirm understanding),
• offer time for questions,
• and provide consent materials in relevant languages where feasible.

5.5 Ethical interviewing: handling sensitive topics responsibly

Sensitive topics require careful interview management:

• start with less sensitive questions,
• gradually move deeper only if participant comfort allows,
• use empathy without leading responses,
• and recognise participant distress signals.

You should also prepare for disclosures:

• if a participant reports immediate danger or serious harm,
• you must follow institutional ethics guidance about mandatory reporting and referral pathways (depending on local policy and ethics approvals).

In an exam, markers often look for your ability to show:

• you recognise potential disclosure risks,
• you understand the need for ethics-approved response plans.

5.6 Confidentiality in focus groups: additional complexity

Focus group confidentiality is harder because participants interact.

Strategies:

• remind participants not to share others’ stories outside the group,
• choose group composition carefully to reduce identifiability risks,
• use ground rules at the start,
• conduct the group in a private venue,
• and avoid reporting exact quotes with distinctive identifiers.

Still, confidentiality cannot be guaranteed in the same way as individual interviews, and this should be communicated ethically.

5.7 Writing qualitative findings: structure and academic communication

A strong qualitative report typically includes:

• introduction and context,
• methodology (design, sampling, data collection, analysis),
• ethics approval and consent,
• findings (themes with supporting excerpts),
• discussion (interpretation, implications, comparison with literature),
• limitations,
• conclusion.

In RHM411, exam questions may ask you to “write up” a qualitative mini-study. You should show:

• coherence between research question and method,
• and coherence between method and findings.

5.8 Using excerpts: how to present quotes without losing analytic control

Excerpts should:

• illustrate the point of the surrounding claim,
• be representative but not only selective,
• be integrated into your argument,
• and be edited to remove identifying information if required.

A good practice:

• introduce the quote,
• explain what it demonstrates analytically,
• and connect it back to the theme definition.

5.9 Discussion: connecting themes to health and society frameworks

In discussion, you interpret themes in relation to:

• health system organisation,
• social determinants of health,
• stigma and cultural meanings,
• power relations,
• and policy context.

A high-quality discussion also addresses:

• similarities and differences with prior research,
• possible explanations,
• and how findings might inform interventions.

5.10 Limitations: writing honestly without undermining rigour

Qualitative limitations include:

• non-generalizability (not the aim),
• potential researcher influence,
• translation limitations,
• limited diversity in sample,
• challenges with access or participant willingness,
• and possibility of recall bias.

The key is to frame limitations constructively:

• show how you mitigated them (e.g., reflexivity, audit trail, sampling strategy),
• and explain what this means for transferability.

5.11 Methodological writing: exam-ready phrasing for each component

A common exam demand is to describe methods clearly and systematically. Below are exam-friendly templates you can adapt.

Template: methodology statement

• Design: “This qualitative study used a [phenomenological / grounded theory / case study] approach to explore [phenomenon] in [context].”
• Sampling: “Purposive sampling was used to recruit [population], with variation by [key characteristics]. Sampling continued until [saturation / data adequacy].”
• Data collection: “Data were collected through [semi-structured interviews / focus group discussions / observation] using an interview guide addressing [core domains].”
• Analysis: “Data were analysed using [thematic analysis / grounded theory coding], involving [coding steps] and theme development through constant comparison.”
• Trustworthiness: “Credibility was supported by [triangulation, audit trail, negative cases, reflexivity], dependability by [documentation], and confirmability by [reflexive memos/peer review].”
• Ethics: “Ethical approval was obtained, and informed consent procedures ensured voluntary participation and confidentiality.”

Even without exact ethics approval numbers (which would be institution-specific), you can show the correct ethical logic.

5.12 Example: a compact but strong “methods” answer (illustrative)

For a question: “Describe how you would conduct a qualitative study on patient experiences of TB treatment in a public clinic.”

A strong response might include:

• Design: phenomenology or case study (depending on whether you focus on lived experience vs clinic routines).
• Sampling: purposive sampling of patients with varied adherence experiences.
• Data collection: semi-structured interviews in private rooms; optionally document review of treatment information materials.
• Analysis: thematic analysis with inductive coding; reflexive memos; negative case analysis.
• Ethics: confidential participation; option to withdraw; referral support if distress arises.

This demonstrates alignment and methodological discipline.

5.13 Frequently examined qualitative methodology pitfalls (and how to avoid them)

Common pitfalls in student exams:

1. Mismatch between question and method
   • e.g., asking about “barriers” but only doing one superficial descriptive question.
2. No sampling rationale
   • simply stating “we sampled participants” without purpose.
3. No analysis detail
   • listing “themes” without explaining coding and theme development.
4. No rigour/ethics detail
   • ignoring translation, confidentiality, distress management, or trustworthiness steps.
5. Overclaiming generalisability
   • stating results “apply to all South Africans” rather than making transferability arguments.

Avoidance strategy:

• always link each design component explicitly to what it helps you answer.

5.14 Exam-style checklists for readiness

Use these checklists when preparing to answer RHM411 exam questions.

Qualitative study plan checklist

• Research question clearly targets meaning/process in a specific context.
• Chosen design fits the question.
• Sampling is purposive with a rationale and saturation/data adequacy logic.
• Data collection methods fit the design (IDIs/FGDs/observation).
• Interview guide includes experience, meaning, context, and process prompts.
• Recording, transcription, translation, and data security described.
• Analysis method is clear: coding → themes → interpretation.
• Trustworthiness addressed with concrete strategies.
• Ethics: consent, confidentiality, risk mitigation described.
• Findings use excerpts that support analytic claims.

Evidence-based writing checklist

• Each theme is defined and grounded in data.
• Negative cases are considered.
• Claims connect back to the research question.
• Discussion relates to health and society context (not only “what participants said”).
• Limitations are honest and bounded.

Final integration: what “good” looks like in SMU RHM411 qualitative work

A high-scoring RHM411 qualitative method submission demonstrates method coherence. It shows how a qualitative question leads to a design; how a design leads to purposive sampling; how sampling leads to ethically careful data collection; how data collection produces analysable evidence; and how analysis leads to themes that are credible, transparent, and meaningful for health and society concerns.

In South Africa’s health research environment—where language, power dynamics, stigma, and structural barriers shape lived experiences—qualitative rigour is not optional. It is the mechanism through which students transform voices into findings that can inform better understanding, better service design, and better social responses to health challenges.

This guide equips you to answer RHM411 exam questions with structured, exam-ready reasoning and to craft qualitative study plans that meet the expectations of health and social science research.