A note on the credibility quality improvement in qualitative research: for housing studies students

A note on the credibility quality improvement in qualitative research: for housing studies students

 

Highlight 5 main ideas of Lincoln and Guba’s trustworthiness framework on how to improve the credibility of qualitative research findings, in the context of doing housing studies dissertation projects. It would be useful to provide an example to illustrate the ideas in terms of research theme of "the preferences of housing needs of the married middle-class generation y citizens in Wanchai, Hong Kong".

Lincoln and Guba’s framework helps a qualitative housing dissertation show that its findings are credible, contextual, traceable, and grounded in participants’ accounts. Their core criteria are credibility, transferability, dependability, and confirmability; some later accounts also add authenticity as a fifth dimension.

Study example

Theme: The preferences and housing needs of married middle-class Generation Y residents in Wan Chai, Hong Kong.

Imagine you conduct semi-structured interviews with 20 married Gen Y residents who live in Wan Chai or are considering moving there. You explore their priorities around flat size, proximity to work, schools, transport, green space, affordability, and neighbourhood identity. The framework below can be presented in your methodology chapter as a quality-assurance plan.

1. Credibility: represent participants accurately

Credibility means the findings plausibly reflect the participants’ actual views rather than a superficial or distorted interpretation. It is the qualitative equivalent of internal validity.

How to improve it in your dissertation:

• Use prolonged engagement: interview participants more than once where feasible, or spend time observing the Wan Chai housing context.
• Apply triangulation: compare interview findings with policy documents, property-market reports, census data, and neighbourhood observations.
• Conduct member checking: send each participant a short summary of your interpretation and ask whether it matches their meaning.
• Use negative-case analysis: deliberately examine residents who do not fit the dominant pattern—for example, married Gen Y residents who prefer a smaller flat in Wan Chai over a larger flat elsewhere.

Example: If most participants say that “walkability to Central” outweighs extra living space, but two say school access matters more because they have young children, do not hide the exception. Report it as a meaningful variation: proximity is dominant for childless couples, whereas school catchment may reshape preferences for families with young children. Member checking can confirm whether your wording captures this distinction.

2. Transferability: describe the context richly

Transferability does not claim that results automatically generalise everywhere. Instead, it gives readers enough contextual detail to judge whether the findings could apply to another setting or population.

How to improve it in your dissertation:

• Provide a thick description of Wan Chai: housing stock, household incomes, commuting patterns, density, school provision, redevelopment pressures, and local amenities.
• Clearly define the sample: married, middle-class, Generation Y residents; their tenure status; household composition; and length of residence.
• State the boundaries of the claim: findings concern Wan Chai, not necessarily all Hong Kong districts or all middle-class young adults.

Example: A finding such as “married Gen Y residents value compact, well-located flats because long commutes reduce family time” should be accompanied by details on Wan Chai’s transport accessibility, housing prices, and participants’ work locations. A reader can then assess whether the same preference might transfer to, say, North Point or Kowloon Tong—but should not assume it does.

3. Dependability: make the process traceable

Dependability concerns the stability, coherence, and transparency of the research process. In qualitative work, this is demonstrated less by repeating a survey and more by documenting decisions so another researcher could follow the route from data to conclusions.

How to improve it in your dissertation:

• Keep an audit trail covering recruitment, interview guides, consent procedures, transcripts, coding schemes, analytic memos, and changes to the research design.
• Explain how the interview guide evolved after pilot interviews.
• Record coding decisions, including why a theme was merged, renamed, or discarded.
• If possible, have a supervisor or peer review a sample of transcripts and coded extracts.

Example: Suppose early interviews suggest “affordability” is the main concern, but later interviews reveal that participants mean not only rent or mortgage payments, but also renovation costs, management fees, and expected family expenses. Your audit trail should show when this broader meaning emerged, which transcript extracts support it, and how the coding framework changed. This makes the evolving interpretation transparent rather than arbitrary.

4. Confirmability: ground claims in evidence

Confirmability asks whether the findings are derived from participants’ data rather than the researcher’s assumptions, values, or preferred narrative. It is the qualitative counterpart of objectivity.

How to improve it in your dissertation:

• Maintain a reflexive journal recording your background, assumptions about housing, and reactions during fieldwork.
• Link every major theme to direct quotations or clearly labelled data extracts.
• Use peer debriefing: discuss emerging interpretations with a supervisor or fellow researcher.
• Distinguish participants’ words from your analytical interpretation.

Example: If you personally believe that married Gen Y residents should prioritise buying property, you must not let that belief shape the analysis. If participants instead emphasise rental flexibility because they expect job mobility, present that view with quotations such as a participant explaining that renting lets them remain close to Wan Chai without committing to a long mortgage. A reflexive journal and data-linked coding can show that the conclusion came from the interviews, not the researcher’s preference.

5. Authenticity: represent voices fairly

In the wider Lincoln and Guba tradition, authenticity addresses whether the research fairly represents participants’ experiences and perspectives, rather than reducing them to a single researcher-driven storyline. It complements the four core trustworthiness criteria.

How to improve it in your dissertation:

• Include diverse voices within the sample: couples with and without children, owners and renters, long-term Wan Chai residents and recent movers.
• Report disagreements and tensions, not only consensus.
• Avoid portraying “middle-class Gen Y” as a uniform group with one housing preference.
• Give participants an opportunity to review how their experiences are represented.

Example: Rather than concluding that “married Gen Y residents in Wan Chai prefer small flats,” present a more faithful account: some prioritise location and lifestyle, others prioritise space for children or home working, and others feel constrained by affordability. Presenting these differences respectfully makes the dissertation more authentic and analytically useful.

Practical dissertation table

Criterion	Main question		Practical action		Wan Chai housing example
Criterion		Main question		Practical action		Wan Chai housing example
Credibility		Do findings reflect participants’ views?		Member checking, triangulation, prolonged engagement		Verify whether “walkability” means access to work, leisure, or both
Transferability		Can readers judge relevance to other contexts?		Thick description of setting and sample		Describe Wan Chai’s density, transport, housing costs, and resident profile
Dependability		Is the research process logical and traceable?		Audit trail, documented coding, peer review		Show how “affordability” was redefined during analysis
Confirmability		Are findings grounded in data, not researcher bias?		Reflexive journal, quotations, peer debriefing		Support the rental-flexibility theme with participant extracts
Authenticity		Are participants’ experiences fairly represented?		Include diverse cases and report tensions		Distinguish childless couples from families with young children

Together, these five ideas would strengthen a dissertation by showing that its account of married middle-class Gen Y housing preferences in Wan Chai is faithful to participants, contextually explained, methodologically transparent, evidence-based, and attentive to differences within the group.

Provide 3 academic references on the topic discussed here, in Harvard reference format.

Here are three suitable academic references in Harvard format for your dissertation’s discussion of Lincoln and Guba’s trustworthiness framework.

1.    Lincoln, Y.S. and Guba, E.G. (1985) Naturalistic inquiry. Beverly Hills, CA: Sage Publications.

2.    Shenton, A.K. (2004) ‘Strategies for ensuring trustworthiness in qualitative research projects’, Education for Information, 22(2), pp. 63–75. doi:10.3233/EFI-2004-22201.

3.    Nowell, L.S., Norris, J.M., White, D.E. and Moules, N.J. (2017) ‘Thematic analysis: striving to meet the trustworthiness criteria’, International Journal of Qualitative Methods, 16(1), pp. 1–13. doi:10.1177/1609406917733847.

How to use them

·        Lincoln and Guba (1985) is the foundational source for credibility, transferability, dependability, and confirmability.

·        Shenton (2004) provides practical strategies for applying those criteria, including member checking, thick description, audit trails, and reflexive practice.

·        Nowell et al. (2017) is especially useful if your dissertation uses thematic analysis to examine housing preferences, because it links the trustworthiness criteria directly to coding, theme development, and interpretation.

For an in-text reference, you could write: “Trustworthiness was addressed through credibility, transferability, dependability, and confirmability (Lincoln and Guba, 1985; Shenton, 2004), with thematic-analysis procedures informed by Nowell et al. (2017).”