Qualitative studies

Version 0.2 (draft, to be reviewed by someone who works in the field) · 2026-11-13

For studies of text, talk or observation: interviews, focus groups, documents, online posts, field notes. In a claimset lab, coded material is recorded with the qualitative extension (codes, codings and counts).

Principle

A qualitative conclusion rests on what material was gathered, how it was read and coded, and by whom. Those choices are made before the conclusion, and a reader can judge the conclusion only when they are stated: which approach (themes found in the material, or a frame applied to it), how cases were chosen and when gathering stopped, how codes were developed and checked, and where the researcher stands.

approach

When: any qualitative analysis.
Default: name the approach and follow it as its authors describe: for example reflexive thematic analysis or codebook thematic analysis (Braun and Clarke 2006; Braun and Clarke 2021), or content analysis, whose summative form counts coded material (Hsieh and Shannon 2005). Say whether codes are developed mainly from the material (inductive) or from existing theory or a frame set beforehand (deductive), and where the analysis lies between the two.
Why: quality criteria differ between approaches, even between kinds of thematic analysis; judging one by another's standard misleads (Braun and Clarke 2021).
References: Braun and Clarke 2006; Braun and Clarke 2021; Hsieh and Shannon 2005.

sampling-and-saturation

When: choosing how many and which cases (people, documents, posts).
Default: state how cases are chosen and the rule for stopping, fixed in advance where the design allows (in a claimset lab, in the plan): for example, analyse an initial set of cases, then stop when a stated number of further cases adds no new code (Francis et al. 2010; Guest, Namey and Chen 2020).
Why: "until saturation" without a stated rule cannot be checked (Francis et al. 2010). Empirical studies give typical numbers, but only for given aims and populations: saturation came within 9–17 interviews or 4–8 focus groups in studies of relatively homogeneous populations with narrow aims (Hennink and Kaiser 2022; Guest, Bunce and Johnson 2006), and more are needed for wider ones.
References: Francis et al. 2010; Guest, Namey and Chen 2020; Guest, Bunce and Johnson 2006; Hennink and Kaiser 2022.

second-coder

When: codes are applied by a frame (codebook or content analysis), or counts decide a claim.
Default: have a second coder code a share of the material independently (10–25% of units is usual), report agreement (Krippendorff's alpha, per code where codes can overlap) and how disagreements were resolved (O'Connor and Joffe 2020; Hayes and Krippendorff 2007).
Why: agreement shows that a coding frame can be applied consistently (O'Connor and Joffe 2020). In reflexive thematic analysis, where the researcher's reading is the method, agreement measures do not fit, and the researcher's reflexive engagement is reported instead (Braun and Clarke 2021).
References: Hayes and Krippendorff 2007; O'Connor and Joffe 2020; Braun and Clarke 2021.

counts

When: a claim rests on how often something occurs in coded material.
Default: fix in advance what is counted (the codes, the unit, distinct by what) and the rule that decides the claim (in a claimset lab, the plan's counts); report the denominator.
Why: counts chosen after reading the material describe what the reading found but cannot test it, because the reading chose them; a test is defined before the outcomes are seen (Nosek et al. 2018).
References: Nosek et al. 2018.

reporting

Default: follow COREQ for interviews and focus groups (Tong, Sainsbury and Craig 2007), or SRQR for qualitative research in general, including documents and observation (O'Brien et al. 2014). Both ask for the research team's characteristics and reflexivity.
References: Tong, Sainsbury and Craig 2007; O'Brien et al. 2014.

References

Braun, V., and Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. doi:10.1191/1478088706qp063oa
Braun, V., and Clarke, V. (2021). One size fits all? What counts as quality practice in (reflexive) thematic analysis? Qualitative Research in Psychology, 18(3), 328–352. doi:10.1080/14780887.2020.1769238
Francis, J. J., Johnston, M., Robertson, C., Glidewell, L., Entwistle, V., Eccles, M. P., and Grimshaw, J. M. (2010). What is an adequate sample size? Operationalising data saturation for theory-based interview studies. Psychology and Health, 25(10), 1229–1245. doi:10.1080/08870440903194015
Guest, G., Bunce, A., and Johnson, L. (2006). How many interviews are enough? An experiment with data saturation and variability. Field Methods, 18(1), 59–82. doi:10.1177/1525822X05279903
Guest, G., Namey, E., and Chen, M. (2020). A simple method to assess and report thematic saturation in qualitative research. PLoS ONE, 15(5), e0232076. doi:10.1371/journal.pone.0232076
Hayes, A. F., and Krippendorff, K. (2007). Answering the call for a standard reliability measure for coding data. Communication Methods and Measures, 1(1), 77–89. doi:10.1080/19312450709336664
Hennink, M., and Kaiser, B. N. (2022). Sample sizes for saturation in qualitative research: a systematic review of empirical tests. Social Science and Medicine, 292, 114523. doi:10.1016/j.socscimed.2021.114523
Hsieh, H.-F., and Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277–1288. doi:10.1177/1049732305276687
Nosek, B. A., Ebersole, C. R., DeHaven, A. C., and Mellor, D. T. (2018). The preregistration revolution. Proceedings of the National Academy of Sciences, 115(11), 2600–2606. doi:10.1073/pnas.1708274114
O'Brien, B. C., Harris, I. B., Beckman, T. J., Reed, D. A., and Cook, D. A. (2014). Standards for reporting qualitative research: a synthesis of recommendations. Academic Medicine, 89(9), 1245–1251. doi:10.1097/ACM.0000000000000388
O'Connor, C., and Joffe, H. (2020). Intercoder reliability in qualitative research: debates and practical guidelines. International Journal of Qualitative Methods, 19, 1609406919899220. doi:10.1177/1609406919899220
Tong, A., Sainsbury, P., and Craig, J. (2007). Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. International Journal for Quality in Health Care, 19(6), 349–357. doi:10.1093/intqhc/mzm042

Versions

0.1 (2026-11-13): first draft, for review by someone in the field.
0.2 (2026-11-13): each citation checked against the paper. The stopping rule now cites the papers that propose it (Francis et al. 2010; Guest, Namey and Chen 2020); typical numbers hold only for given aims and populations; the second-coder entry separates what agreement shows from reflexive thematic analysis; content analysis and the counts entry gain references.

From entrylib/study-planning at 104ba1c (2026-11-13), as the installed claimset package carries it. Changes are proposed there, with the references that support them.