Longitudinal Reflexive Thematic Analysis
Also known as: longitudinal RTA, repeated-wave thematic analysis, longitudinal qualitative thematic analysis, L-RTA
Longitudinal Reflexive Thematic Analysis (L-RTA) applies Braun and Clarke's reflexive thematic analysis framework to qualitative data collected from the same participants (or context) at two or more time points. Rather than producing a single static account, it tracks how meanings, experiences, and themes evolve, persist, or transform over time, foregrounding the researcher's active reflexive engagement at every stage of the iterative process.
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When to use it
L-RTA is appropriate when the research question is explicitly about change, development, or trajectory in lived experience — for example, how patients adapt to a long-term diagnosis, how professional identity develops during training, or how community meanings shift following a social event. It requires commitment to retaining the same or comparable participants across multiple waves; attrition is a real methodological threat. Choose L-RTA over single-wave RTA when time itself is theoretically meaningful. Do not use it if the research budget, timeline, or population allows only a single data-collection point, or if the phenomenon of interest is inherently static. It is also unsuitable when the analytic goal is theory generation (grounded theory is more appropriate) or causal explanation (which requires quantitative or mixed-methods design).
Strengths & limitations
- Captures processes of change, continuity, and trajectory that cross-sectional methods miss entirely.
- Braun and Clarke's reflexive framework provides a rigorous, transparent analytic scaffold that is adaptable to multiple epistemological positions.
- The built-in reflexivity requirement makes the researcher's evolving influence on data visible and accountable rather than concealed.
- Strengthens theoretical depth by allowing preliminary themes from early waves to be refined or challenged by later data.
- Particularly powerful for health, education, and social science questions where experience unfolds over meaningful timescales.
- Participant attrition across waves can compromise the panel and introduce systematic bias if drop-outs differ from those who remain.
- Substantially greater resource investment than single-wave studies in time, funding, and researcher availability.
- Comparability across waves requires careful protocol design; changes in interview guides or context can confound apparent temporal change.
- The volume of data (multiple waves, multiple participants) makes analysis particularly demanding and time-intensive.
- Does not produce statistical estimates of change rates or causal effects; longitudinal claims remain interpretive and contextual.
Frequently asked
How is this different from just doing thematic analysis twice?
Simply running separate thematic analyses at two time points and then comparing them in a discussion section is not longitudinal RTA. True L-RTA integrates the temporal dimension into the analytic design itself: codes are constructed to be comparable across waves, themes are explicitly interrogated for change or continuity, and the researcher's reflexive documentation spans the entire project. The wave-by-wave data are treated as a single longitudinal dataset, not as independent studies.
How many waves and participants do I need?
A minimum of two waves is required for any longitudinal claim. Three or more waves substantially strengthen temporal conclusions. For participants, standard RTA guidance (typically 6–30 for a small-to-medium study) applies at each wave, but retaining a sufficient sub-sample across all waves is the critical constraint. Attrition of up to 30–40 percent across waves is common in practice; design with expected drop-out in mind.
Do I have to use the same interview questions at each wave?
Consistency in core questions aids comparability, but rigid repetition can make later interviews feel formulaic and reduce depth. A common strategy is a stable core protocol supplemented by wave-specific questions developed from earlier findings. Any deliberate departures from the original protocol should be documented and accounted for in the analytic write-up.
Can I use this with data that were not originally collected longitudinally?
Secondary analysis of archived longitudinal qualitative datasets is possible and sometimes used. However, if the data were collected for a different purpose, the researcher must assess whether the interview content and timing support meaningful temporal analysis. Retrospective accounts from a single interview (asking participants to recall past experiences) are not a substitute for genuine repeated-wave data collection.
How do I handle participants who are lost to follow-up?
Report attrition systematically: how many participants were recruited, how many completed each wave, and any known differences between completers and drop-outs. Analyze whether attrition is random or patterned. If a participant drops out, their data from completed waves are typically retained in the analysis for those waves. Transparent reporting of attrition is a methodological quality standard for longitudinal qualitative research.
Sources
- Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. DOI: 10.1191/1478088706qp063oa ↗
- Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589–597. DOI: 10.1080/2159676X.2019.1628806 ↗
How to cite this page
ScholarGate. (2026, June 3). Longitudinal Reflexive Thematic Analysis. ScholarGate. https://scholargate.app/en/qualitative/longitudinal-reflexive-thematic-analysis
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Interpretive Reflexive Thematic AnalysisQualitative↔ compare
- Longitudinal Content AnalysisQualitative↔ compare
- Longitudinal Narrative ResearchQualitative↔ compare
- Reflexive Thematic AnalysisQualitative↔ compare
- Thematic AnalysisQualitative Research↔ compare