Interpretive Reflexive Thematic Analysis

Reflexive thematic analysis already assumes a constructivist epistemology in Braun and Clarke's formulation, so the 'interpretive' label signals an explicit commitment to an interpretivist paradigm — meaning is treated as co-constructed between researcher and participant, not as a fixed property of text. In practice this means the analytic work aims at interpretation of meaning rather than description of content, and the researcher's theoretical perspective is actively drawn upon throughout.

No. Inter-rater reliability (IRR) assumes that codes and themes are objective features of data that different coders should independently agree on. Reflexive thematic analysis rejects this assumption: themes are analyst constructions, not facts in the data, so IRR is conceptually incompatible with the method. Rigour is instead demonstrated through reflexivity, analytic depth, coherence, and transparent documentation of analytic decisions.

There is no prescribed number. Braun and Clarke advise against aiming for a specific count; themes should be as numerous as the research question and dataset require to produce a complete and coherent interpretive account. Typically qualitative studies report between three and seven themes, but this is a norm of convention rather than a methodological rule.

Qualitative data software can assist with organising, storing, and retrieving coded segments, but the interpretive and reflexive work must be done by the researcher. Software does not generate meaning — it manages data. Some analysts prefer to code manually to maintain close engagement with the text; others use software as a practical tool while keeping reflective memos separately. Either approach is acceptable provided the reflexive analytic process is genuinely enacted.

Both are interpretivist and attend to meaning in language, but they differ in focus and method. Interpretive RTA focuses on patterned meanings across a dataset at the level of semantic and latent content, producing themes. Discourse analysis focuses on how language constructs social realities, identities, and power relations, often analysing specific textual features and rhetorical moves in fine-grained detail. RTA produces broader thematic accounts; discourse analysis typically engages in closer, more linguistically detailed reading of smaller data extracts.