Methodology Guide
Reflexive Thematic Analysis
Braun and Clarke's researcher-centred approach to thematic analysis, and how QualIntel OS supports it with audit trail and AI disclosure.
What is Reflexive Thematic Analysis?
Reflexive Thematic Analysis (RTA) was developed by Virginia Braun and Victoria Clarke (2006, substantially updated 2019–2022). Unlike earlier versions of thematic analysis, RTA positions themes as researcher constructions — active interpretations made by the researcher — rather than objective patterns residing in the data.
RTA foregrounds the researcher's reflexive engagement with data: their theoretical positioning, analytical choices, and the role their subjectivity plays in shaping the analysis. It is compatible with a wide range of epistemological and theoretical frameworks, and is one of the most widely used qualitative methodologies in psychology, health sciences, education, and the social sciences.
Commonly used in: Psychology, health sciences, education, sociology, social work, applied qualitative research
Why rigour documentation matters
Examiners and supervisors reviewing an RTA submission expect transparent documentation of how themes were constructed — not merely reported. This includes evidence of researcher engagement with data at the code level, a rationale for how codes developed and were organised, a reflexivity statement about the researcher's positionality, and — increasingly — clear disclosure of any AI tools used and where the researcher's own judgement was exercised.
How QualIntel OS supports Reflexive Thematic Analysis
- RTA mode adjusts synthesis prompts to foreground researcher interpretation — outputs use language like 'the researcher identified...' rather than 'the data shows...'
- Codebook is researcher-constructed from your research design, not auto-applied: you define, approve, and refine every code before evidence review begins
- Quality checks flag over-reliance on a single participant's voice — a common examiner concern in RTA submissions
- Reflexivity template included in every submission export as a structured starting point for your methods chapter
- Complete audit trail: every code created, renamed, merged, or deleted is timestamped
- Auto-generated AI Disclosure Statement documents exactly where AI surfaced candidate evidence and where you exercised interpretive judgement
Frequently asked questions
Can I use AI tools for Reflexive Thematic Analysis?
Yes, with appropriate transparency. Many universities now permit AI assistance in research provided it is clearly disclosed and the researcher retains interpretive ownership. QualIntel OS is designed for this: AI surfaces candidate evidence (transcript segments that may relate to a code) but you confirm or reject every suggestion. No code or theme is auto-applied. QualIntel OS generates a non-editable AI Disclosure Statement from the audit log documenting this.
What does RTA mode do in QualIntel OS?
RTA mode adjusts the synthesis editor prompts and theme-naming guidance to align with Braun and Clarke's 2019 reflexive framework. It prompts you to articulate your analytical rationale for each theme, foregrounds researcher interpretation in drafted text, and includes the reflexivity template in your submission export. Quality checks are calibrated for RTA's epistemological orientation.
How do I demonstrate methodological rigour in my RTA submission?
Strong RTA rigour documentation typically includes: a complete codebook showing how codes were developed and organised; a reflexivity statement addressing the researcher's positionality; an audit trail demonstrating researcher engagement with data at every step; and an AI Disclosure Statement if AI tools were used. QualIntel OS produces all four as part of its standard submission export at Step 6.