What the study analysed
The qualitative study examined how medically transitioned transgender women interpret contemporary media representations of their community, and how those representations bear on identity, belonging, and psychological wellbeing. Eight participants aged 21 to 39 were recruited through purposive, convenience, and snowball sampling.
Interviews were semi-structured, conducted online, and ran roughly 45 minutes each. All were audio-recorded, transcribed verbatim, corrected against the audio, and stripped of identifying information before analysis. The study was approved by the University of Split's Human Research Ethics Committee.
Manual coding first, AI as a consistency check
Coding was conducted manually and inductively through repeated close readings, following a general inductive approach and reflexive theme development. Only then was the initial thematic coding processed through Evidano to support triangulation.
The analysis produced five themes — Authenticity of Identity, Hypervisibility Incongruence, Representational Distancing, Psychological Impact of Media, and Desired Forms of Representation — and the thesis went on to propose a new construct, hypervisibility-induced representational distancing.
How Evidano fit the workflow
A reflexive, researcher-led process, with AI used as a supplementary check.
- 1Interviews transcribed and anonymised
Transcripts were manually reviewed and corrected, and identifying information removed.
- 2Manual inductive coding
Codes were refined and organised into thematic categories through repeated close readings and comparison across accounts.
- 3Initial coding processed through Evidano
A supplementary pass to support analytic triangulation across the dataset.
- 4Outputs reviewed and verified by the authors
Final coding decisions, interpretations, and theme development remained researcher led.
“To support analytic triangulation, initial thematic coding was processed using AIlyze (2023), and all outputs were subsequently reviewed and verified by the authors.”
“All final coding decisions, interpretations, and theme development remained researcher led.”
“AIlyze was used solely as a supplementary analytic tool to enhance the consistency and thoroughness of the coding process rather than to generate or determine the final themes.”
A second pass over sensitive interview data
Solo coding of emotionally rich interviews leaves the researcher's own positionality unchecked, with no second reader to compare against.
A supplementary analytic pass that tests the consistency and thoroughness of manual coding, without taking the interpretation out of the researcher's hands.
The thesis discloses exactly what the tool was and was not used for.
Identifying information was removed before any analysis.
Used to check consistency, not to generate or determine final themes.
About Evidano (previously AILYZE)
Evidano is AI-assisted qualitative data analysis software for interviews, focus groups, open-ended survey responses, and documents. It supports AI-assisted thematic analysis with your own or an AI-suggested codebook, transcription and translation in 100+ languages, clickable quotes and citations, and exportable visual reports. End-to-end encryption, no third-party data sharing, and your data is not used to train AI. From USD 50/month for unlimited analysis.
Run the first pass in days, not weeks
Keep the judgment with you. Let Evidano do the heavy lifting on your interviews, focus groups, open-ended responses, and documents.
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