Qualitative analysis of mental health recovery: Thailand

Evidano is an AI-powered qualitative data analysis platform that automates transcription, translation, AI-assisted coding, and secure workflows described in this post. The Thailand study (Inta et al., published July 20, 2026) interviewed 30 people and identified four culturally situated themes that require dialect-sensitive handling. Use bilingual transcription plus a project glossary, participant validation, and AI-assisted inductive coding to preserve cultural nuance while cutting weeks from manual analysis.

• The Thailand study (30 interviews, Apr–Sep 2025) produced four overarching themes, so build a hierarchical codebook and preserve dialect tokens.
• Bilingual transcription with a glossary and member-checking validated culturally grounded themes (e.g., merit/karma, family roles, alcohol-related relapse risk).
• AI-assisted coding speeds cross-segment frequency and co-occurrence reports, but preserve human review for translation and idioms.
• Secure workflows matter for mental health data: anonymise, redact PII, and use platforms that guarantee no third-party model training.

Fast take: Inta et al. (published July 20, 2026) interviewed 30 people (service users, carers, and healthcare professionals) in Chiang Mai to build a culturally situated Recovery Support Model with four themes: conceptions of recovery, attitudes, successful recovery characteristics, and barriers.

• Source: PLOS One
• Why it matters: the study surfaces translation-sensitive themes (Buddhist practices, family roles, alcohol-related relapse risk) that demand careful transcript handling and cross-segment comparison.

The research applied reflexive thematic analysis on transcribed interviews in Thai and Northern Thai, with professional translation to English and review against originals to preserve meaning. The research team triangulated findings with feedback workshops and PPI input to validate culturally grounded themes.

• Key methodological features to emulate: bilingual transcription and translation with a shared glossary, line-by-line coding, NVivo for audit trails, and participant feedback events.
• Analytic priority: preserve dialectal expressions and culturally embedded concepts (karma, merit, family duty) instead of collapsing them into generic codes.

This checklist lists seven steps to replicate the Thailand analysis with AI.

Step 1: Gather audio and consent forms, note dialect preferences and PPI inputs.

Step 2: Transcribe with a custom dictionary (local terms, ritual names) and run PII redaction.

Step 3: Translate with glossary preservation and a reviewer check against originals.

Step 4: Run AI-assisted inductive coding; seed codes from CHIME or INSPIRE if desired.

Step 5: Produce cross-segment frequency tables (SU vs carers vs HCP) and co-occurrence networks.

Step 6: Create touchpoint artifacts and short quote bundles for feedback workshops.

Step 7: Iterate codes with participants (member-checking) and export visuals for policy briefs.

If you are planning a qualitative analysis of mental health recovery, especially in multilingual or culturally specific settings like the Thailand study, combine careful transcription and translation with participant validation plus AI-assisted coding and cross-segment analytics to cut weeks of manual work.

Quick trial: upload a small set of transcripts, import a glossary, run an AI-assisted code sweep, and generate cross-segment frequency tables for your next feedback workshop.

Start here: Try Evidano for free.