Qualitative analysis of recovery in Thailand

The PLOS study in Chiang Mai shows recovery narratives shift from clinical and functional milestones toward personal recovery shaped by family, community, and Buddhist-influenced meanings.

• Sample and timing: n=30 (10 service users, 5 carers, 15 healthcare professionals), interviews conducted Apr–Sep 2025, paper published 20 Jul 2026.
• Methodology: Experience-Based Co-Design experience-gathering combined with reflexive thematic analysis using NVivo v15.
• Core themes: four themes identified, conceptions of recovery, attitudes, characteristics of successful recovery journeys, and barriers to recovery.
• Practical implication: bilingual checks, relational codes (family, religion, stigma), and EBCD touchpoint mapping are essential for culturally valid qualitative work.

The PLOS study found that recovery in Chiang Mai moves from clinical and functional improvement toward personal recovery shaped by family, community, and Buddhist-influenced meanings.

The study by Inta, Grealish & Leamy interviewed 30 participants (10 service users, 5 carers, 15 healthcare professionals) in Chiang Mai between April and September 2025 and identified four themes: conceptions of recovery, attitudes, characteristics of successful recovery journeys, and barriers to recovery.

Read the full paper at PLOS ONE.

The methods section reports that the lead researcher conducted 30 semi-structured interviews which were audio-recorded, transcribed verbatim, and translated from Thai/Northern Thai into English.

The lead researcher (NI) conducted 30 semi-structured interviews (23–70 minutes), audio-recorded, transcribed verbatim and translated from Thai/Northern Thai into English.

Reflexive thematic analysis followed Braun and Clarke’s six-phase approach, and NVivo v15 supported coding and touchpoint identification; two feedback workshops validated preliminary findings with participants.

• Translation and transcription safeguards included a glossary of study-specific terms, translator/transcriber briefings, and transcript checks by the lead researcher.
• Ethics note: the study was approved by King’s College London (HR/DP-24/25–45539) and the Chiang Mai Provincial Public Health Office, and the analysis is research-focused and non-diagnostic.
• Limitations: purposive sample, a small carer subgroup, limited medical staff participation, which are typical trade-offs for deep qualitative work.

The 7-step checklist explains how to go from raw audio to stakeholder-ready insights using AI-enabled tooling.

• 1) Collect and catalog audio and video files and consent forms (input).
• 2) Auto-transcribe in Evidano with a Thai/Northern Thai custom dictionary and enable PII redaction (output: cleaned transcripts).
• 3) Import transcripts and the study’s preliminary codebook (CHIME plus inductive codes) into Evidano.
• 4) Run AI-assisted initial coding and review and refine hierarchical codes into subcodes (output: coded corpus).
• 5) Run thematic frequency and cross-segment analyses (users versus carers versus HCPs) and generate co-occurrence networks.
• 6) Extract verified participant quotes and assemble an evidence pack for feedback workshops (EBCD touchpoints).
• 7) Produce visuals and an executive brief and use Evidano’s AI chat to answer stakeholder questions and iterate.

The PLOS study (published 20 Jul 2026) demonstrates that recovery is culturally situated, with clinical and functional milestones often preceding personal recovery while family, community, and spiritual practices play central roles.

Researchers and teams that need to scale reliable, transparent qualitative analysis of recovery narratives, especially across languages and stakeholder groups, should use an AI research platform that preserves context and privacy.

• Ready to try this on your transcripts? Start a pilot on Evidano at Try Evidano for free and import a small set (5–10 interviews) to test transcription, custom-dictionary translation, coding, and cross-segment visuals.
• Read the original paper at PLOS ONE.