Faster Insights: qualitative analysis of HIV disclosure DAs

Evidano is an AI-powered qualitative data analysis platform that helps teams convert NGT notes and ranking data into adaptation-ready recommendations quickly.

A July 16, 2026 PLOS One NGT study with n = 22 stakeholders in Tbilisi found people living with HIV prioritized a Family disclosure decision aid, while providers favored the digital READY tool.

• Study snapshot: published July 16, 2026 in PLOS One, n = 22 (12 providers; 10 PLWH), recruitment Feb 9–Mar 3, 2026.
• Main contrast: PLWH prioritized one-to-one session-based Family disclosure DA (trust, individualized support); providers prioritized digital formats (READY) for scalability.
• Top adaptation asks to code and operationalize: peer educators, legal/treatment content, confidentiality/medication management, and flexible session sequencing.

This section summarizes the study and its immediate implications for adaptation workflows.

• What happened: On July 16, 2026 Zurashvili et al. published an NGT study that ran separate consensus sessions with 12 HIV providers and 10 people living with HIV, then held a joint meeting to prioritize existing disclosure decision aids for adaptation to Georgia.
• Source: PLOS One.
• Headline result: PLWH prioritized an individual session-based Family disclosure DA; providers prioritized digital formats (READY).
• Why it matters: Stakeholder segmentation changes format preference and highlights adaptation priorities (peer educators, legal content, confidentiality).

This section explains the NGT workflow the study used and how notes and rankings were analyzed.

The study team ran two 60-minute NGT sessions (providers; PLWH) followed by a 40-minute joint meeting, reviewed one-page summaries of nine candidate interventions grouped by format (session-based, paper-based, digital), generated pros and cons, and independently ranked formats and specific interventions within preferred formats; notes were de-identified and analyzed with descriptive content analysis.

• Providers scored digital highest for accessibility and scalability; PLWH scored session-based highest for trust and individualized support.
• Within formats: providers preferred READY (digital); PLWH preferred the Family disclosure DA (individual sessions focused on family disclosure).
• Adaptation priorities included peer delivery, legal guidance, confidentiality/medication management, and options for phased individual to group support.

This section gives a reproducible six-step workflow to take raw notes and rankings to adaptation-ready recommendations using the study as an example.

• 1) Import and de-identify session notes and ranking spreadsheets, and set PII redaction rules.
• 2) Transcribe audio and translate Georgian text using custom dictionaries to preserve legal and clinical terms.
• 3) Auto-extract themes; review and import a codebook (for example, 'format preference', 'trust', 'peer involvement', 'legal info').
• 4) Run cross-segment frequency and co-occurrence analyses comparing providers versus PLWH to surface diverging priorities numerically.
• 5) Create visuals and a ranked recommendations list (for example, prioritize Family disclosure DA; add peer delivery and legal modules).
• 6) Export a stakeholder-ready report and share a clickable quotes pack for adaptation workshops and pilot planning.

This conclusion summarizes the recommended next steps for teams adapting disclosure decision aids and links to study and product resources.

If you are adapting a disclosure decision aid, start by segmenting stakeholders (providers versus PLWH), code for relational and practical adaptation needs, and translate those codes into MVP features (peer delivery, legal content, flexible session sequencing).

• Run a two-week pilot analysis in Evidano to turn raw notes and rankings into an actionable adaptation plan, visit Evidano to get started or request a demo tailored to sensitive-health workflows.
• Original study: PLOS One.
• Get started: Try Evidano for free.