Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. Youth-engaged qualitative analysis is a research approach that trains young people to collaborate on coding, theme development, and interpretation; the primary payoff is improved validity and recruitment for studies with minoritized youth. The PLOS One study by Pham et al. (published July 30, 2026) reports a concrete model and metrics from the Research on Identity Specific Eating Disorder Symptoms (RISES) Project that other teams can replicate. The PLOS One study (Pham et al., 2026) documents recruitment starting 08/04/2024, five transgender and gender-diverse (TGD) youth on a youth advisory board (YAB), and procedures that produced an 83.3% retention rate after one year.
Key Takeaways
The core finding from the PLOS One study is that youth-engaged qualitative analysis can be implemented with TGD youth when teams invest in training, mentorship, flexible scheduling, and compensation, as described in the PLOS One report (Pham et al., 2026).
- The PLOS One study (Pham et al., 2026) recruited a YAB beginning 08/04/2024 and retained 83.3% of members after one year (published July 30, 2026).
- The PLOS One study (Pham et al., 2026) trained five YAB members and reported 100% of those trained completed qualitative-analysis training in 2025–2026.
- The PLOS One study (Pham et al., 2026) reported that YAB members and mentors coded 25 out of 42 transcripts during the project and that each YAB member coded between 2 and 6 transcripts.
- The PLOS One study (Pham et al., 2026) changed compensation from $250 per 6 months to $125 per 3 months in response to participant feedback and also paid $10 per transcript to support retention.
What Happened and How the RISES Team Measured It
This section describes who ran the study, what the youth advisory board did, when recruitment and coding occurred, and how outcomes were measured in the PLOS One study (Pham et al., 2026).
The PLOS One study (Pham et al., 2026) established a five-member youth advisory board (YAB) of transgender, non-binary, and gender-diverse youth recruited beginning 08/04/2024 to advise and participate in qualitative analysis for the RISES project.
The PLOS One study (Pham et al., 2026) screened 12 people, interviewed 8, invited 6 to join the YAB, and worked closely with 5 YAB members throughout the qualitative study.
The PLOS One study (Pham et al., 2026) trained YAB members using a three-part approach: formal online responsible-conduct training, three 45-minute didactic sessions on qualitative methods, and hands-on coding practice paired with mentors.
The PLOS One study (Pham et al., 2026) measured engagement via the Research Engagement Survey Tool (REST), attendance records, number of transcripts coded per YAB member (2–6 each), and retention after one year (83.3%).
The PLOS One study (Pham et al., 2026) reports both procedural shifts and qualitative evidence of support, including YAB member feedback such as "Thank you so much, I am so grateful to have you guys as support! !" quoted from a TGD YAB member in the article.
Findings Snapshot
| Date or Period | Metric | Value | Implication (from PLOS One) |
|---|---|---|---|
| 08/04/2024 (recruitment start) | Screening → Invitation | 12 completed screening, 8 interviewed, 6 invited, 5 engaged | Shows selective recruitment and triage to support YAB mental health (Pham et al., 2026) |
| 2025 (coding period) / through 2026 | Transcripts coded by YAB/mentors | 25 of 42 transcripts coded by YAB members and mentors (21 double-coded → 42 total codings) | Demonstrates feasible contribution to coding workload while maintaining TGD representation (Pham et al., 2026) |
| After 1 year (reported 2026) | YAB retention | 83.3% retained after one year | High retention attributed to flexible scheduling, mentorship, and revised compensation (Pham et al., 2026) |
| Throughout project | Training completion | 100% of YAB members trained in qualitative analysis (of those trained) | Training plus mentor pairing is effective for capacity building (Pham et al., 2026) |
| Compensation policy (mid-project change) | Payment cadence | Changed from $250 per 6 months to $125 per 3 months; $10 per transcript | Frequent, smaller payments improved perceived fairness and retention (Pham et al., 2026) |
Implications for Qualitative Researchers and Youth-Engaged Teams
Teams that aim to replicate youth-engaged qualitative analysis should expect to invest time, mentorship, and flexible compensation, based on the PLOS One study (Pham et al., 2026).
The PLOS One study (Pham et al., 2026) shows a practical mentoring model: pair each youth coder with a trained graduate or medical student, check in weekly, and use a coordinator as a communication liaison to reduce burden on youth.
The PLOS One study (Pham et al., 2026) recommends asynchronous and synchronous options; in practice, the RISES team found YAB members preferred meeting and coding during scheduled meetings rather than heavy asynchronous tasks.
The PLOS One study (Pham et al., 2026) highlights ethical and safety practices: require responsible-conduct training, screen for current distress, secure parental consent when required, and offer pauses if sociopolitical events increase stress for participants.
How Evidano Helps with Youth-Engaged Qualitative Analysis
Problem: Training and consistency of codes across youth and mentors → Solution: Thematic synthesis and shared codebooks
Evidano makes it faster to develop, distribute, and version a shared codebook across mentors and youth coders by supporting hierarchical codes and real-time code updates; teams can export codebooks for training and keep a single source of truth.
Use Evidano's thematic analytics and visualization to show discrepancies and consensus rates across youth/mentor pairs so the PI can triage where additional mentorship is needed.
Learn more about features in the Evidano product documentation: Evidano Features.
Problem: Burden and time tracking for youth coders → Solution: Progress dashboards and flexible assignments
Evidano provides per-coder workload tracking and cross-segment analysis so coordinators can balance coding loads (for example, assign 2–6 transcripts per youth as the PLOS One study did) and avoid overload.
Evidano's analysis makes it simple to report who coded which transcript and to calculate how many transcripts were double-coded, reproducing the PLOS One workflow where 21 transcripts were double coded to yield 42 coder entries.
Problem: Confidential transcription and safety for vulnerable youth → Solution: Secure transcription and redaction
Evidano supports secure speech-to-text with custom dictionaries and PII redaction so teams can safely transcribe interviews for youth-engaged coding while maintaining privacy.
Evidano encrypts project data and does not use customer data to train third-party models; teams can pair this with local IRB requirements and the NIH Good Clinical Practice training noted in the PLOS One protocol.
Problem: Ongoing Q&A and interpretation across many documents → Solution: AI chat and summarization over documents
Evidano's AI chatbot can answer coder questions about code definitions, return exemplar quotes, and generate concise theme summaries for review meetings, reducing the coordinator burden described in the PLOS One study (Pham et al., 2026).
Using AI to surface candidate themes and supporting quotes lets mentors focus on mentorship and ethical oversight rather than repetitive synthesis tasks.
FAQ: youth-engaged qualitative analysis
What is youth-engaged qualitative analysis and why does it matter?
Youth-engaged qualitative analysis trains young people to participate as coders and interpreters in qualitative projects, improving cultural validity and recruitment for youth-focused studies.
The PLOS One study (Pham et al., 2026) reports that partnering with a TGD youth advisory board improved recruitment materials, code definitions, and choice of exemplar quotes, and that the YAB authorship strengthened ownership of findings.
How did the RISES project train youth for coding?
The RISES project combined formal online responsible-conduct training, three 45-minute didactic sessions, and hands-on coding practice paired with mentors to train youth coders (Pham et al., 2026).
The PLOS One study (Pham et al., 2026) reports that 100% of YAB members who were trained completed the qualitative-analysis training and that pairing each youth with a mentor supported asynchronous and synchronous practice.
How much time and compensation should teams plan for youth-engaged coding?
Plan for dedicated coordinator time, weekly mentorship check-ins, and flexible compensation schedules to maintain engagement; the PLOS One study changed payment cadence mid-project to improve retention (Pham et al., 2026).
The PLOS One study (Pham et al., 2026) originally offered $250 per 6 months, then switched to $125 per 3 months and added $10 per transcript, and achieved an 83.3% retention rate after one year.
Can AI tools like Evidano reduce the workload without replacing youth roles?
Yes, AI tools can automate transcription, surface preliminary themes, and generate consensus reports while preserving youth decision-making over codes and themes.
The PLOS One study (Pham et al., 2026) emphasizes mentorship and human oversight; Evidano is designed to augment those human roles rather than replace youth or mentor judgment.
Conclusion & Next Steps
The PLOS One study (Pham et al., 2026) shows that youth-engaged qualitative analysis with a TGD youth advisory board is feasible when teams budget for training, mentorship, flexible scheduling, and fair compensation.
The PLOS One study (Pham et al., 2026) provides specific operational numbers: recruitment beginning 08/04/2024, five active YAB members, coding contributions of 25 out of 42 transcripts by youth/mentor pairs, and 83.3% retention after one year.
Teams that want to scale participatory coding can combine the practices described in the PLOS One study (Pham et al., 2026) with AI-enabled workflows to reduce coordinator burden and preserve youth-led interpretation.
If you want to pilot youth-engaged qualitative analysis with secure transcription, versioned codebooks, and AI-assisted synthesis, Try Evidano for free.