This post shows practical steps for researchers and UX/health teams who want to run youth-engaged qualitative analysis and keep projects ethical, rigorous, and sustainable. The primary keyword is youth-engaged qualitative analysis and this post summarizes recruitment, training, coding, retention, and engagement metrics so you can reproduce the approach. The analysis below refracts the methods and numbers from a PLOS ONE study (Pham et al., 2026) so teams can plan budgets, timelines, and mentorship structures.
Key Takeaways
According to the PLOS ONE paper, partnering five transgender and gender-diverse youth as a youth advisory board (YAB) produced a practical, trainable pathway to include youth in qualitative analysis while maintaining retention and coder training PLOS ONE.
- According to PLOS ONE (Pham et al., 2026), the Research on Identity Specific Eating Disorder Symptoms (RISES) project recruited a YAB beginning on 08/04/2024 and reported a one-year YAB retention rate of 83.3% as of July 30, 2026.
- According to PLOS ONE (Pham et al., 2026), five youth served actively on the YAB, all trained in qualitative analysis (100% of those trained), and each YAB member coded between 2 and 6 transcripts during the project.
- According to PLOS ONE (Pham et al., 2026), the team coded 42 transcripts in total, with YAB members and mentors coding 25 of those transcripts (21 transcripts were double-coded resulting in 42 coded files).
- According to PLOS ONE (Pham et al., 2026), the study recruited 21 transgender and gender-diverse youth aged 12–22 for the broader qualitative study in 2025 to explore research participation barriers and promoters.
What happened and how the team measured it
The PLOS ONE paper directly describes who, when, and how the youth-engaged qualitative analysis was carried out: the RISES project formed a five-member transgender and gender-diverse youth advisory board and integrated those youth into all phases of a qualitative study beginning recruitment on 08/04/2024, with the article published on July 30, 2026 PLOS ONE.
According to PLOS ONE (Pham et al., 2026), the team measured engagement by meeting attendance, involvement in qualitative analysis (codebook contribution and number of transcripts coded), and partnership using the Research Engagement Survey Tool (REST).
According to PLOS ONE (Pham et al., 2026), the team required formal training: all YAB members completed the NIH Good Clinical Practice course before coding and participated in three 45-minute didactic sessions plus hands-on coding practice and mentorship.
Direct quotation from the YAB recorded in the PLOS ONE paper: "Thank you so much, I am so grateful to have you guys as support! !" (quoted from a YAB member and reported in Pham et al., 2026).
Findings Snapshot
| Date | Metric | Value | Implication |
|---|---|---|---|
| 08/04/2024 | YAB recruitment start | Recruitment began for TGD youth aged 16–21 | Set a clear recruitment window and eligibility (history of disordered eating via EDE-QS) per PLOS ONE (Pham et al., 2026). |
| 2025 | Qualitative interview sample | 21 TGD youth aged 12–22 interviewed | Plan for a broader participant pool to supply transcripts for YAB coding, per PLOS ONE (Pham et al., 2026). |
| July 30, 2026 | YAB retention | 83.3% retention after one year | Budget for compensation and engagement activities to maintain ~80%+ retention as demonstrated in Pham et al., 2026. |
| 2025-2026 | Coding throughput | 25 of 42 transcripts coded by YAB/mentors (2–6 per YAB member) | Expect variable per-member coding loads; build mentorship and flexibility into timelines per PLOS ONE (Pham et al., 2026). |
| July 30, 2026 | Coder training outcome | 100% of YAB members trained in qualitative analysis (those who completed training) | Allocate formal training (GCP + didactic + practice) to achieve trained-youth coders, per Pham et al., 2026. |
Implications for qualitative researchers and UX teams
Youth-engaged qualitative analysis is feasible with resources: the PLOS ONE study shows that dedicated compensation, mentorship, and flexible scheduling supported sustained youth participation (Pham et al., 2026).
- According to PLOS ONE (Pham et al., 2026), compensate youth frequently and transparently (the RISES team shifted from $250 per 6 months to $125 per 3 months and paid $10 per transcript) to reduce financial barriers and improve retention.
- According to PLOS ONE (Pham et al., 2026), plan mentorship pairs and weekly check-ins so youth can learn coding skills without being overwhelmed; YAB mentors were expected to check in at least once per week.
- According to PLOS ONE (Pham et al., 2026), build in flexible coding loads: each YAB member coded 2–6 transcripts to accommodate exams, jobs, and personal stressors.
How Evidano helps translate these lessons into practice
What is Evidano?
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Evidano supports transcription, team coding, thematic and cross-segment analysis, and AI chat over your documents so teams can scale youth-engaged analysis workflows while maintaining audit trails and data security.
Problem: Training and quality control of youth coders
Solution: Use Evidano to centralize training materials, share annotated example transcripts, and run side-by-side coder comparisons so mentors and youth can see code overlaps and discrepancies in one place.
The PLOS ONE team emphasized mentor-driven, hands-on training and double-coding; Evidano’s codebook versioning and coder agreement dashboards make that reproducible across geographically dispersed YAB members.
Problem: Managing asynchronous communication and workload
Solution: Evidano’s project workspace centralizes transcripts, comments, and feedback so youth can code asynchronously but still receive mentor input without email or fragmented group chats.
The PLOS ONE team moved to encrypted group messaging for safety and used shared documents for asynchronous coding; Evidano complements those practices by keeping data and interactions tied to transcripts and codes.
Problem: Extracting themes, quotes, and metrics for manuscripts
Solution: Evidano automatically extracts exemplary quotes, code frequencies, and cross-segment comparisons that speed Steps 4–6 of reflexive thematic analysis referenced in the PLOS ONE paper (Braun and Clarke, 6-step approach noted in Pham et al., 2026).
Use Evidano’s exportable visualizations to show funders and YAB members how their input changed materials, matching the transparency practices recommended by Pham et al., 2026.
Try features that map to the PLOS ONE lessons
See how the platform supports transcription and secure workflows on the Evidano features page: Evidano features.
Evidano keeps projects encrypted and offers role-based access so youth advisors, mentors, and PIs can have appropriate permissions during training and manuscript preparation; see our security commitments at Evidano data security.
FAQ: youth-engaged qualitative analysis
How long does it take to train youth advisory board members to code qualitatively?
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Answer: Training can be completed in a matter of weeks with structured didactics plus hands-on practice and mentorship.
According to PLOS ONE (Pham et al., 2026), the RISES team used an initial NIH Good Clinical Practice course, three 45-minute didactic sessions, and paired hands-on coding practice; that sequence produced 100% of invited trainees completing qualitative analysis training.
What compensation and supports improve YAB retention?
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Answer: Frequent, predictable compensation plus mentorship and flexible workloads improves retention.
According to PLOS ONE (Pham et al., 2026), the team switched from $250 per 6 months to $125 per 3 months and added $10 per transcript, and achieved an 83.3% retention rate after one year.
Can youth reliably contribute to codebooks and theme development?
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Answer: Yes, youth can contribute meaningfully to codebooks and theme validation when given mentorship and structured steps.
According to PLOS ONE (Pham et al., 2026), four of five YAB members contributed to the codebook and all provided feedback on themes and supporting quotes; one YAB member met authorship criteria and co-authored the paper.
How should teams manage emotional safety when analyzing sensitive topics with youth?
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Answer: Build wellness checks, flexible workloads, and explicit consent processes into every phase of analysis.
According to PLOS ONE (Pham et al., 2026), the team offered pauses during politicized events, checked in about wellbeing, and allowed members to reduce responsibilities; a YAB member commented, "I really, really appreciate it."
Conclusion & Next Steps
Including youth as trained collaborators in qualitative analysis is achievable with clear expectations, compensated time, mentorship, and flexible workflows, as demonstrated by the PLOS ONE study (Pham et al., 2026).
The PLOS ONE team reported specific outcomes you can plan for: recruitment beginning on 08/04/2024, a one-year retention of 83.3%, 100% of trained coders among the YAB, and 25 of 42 transcripts coded with youth involvement (Pham et al., 2026).
If you are building a youth-engaged qualitative pipeline, combine structured training, mentor pairs, and tools that centralize transcripts, codebooks, and agreement metrics.
To try an AI platform built for applied qualitative work, Try Evidano for free.
Topics
- youth-engaged qualitative analysis
- youth advisory board qualitative methods
- participatory qualitative analysis
Keep reading
- Commentary on NewsYouth-Engaged Qualitative Analysis: Lessons from RISESHow the RISES PLOS One study trained transgender youth to conduct qualitative analysis. Practical, evidence-backed lessons and AI-ready workflows for research teams.
- Commentary on NewsYouth-Engaged Qualitative Analysis: Practical MethodsPractical lessons for youth-engaged qualitative analysis from a PLOS ONE study, with actionable steps and AI-enabled tools for research teams. Learn more and try Evidano.
- Commentary on NewsYouth-Engaged Qualitative Analysis: Practical LessonsPractical methods from a PLOS One study on youth-engaged qualitative analysis with transgender youth; actionable steps and AI-enabled tools to scale participatory coding.