The primary challenge for qualitative teams is translating community engagement into rigorous analysis workflows. According to the PLOS ONE article, youth-engaged qualitative analysis integrates youth as collaborators in coding, theme development, and dissemination to improve relevance and representation. This guide is written for qualitative researchers, community-engaged teams, and UX/research operations leads who want concrete steps, dates, and metrics to reproduce the Research on Identity Specific Eating Disorder Symptoms (RISES) Project’s approach.
Key Takeaways
According to the PLOS ONE article, partnering five transgender and gender-diverse youth as a youth advisory board (YAB) enabled youth to co-develop a codebook, code transcripts, and provide thematic feedback across a one-year project (PLOS ONE).
- Retention: According to the PLOS ONE article, the YAB achieved an 83.3% retention rate after one year (published July 30, 2026).
- Training and contribution: According to the PLOS ONE article, 100% of YAB members who were trained completed qualitative analysis training and each member coded between 2 and 6 transcripts during the project in 2025–2026.
- Sample and scope: According to the PLOS ONE article, the underlying qualitative study interviewed 21 transgender and gender-diverse youth in 2025 and the YAB/mentors together coded 25 of 42 transcripts.
- Practical supports: According to the PLOS ONE article, the team changed compensation to $125 every 3 months in response to YAB feedback and used encrypted group messaging (Signal) to improve meeting attendance and safety.
What happened and how the RISES YAB process worked
Summary answer: According to the PLOS ONE article, the RISES team recruited and trained a five-member transgender and gender-diverse youth advisory board to participate in qualitative analysis across recruitment, coding, theme review, and dissemination.
According to the PLOS ONE article, recruitment began on August 4, 2024 and targeted TGD youth aged 16–21 with a history of disordered eating, using screening via REDCap and the EDE-QS instrument; 12 people completed screening, 8 completed the interview and follow-up task, 6 were invited, and 5 remained active for the year.
According to the PLOS ONE article, the team used Braun and Clarke’s reflexive thematic analysis steps, provided NIH Good Clinical Practice training, ran three 45-minute didactic sessions, paired each youth with a trained mentor, and assigned double coding where feasible.
According to the PLOS ONE article, YAB members coded 2–6 transcripts each and, together with mentors, coded 25 of the total 42 transcripts; the PI resolved discrepancies and the YAB reviewed and confirmed preliminary themes before finalization.
Findings Snapshot
| Date | Metric | Value | Implication |
|---|---|---|---|
| August 4, 2024 | YAB recruitment start | 12 screened, 8 interviewed, 6 invited, 5 active | Screening plus a follow-up task helped select committed YAB members, according to PLOS ONE |
| 2025 | Qualitative interviews | 21 TGD youth interviewed | Provided data for thematic analysis of research participation barriers, according to PLOS ONE |
| 2025–2026 | Transcripts coded by YAB/mentors | 25 of 42 transcripts (double-coded = 21 transcripts yielding 42 coder assignments) | Allocated coding to balance rigor and time, according to PLOS ONE |
| One-year follow-up (published July 30, 2026) | YAB retention | 83.3% retention after one year | High retention attributed to compensation, mentorship, and clear responsibilities, according to PLOS ONE |
| During project | Compensation schedule | Changed from $250/6 months to $125/3 months | More frequent payments improved perceived fairness and engagement, according to PLOS ONE |
Implications for qualitative researchers and UX teams
Direct answer: According to the PLOS ONE article, researchers who want to include youth in analysis should budget for training, mentorship, flexible timelines, and frequent compensation.
According to the PLOS ONE article, training non-research youth requires a mix of formal didactics (NIH Good Clinical Practice and three 45-minute sessions in this study), hands-on practice codings, and one-to-one mentorship to achieve analysis competence.
According to the PLOS ONE article, logistical choices such as encrypted group messaging (Signal), scheduling reminders, and options for synchronous or asynchronous coding materially improved attendance and participation.
According to the PLOS ONE article, assessment and adaptation matter: the RISES team tracked meeting attendance and coding load and adjusted responsibilities so each YAB member coded between 2 and 6 transcripts without burning out.
How Evidano Helps
Problem: Training youth to code qualitative transcripts is time intensive → Solution
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
According to the PLOS ONE article, hands-on practice plus mentorship enabled youth to learn coding: Evidano can accelerate that training by providing auto-generated initial codes and example-coded excerpts to use in training exercises.
Evidano’s thematic and content analysis features reduce the manual burden of creating an initial codebook, which matches the RISES team’s goal of shared codebook development.
Problem: Managing asynchronous coding across mentors and youth → Solution
According to the PLOS ONE article, YAB members used shared Google documents and mentors to coordinate asynchronous work; Evidano supports the same workflow with centralized transcript ingestion and shared coding workspaces.
Evidano’s AI chat over your documents helps mentors review code assignments quickly and standardize definitions before double coding occurs, which aligns with the RISES approach of PI-curated codebook reconciliation.
Problem: Privacy, PII, and safe communication for vulnerable youth → Solution
According to the PLOS ONE article, the research team prioritized encrypted messaging (Signal) and careful consent procedures; Evidano supports secure handling of qualitative data and offers PII redaction in transcription workflows.
For teams that need governance details, see Evidano’s data security information and product features that map to mentorship, transcription, and collaborative coding needs.
FAQ: youth-engaged qualitative analysis
What is youth-engaged qualitative analysis and why use it?
Answer: Youth-engaged qualitative analysis makes young people collaborators in coding and interpretation rather than only participants.
According to the PLOS ONE article, youth-engaged research (YER) integrates lived experience into every study phase to improve validity and representativeness, and was shown in this study to strengthen rigor and professional development for youth authors.
How do you train youth advisory board members to code reliably?
Answer: Combine formal training, hands-on practice, and one-to-one mentorship to build coding skills.
According to the PLOS ONE article, the RISES team used the NIH Good Clinical Practice course, three 45-minute didactic sessions, practice transcripts, and weekly mentor check-ins; each YAB member then coded 2–6 transcripts.
How do you balance rigor with youth workload and wellness?
Answer: Set clear expectations, offer flexible timelines, provide compensation, and monitor burden through regular check-ins.
According to the PLOS ONE article, the RISES team adjusted payment cadence to $125 every 3 months, limited asynchronous load, and paused responsibilities when youth were distressed, which supported an 83.3% retention after one year.
How should a team protect sensitive data when working with minoritized youth?
Answer: Use encryption, consent best practices, and PII redaction in transcripts.
According to the PLOS ONE article, the team required parental consent for members under 18, used Signal for encrypted messaging, and emphasized safety; teams should also consult institutional review boards for approvals.
Conclusion & Next Steps
According to the PLOS ONE article, the RISES project demonstrates that youth-engaged qualitative analysis is feasible with dedicated training, mentorship, flexible timelines, and fair compensation.
According to the PLOS ONE article, the team’s concrete outputs included 5 trained YAB members, 25 transcripts coded by YAB/mentors, and a retention rate of 83.3% after one year (published July 30, 2026).
If your team is planning youth-engaged analysis, start by budgeting for training and mentorship, use secure communication channels, and pilot a small codebook exercise that youth can modify.
Get hands-on with AI-enabled workflows and secure collaboration: Try Evidano for free.