Youth-engaged qualitative analysis: lessons for researchers

This post explains practical methods for youth-engaged qualitative analysis and is written for qualitative researchers, UX teams, and program evaluators who want to partner with young people. The primary keyword "youth-engaged qualitative analysis" appears throughout to help teams find concrete, reproducible steps. The PLOS One article by Pham et al. (published July 30, 2026) documents how the Research on Identity Specific Eating Disorder Symptoms (RISES) project trained a five-member transgender and gender-diverse youth advisory board to co-conduct qualitative analysis, and this post refracts those lessons through AI-enabled qualitative research workflows so teams can scale training, coding, and safeguarding.

Key Takeaways

The PLOS One study documents a feasible model for youth-engaged qualitative analysis when teams invest time, mentorship, and compensation, according to PLOS One.

In July 2026, Pham et al. reported a youth advisory board (YAB) of five transgender and gender-diverse (TGD) youth who were trained and participated in analysis, with a one-year retention rate of 83.3% (published July 30, 2026) according to PLOS One.
The RISES project collected qualitative interviews with 21 TGD youth in 2025 and coded 42 transcript passes, of which YAB members and mentors coded 25 transcripts between 2024 and 2025, according to PLOS One.
Pham et al. found that structured mentorship, flexible scheduling, encrypted group messaging, and revised compensation (changed to $125 per 3 months) substantially supported engagement during 2024–2025, according to PLOS One.

What happened: how the RISES study applied youth-engaged qualitative analysis

The PLOS One report describes how the RISES team formed a five-person transgender and gender-diverse youth advisory board (YAB) and trained members to participate in coding and theme review, according to PLOS One (Pham et al., 2026).

According to PLOS One, the RISES team recruited TGD youth starting on 08/04/2024, screened 12 applicants, interviewed 8, invited 6, and worked closely with 5 YAB members aged 16–18 and 18–21 in 2024–2025 (Pham et al., 2026).

The PLOS One article reports that the RISES team used Braun and Clarke’s reflexive thematic analysis framework and that each transcript was double coded where possible, with YAB members coding 2–6 transcripts each and the YAB/mentor pairs coding 25 of 42 transcript passes in total, according to PLOS One.

The PLOS One study documents training that included NIH Good Clinical Practice coursework, three 45-minute didactic sessions, hands-on practice using adapted transcripts, and one-to-one mentorship from graduate or medical students, according to PLOS One.

Findings snapshot

Date	Metric	Value	Implication
08/04/2024	YAB recruitment opened	12 screening surveys, 8 interviews, 6 invitations, 5 active YAB members	Rigorous screening plus a follow-up task reduced early attrition, according to PLOS One
2025	Qualitative sample	21 TGD youth interviews (ages 12–22)	Provides the data corpus used to inform recruitment and codebook development, according to PLOS One
2024–2025	Transcripts coded	25 of 42 transcript passes coded by YAB/mentor pairs	Combining YAB and TGD research team coding kept analysis within a 3-month timeline, according to PLOS One
July 30, 2026	Publication	PLOS One article describing methods and lessons learned	Public reporting enables replication of youth-engaged qualitative analysis methods, according to PLOS One

Implications for qualitative researchers and program teams

Youth-engaged qualitative analysis requires explicit investment in mentorship and flexible timelines, according to PLOS One.

Design your protocol for capacity building: Pham et al. required all YAB members to complete NIH Good Clinical Practice training before coding, which in this study led to 100% of the trained YAB completing their qualitative analysis training by the end of the year, according to PLOS One (published July 30, 2026).
Plan compensation and cadence: the RISES team changed payments to $125 per 3 months after YAB feedback in 2024, which the authors cite as improving retention to 83.3% at one year, according to PLOS One.
Use encrypted group messaging for safety and reminders: Pham et al. moved to Signal for end-to-end encrypted group chat during 2024–2025, which improved attendance and private check-ins, according to PLOS One.

How Evidano helps teams operationalize youth-engaged qualitative analysis

Problem: onboarding, training, and shared codebooks is slow

Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.

Evidano accelerates codebook co-creation by extracting candidate codes from transcripts and producing annotated examples that mentors and youth can review together, reducing the initial coding workload described as heavy by Pham et al. in PLOS One (Pham et al., 2026).

Evidano integrations such as Speech-to-text and secure import pipelines let teams turn recorded YAB practice sessions into searchable transcripts, matching the RISES emphasis on hands-on transcript practice (Pham et al., 2026).

Problem: double coding and discrepancy reconciliation is time consuming

Evidano provides thematic and frequency analysis views and side-by-side coder comparisons so mentors can resolve discrepancies efficiently, addressing the double-coding workload that required PI adjudication in the PLOS One study (Pham et al., 2026).

Evidano supports mentor workflows and documentation so teams can preserve mentorship notes and provide evaluative feedback similar to the mentor summaries used by the RISES team, while keeping participant data encrypted and protected per our data security guidance.

Problem: sustaining engagement and reporting impact

Evidano creates visualizations (code co-occurrence networks and hierarchical code maps) that teams can share with YAB members to demonstrate how their input changed study materials and analyses, supporting the RISES practice of returning final materials to youth for validation (Pham et al., 2026).

Evidano’s AI chat over your documents helps mentors answer questions from YAB members asynchronously and summarize coding tips, reducing the communication burden highlighted by Pham et al. in PLOS One (Pham et al., 2026).

For teams that need to justify budgets and timelines, Evidano’s exportable metrics show per-coder transcript counts and time-to-completion, which aligns with the RISES team’s tracking of 2–6 transcripts per YAB member reported in PLOS One.

FAQ: youth-engaged qualitative analysis

How many youth should be on a youth advisory board for qualitative analysis?

Answer: A small, well-supported board of about five youth can work effectively for coding and feedback, according to PLOS One (Pham et al., 2026).

Supporting detail: The PLOS One study used a five-member YAB recruited in August 2024 and sustained engagement through mentorship and revised compensation, reaching 83.3% retention at one year, according to PLOS One.

How much training is needed before youth can code transcripts reliably?

Answer: Structured coursework plus hands-on practice and one-to-one mentorship is effective for training youth as coders, according to PLOS One (Pham et al., 2026).

Supporting detail: Pham et al. required NIH Good Clinical Practice training, three 45-minute didactic sessions, practice with four training transcripts, and ongoing mentorship, and they report 100% completion of qualitative analysis training for those trained by the end of the year, according to PLOS One.

What logistics improve retention when youth do qualitative analysis?

Answer: Flexible schedules, encrypted group messaging, periodic compensation adjustments, and visible evidence of impact improve retention, according to PLOS One (Pham et al., 2026).

Supporting detail: The RISES team switched group messaging to Signal for privacy, changed payments to $125 every three months after feedback in 2024, and showed youth final materials to reinforce contribution, which the authors link to their 83.3% one-year retention rate, according to PLOS One.

Conclusion & Next Steps

The PLOS One methods paper (Pham et al., published July 30, 2026) demonstrates that youth-engaged qualitative analysis is feasible when teams invest in training, mentorship, communication security, and fair compensation.

Researchers should plan for mentorship bandwidth, flexible timelines, and documentation of per-coder work, as the RISES project coded 25 of 42 transcript passes with YAB involvement during 2024–2025, according to PLOS One.

If your team plans to operationalize youth-engaged analysis, combine incremental training, encrypted group channels, and analysis tooling to reduce overhead; Evidano’s platform supports these steps and integrates transcription and coder comparison tools for teams ready to scale.

To try these workflows yourself, Try Evidano for free.

Topics

youth-engaged qualitative analysis
youth advisory board qualitative
transgender youth participatory research
qualitative coding with youth

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Youth-engaged qualitative analysis: lessons for researchers

Key Takeaways

What happened: how the RISES study applied youth-engaged qualitative analysis

Findings snapshot

Implications for qualitative researchers and program teams

How Evidano helps teams operationalize youth-engaged qualitative analysis

Problem: onboarding, training, and shared codebooks is slow

Problem: double coding and discrepancy reconciliation is time consuming

Problem: sustaining engagement and reporting impact

FAQ: youth-engaged qualitative analysis

How many youth should be on a youth advisory board for qualitative analysis?

How much training is needed before youth can code transcripts reliably?

What logistics improve retention when youth do qualitative analysis?

Conclusion & Next Steps

Topics

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