Practical Considerations for Engaging Youth With Lived And/or Living Experience of Substance Use as Youth Advisors and Co-Researchers
Bibliographic record
Abstract
Background Although youth participatory action research (YPAR) has been gaining popularity in the context of substance use research over the last decade, few studies report on how to apply these methods effectively with youth. To address this gap, this paper describes how we engaged youth as advisors and research assistants in a qualitative research study, as well as our key learnings and practical considerations for engaging youth with lived and/or living experience of substance use. Methods We applied YPAR methods by partnering with youth from across BC who have lived and/or living experience of substance use to form a project youth advisory that co-designed the research protocol and materials. Three members became youth research assistants to facilitate focus groups and qualitative interviews with other youth with lived/living experience and peer support workers who work with youth, and support with data analysis and the dissemination of research findings. Mid- and end-point surveys were distributed to evaluate and improve our youth engagement methods over the course of the study. Results The positive impact of engaging youth with lived/living experience over the course of the study was reflected by study participant responses to the quality and relevance of the focus group/interview questions and positive experiences with the youth facilitators. Youth partners also described developing new skills in research, group facilitation, leadership, communication, and professionalism. Lessons learned and considerations for engaging youth in substance use research included: an equitable hiring process; proper compensation; communication, transparency, and accountability; safe spaces; flexibility; and youth capacity building. Conclusion This study demonstrates varying ways of engaging youth with lived and/or living experience of substance in research and how youth contributions can improve the relevance, quality, and validity of the research. Lessons learned from this study can be applied by other researchers considering engaging youth with lived/living experience or other marginalized populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.180 | 0.156 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.021 | 0.018 |
| Scholarly communication | 0.015 | 0.019 |
| Open science | 0.006 | 0.026 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".