A participatory arts program to support the well-being and psychosocial adjustment of adolescents and young adults living with mental health issues: investigating factors associated with differential change following participation
Bibliographic record
Abstract
Abstract Growing evidence suggests that participatory arts programs (PAPs) may represent acceptable and promising avenues to help limit the impacts of mental disorders on the psychosocial functioning and developmental trajectories of young people. In this naturalistic evaluation study, we measured the subjective well-being, global self-esteem, and perceived social functioning of 171 adolescents and young adults before and after their participation in a PAP especially developed to foster their psychosocial adjustment and well-being. We assessed the pre-post-program evolution of these three dimensions and investigated its variation as a function of participants’ demographic and clinical characteristics. Globally, all three psychosocial adjustment dimensions improved significantly from pre- to post-program (p ≤ 0.001). Their evolution did not vary according to the age, gender, or migration status of participants, but did as a function of their geographical setting and severity of functional impairments due to mental health problems. Improvements in self-esteem and social functioning were observed in participants living in rural or semi-rural regions (p < 0.001), but not in the metropolitan area. Youths reporting severe impairments had the greatest improvements in all three dimensions of psychosocial functioning (p < 0.001), followed by those reporting moderate impairments (p < 0.001), and no changes were observed in the low severity sub-group. Results suggest that participatory arts programs can foster the well-being and psychosocial functioning of transition-aged youths with varied mental health issues, while emphasizing the importance to consider participants’ characteristics in evaluation research.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".