Mental health at the intersections: understanding South Asian Muslim youth mental health in Peel Region, Toronto, Canada
Bibliographic record
Abstract
Purpose The purpose of this study was to understand the unique mental health concerns and access barriers experienced by South Asian Muslim youth populations living in the Peel Region of Toronto, Canada. Design/methodology/approach For this qualitative exploratory study, interviews (n = 15) were conducted with mental health professionals, educators and spiritual leaders (n = 11) who work with South Asian Muslim youth living in Peel Region, as well as with South Asian Muslim youth themselves (n = 4, aged 20–23). Interview transcripts were analyzed using reflexive thematic analysis. Findings Four primary themes emerged from the data: challenges and stressors, barriers, facilitators and hope and recovery. South Asian Muslim youth navigate a number of unique stressors related to the domains of culture, religion and family dynamics, as well as the impact of migration. Practical implications The findings stress the necessity of creating culturally safe, multilevel strategies to meet the nuanced challenges and diverse needs of South Asian Muslim youth communities. Originality/value This is one of the few papers to the knowledge that addresses the mental health needs and service access barriers of youth populations at the intersections of South Asian diasporic community belonging and Muslim faith in Canada.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".