An examination of substance use trends among adolescents receiving mental health treatment in Ontario
Bibliographic record
Abstract
Introduction: Adolescent substance use continues to pose a significant public health concern due to its well-documented adverse effects on long-term health and well-being. Various risk factors, including mental health concerns (e.g., anxiety, depression), residential instability, prenatal exposure to substances, and various psychosocial concerns (e.g., low self-concept, poor social skills), have been recognized as contributors to adolescent substance use. Given the complex nature of substance use, it is essential to better our understanding of the factors that contribute to it. Methods: The current study aims to explore substance use trends among Ontario adolescents and examine the contexts in which these behaviors emerge. This study uses data from the interRAI Child and Youth Mental Health (ChYMH) assessment instrument, collected from youth receiving mental health services in Ontario between 2012 and 2022. Hierarchical logistic regression analysis was used to identify factors associated with triggering the Substance Use CAP. Results: In our sample, females, and older youth (15-18) were most likely to engage in substance use. Results indicated that residential instability, living alone or in a shelter, and living with a single parent are associated with substance use in adolescents. Furthermore, findings revealed that past or recent trauma, internalizing behavior, and school disengagement increased likelihood of engaging in substance use. Discussion and implications: This research provides researchers and clinicians with important insights into risk factors for substance use among adolescents which can be used to inform care planning and the development of prevention and early intervention efforts.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".