Enhancing prevention and intervention for youth concurrent mental health and substance use disorders: The Research and Action for Teens study
Bibliographic record
Abstract
BACKGROUND: Concurrent mental health and substance use disorders among youth are associated with functional impairment in developmentally salient domains, yet research on prevention and intervention for this vulnerable population is sparse. This paper describes the rationale and design of the Research and Action for Teens study, an initiative designed to strengthen the evidence base for prevention, screening, treatment and service delivery for youth concurrent mental health and substance use concerns. METHODS: Four sub-studies were developed: (1) a cohort study examining the emergence of mental health and substance use concerns from early to mid-adolescence; (2) a screening and diagnosis study validating screening tools with a diagnostic interview; (3) a treatment study examining the feasibility and effectiveness of dialectical behaviour therapy skills training interventions for youth and family members; and (4) a systems study implementing cross-sectoral collaborative networks of youth-serving agencies using a common screening tool. RESULTS: Multiple stakeholders, including service providers from youth-serving agencies across sectors, consumer groups and family members participated in an initial consultation, and in the implementation of 4 sub-studies. CONCLUSIONS: Collaboration with community stakeholders across sectors and disciplines throughout the research process is challenging but feasible, and is important for the production of applicable knowledge across the continuum of care.
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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 | 0.025 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| 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".