Waiting for What? An Inquiry into the Fundamental Questions of How to Fix Adolescent Mental Healthcare
Bibliographic record
Abstract
Improving the effectiveness of mental health and substance abuse care for young Canadians is a complex and pressing issue. Currently, there is a focus on reducing wait times and facilitating "system integration" as proposed solutions to the crisis in mental health care. As resources are being allocated toward pursuing those two solutions, the authors argue that the more fundamental challenge to addressing the crisis in mental health care for Canadian adolescents is to urge treatment providers and agencies to clearly define the goals and mechanisms of treatment while evaluating program impacts in order to generate knowledge about effective approaches to treatment. In essence, the authors suggest asking two fundamental questions: What are we treating? And what works? Drawing from insights gained through the creation of a mental health treatment centre at Pine River Institute and the development of subsequent collaborations with various clinical and research communities, the authors outline the importance of clarifying the goals and mechanisms of mental health treatment and creating better definitions and measures of treatment success as a strong foundation for moving toward decreasing wait times and increasing system integration. More specifically, they suggest that the government's most effective role is to increase system capacity by setting standards for excellence. The government can increase system capacity by requiring accountability through accreditation and outcome evaluation; increasing resources for program evaluation; and encouraging innovation by funding research into potentially effective treatment that can contribute evidence to the field of adolescent mental health and substance abuse treatment.
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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 | 0.035 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.033 | 0.055 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.013 | 0.018 |
| 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".