Increasing Access to Cognitive-Behavioural Therapy (CBT) for the Treatment of Mental Illness in Canada: A Research Framework and Call for Action
Bibliographic record
Abstract
International studies suggest that cognitive-behavioural therapy (CBT) for the treatment of mental disorders results in improved clinical and economic outcomes. In Canada, however, publicly funded CBT is scarce, representing an inequity in service delivery. A research framework to evaluate the Canadian health economic impact of increasing access to CBT is proposed. Canadian data related to the epidemiology of mental disorders, patterns of usual care, CBT effectiveness, resource allocation and costs of care will be required and methodologies should be transparent and outcomes meaningful to Canadian decision-makers. Findings should be delivered by multidisciplinary teams of researchers and health professionals. Barriers to funding reform must be identified and knowledge translation strategies delineated and implemented. Canadian clinical and economic outcomes data are essential for those seeking to provide decision-makers with the evidence they need to evaluate whether CBT represents value for mental health dollars spent.
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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 | 0.031 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.012 | 0.017 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".