THE CANADIAN PSYCHOLOGY ASSOCIATION Executive Summary
Bibliographic record
Abstract
There is extensive evidence demonstrating that psychotherapy can be an efficacious and effective health care service for a wide range of commonly experienced mental health and health conditions. This conclu-sion applies across the lifespan and is based on many hundreds of studies, including both randomized controlled trials and studies examining the impact of evidence-based psychological treatments delivered in typical clinical settings. Psychotherapy works for the treatment of depression. Contrary to popular belief, it works at least as well (if not better) for patients with severe symptoms as it does for those experiencing milder forms of depres-sion. Psychotherapy is as effective as medication in treating depression and is more effective than med-ication in preventing relapse. For some patients, the combination of psychotherapy and medication will be more beneficial than either treatment on its own. Compared to the use of medication alone for the treatment of bipolar disorder, combining psychotherapy with medication leads to patients functioning better and having fewer relapses. Emerging evidence sug-gests that adding psychotherapy to medication results in better treatment adherence, reduced subjective burden of disease, and lower suicide rates. In the treatment of anxiety and related disorders, there is strong evidence to support the use of psychother-
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.619 | 0.410 |
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".