Cost-Effectiveness of Cognitive-Behavioural Therapy for Mental Disorders: Implications for Public Health Care Funding Policy in Canada
Bibliographic record
Abstract
Objective: Publicly funded cognitive-behavioural therapy (CBT) for mental disorders is scarce in Canada, despite proven efficacy and guidelines recommending its use. This paper reviews published data on the economic impact of CBT to inform recommendations for current Canadian mental health care funding policy. Method: We searched the literature for economic analyses of CBT in the treatment of mental disorders. Results: We identified 22 health economic studies involving CBT for mood, anxiety, psychotic, and somatoform disorders. Across health care settings and patient populations, CBT alone or in combination with pharmacotherapy represented acceptable value for health dollars spent, with CBT costs offset by reduced health care use. Conclusions: International evidence suggests CBT is cost-effective. Greater access to CBT would likely improve outcomes and result in cost savings. Future research is warranted to evaluate the economic impact of CBT in Canada. Objectif: La thérapie cognitivo-comportementale (TCC) financée par l'État pour les troubles mentaux est rare au Canada, malgré son efficacité prouvée et les lignes directrices qui la recommandent. Cet article examine les données publiées sur l'effet économique de la TCC afin d'éclairer les recommandations en vue des politiques canadiennes actuelles de financement des soins de santé mentale. Méthode: Dans la documentation, nous avons recherché des analyses économiques de la TCC dans le traitement des troubles mentaux. Résultats: Nous avons repéré 22 études économiques de la santé faisant appel à la TCC des troubles de l'humeur, anxieux, psychotiques et somatoformes. Dans les établissements de santé et parmi les populations de patients, la TCC seule ou combinée avec la pharmacothérapie représentait une valeur acceptable pour les fonds de santé dépensés, car les coûts de la TCC sont compensés par une utilisation réduite des soins de santé. Conclusions: Les données probantes internationales suggèrent que la TCC est rentable. Un meilleur accès à la TCC améliorerait probablement les résultats et se traduirait par des épargnes. Il faut plus de recherche pour évaluer l'effet économique de la TCC au Canada.
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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 | 0.012 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".