La collaboration interprofessionnelle comme enjeu de la qualité des services en santé mentale : le cas des travailleuses sociales et des médecins psychiatres
Bibliographic record
Abstract
Depuis le premier Plan d’action en santé mentale au Québec (MSSS, 2005), le ministère de la Santé et des Services sociaux privilégie des soins collaboratifs, un modèle de plus en plus souvent adopté dans les provinces canadiennes depuis 2011 (Kates et al., 2023). Bien que la collaboration interprofessionnelle soit reconnue comme un moyen de fournir des soins de qualité (McNeil et al., 2013) et de protéger le bien-être des patients, peu de recherches explorent la dynamique entre le travail social et le traitement médical en santé mentale. Quelles possibilités de collaboration existent entre ces professions? Comment leurs expertises en évaluation, planification et prise de décision partagée peuvent-elles améliorer les résultats et la qualité des soins? Cet article discute des stratégies susceptibles de contribuer à co-construire des territoires partagés entre ces professions. Nous soutenons que pour y parvenir, il est essentiel de remettre en question les rapports de pouvoir entre les groupes professionnels, d’encourager la créativité et de reconnaître les différents savoirs professionnels.
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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 | 0.041 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.025 | 0.014 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".