Évaluation d’une formation québécoise fondée sur des données probantes pour améliorer le dépistage des troubles du comportement alimentaire
Bibliographic record
Abstract
Une formation pour le dépistage des troubles du comportement alimentaire (TCA) destinée à des intervenant(e)s des services de santé généraux du Québec a été évaluée dans le but de cerner ses effets sur l’utilisation de données probantes dans les pratiques. L’analyse des réponses aux questionnaires complétés par les intervenant(e)s révèle une acquisition de connaissances, des réactions positives envers la formation et une intention d’utiliser les connaissances acquises. Lors d’entretiens semi-structurés postformation (3 mois), les intervenant(e)s rapportent avoir utilisé les connaissances sous diverses formes et ont identifié des facteurs influençant l’adoption des pratiques enseignées. L’importance d’adapter les pratiques au contexte québécois est discutée.
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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 | 0.038 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".