[Implementation Evaluation of the Pare-Chocs Program in High School].
Bibliographic record
Abstract
Despite the important increase in the prevalence of depression during adolescence, a low proportion of adolescent presenting elevated depressive symptoms receive school-based mental health services. Moreover, programs implemented in school settings often suffer of a less rigorous implementation, thus limiting their potential effectiveness. The identification of factors influencing implementation fidelity is essential to improve the quality of services. Guided by a theory-driven evaluation model, we assessed the quality of implementation of the Pare-Chocs program and the factors that affected this quality with the elements of action model of Chen (2005). Participants were 15 professionals that implemented Pare-Chocs with six groups of adolescents exhibiting high depressive symptoms. A mixed-method approach was used to collect quantitative data on implementation fidelity in the six groups and qualitative data on action model components. Our results suggest that adherence, dose and participant responsiveness were high. Time constraints and lack of previous education linked to program theory limited the fidelity of implementation, but training, supervision and program guide enhanced it. These findings confirm that prevention programs disseminated in school settings could be implemented with a high level of fidelity, although some challenge must be considered in treatment planning to contribute to higher program effects. Moreover, fidelity should be systematically evaluated in this setting.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".