Outcome Evaluation of a Multimodal Suicide Prevention Program Designed Through International Collaboration: Protocol for a Controlled Interrupted Time Series Study
Bibliographic record
Abstract
BACKGROUND: The Coopération Québec-France contre la Dépression et l'Isolement (CQFD-I) initiative represents a collaborative effort between Outaouais, a region in Quebec, and Brest, a metropolitan area in France, to reduce suicide through a multimodal approach. CQFD-I integrates 5 key strategies: a web portal on depression, education of primary care physicians on depression, training for mental health professionals in suicide risk assessment and management, and standardized postcrisis outreach and outpatient monitoring protocols. OBJECTIVE: This paper aims to evaluate the effectiveness of CQFD-I in reducing outcomes related to suicidal behavior, namely suicide mortality, hospitalizations due to suicide attempts, and emergency room visits for suicide attempts, across the implementation sites compared to control areas. METHODS: The evaluation will use a controlled, segmented interrupted time series design, spanning 3 distinct phases: preimplementation (2015 to 2020), implementation (2020 to 2022), and postimplementation (2022 to 2024) phases. The outcomes will be (1) suicide mortality, (2) hospitalizations for suicide attempts, and (3) emergency room visits for suicide attempts. Datasets covering September 2015 to August 2024 will be provided by public health organizations in both jurisdictions, that is, the Institut national de la santé publique du Québec and Santé publique France. In Quebec, control sites will consist of the 14 other health regions with a population of at least 50,000, while in France, control sites will include the 18 metropolitan areas with a status comparable to that of Brest Métropole. The analysis will focus on age- and sex-adjusted monthly rates of the specified outcomes, with an emphasis on changes across the study phases to assess the putative effectiveness of the CQFD-I intervention. We hypothesize that each study outcome will decrease by 20% at implementation sites compared to control sites between the preimplementation and postimplementation phases. RESULTS: This project is funded by the Ministère de la Santé et des Services Sociaux du Québec, with access to data and expertise representing in-kind contributions from Santé publique France and Institut national de la santé publique du Québec. Data collection, led by the first author, will take place in September 2027 to allow for the delay required to confirm suicide deaths in official registers, with analysis planned between 2027 and 2028. CONCLUSIONS: To our knowledge, this study will be the first to document the outcomes of a multimodal suicide prevention program targeting geographically defined areas within 2 countries, not limited to the European Union. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/66976.
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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 | 0.105 | 0.086 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.028 | 0.005 |
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".