Better care through an optimized mental health services continuum (Eastern Townships, Québec, Canada): A systematic and multisource literature review
Bibliographic record
Abstract
INTRODUCTION: In 2014, the health authorities of the Eastern Townships (Québec, Canada) commissioned an evaluation of the mental health admission system for adults (GASMA) to identify the best GASMA organizational or structural elements and optimize the mental health services continuum. METHODS: To develop better services, seven indicators (ie, accessibility to services, integration of levels of services, user satisfaction, guidance and management time, evaluation tools, professional composition, and interprofessional collaboration) were examined through four evaluation questions. A three-step systematic and multisource evaluation was realized. A systematic review of the scientific and gray literature was performed. This evaluation also included key informant opinions to contextualize results from this review. RESULTS: Results from 91 scientific articles, 40 gray literature documents, and 10 interviews highlighted determinants and barriers associated with the examined indicators. From these results, 24 preliminary recommendations were formulated and discussed in a steering committee. These recommendations were then weighted and validated. This served to formulate three final recommendations. CONCLUSION: To optimize the regional mental health services continuum, stakeholders should (1) implement a single-window access for adults with mental health needs, (2) develop alternative services based on users' needs, and (3) test the effectiveness of new methods, initiatives, and tools.
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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 | 0.013 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.020 | 0.026 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".