P143 Projet Jalons: A Provincial Adaptation Of Clinical Practice Guidelines For Depression In Primary Care
Bibliographic record
Abstract
Background The development of a care protocol for major depression in primary care emerged as an extension of a knowledge application programme developed in Quebec (Canada) to improve care for anxiety and depressive disorders in primary care (2012; JALONS: http://www.qualaxia.org/ms/jalons/ ). The main goal of the project was to develop or adapt tools to support primary mental health care providers in their clinical practice. Context The 2005 reform in Quebec’s mental health services aimed at strengthening primary care services, and included the creation of multidisciplinary community-based primary mental healthcare teams. Description of Best Practice We used the ADAPTE method to develop a care protocol for major depression in primary care tailored for the local context, with a consideration of the organisation of health care services in primary care. The work was monitored by an expert committee composed of mental health specialists, general practitioners, health care administrators and decision-makers at regional and provincial levels. The care protocol is based on two clinical practice guidelines: the NICE guideline on the treatment and management of depression in adults (2010) and the CANMAT clinical guidelines for the management of major depressive disorder in adults (2009). Lessons We will share the challenges associated with the adaptation of clinical recommendations and organisational strategies to the local context, and the actual implementation of the care protocol in primary care. We will discuss issues dealing with the applicability and successful uptake of recommendations in local contexts (ex.: availability of resources for guideline adaptation, types of professionals involved, barriers).
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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 | 0.058 | 0.116 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".