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Record W2059052308 · doi:10.1136/bmjqs-2013-002293.178

P143 Projet Jalons: A Provincial Adaptation Of Clinical Practice Guidelines For Depression In Primary Care

2013· article· en· W2059052308 on OpenAlexaffabout
Pasquale Roberge, Louise Fournier, Hélène Brouillet

Bibliographic record

VenueBMJ Quality & Safety · 2013
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsInstitut National de Santé Publique du QuébecUniversité de MontréalUniversité de Sherbrooke
Fundersnot available
KeywordsMedicinePrimary careAdaptation (eye)Depression (economics)Clinical PracticeFamily medicineNursingPsychology

Abstract

fetched live from OpenAlex

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).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.517
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.371
GPT teacher head0.619
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2013
Admission routes2
Has abstractyes

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