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Record W2258269725 · doi:10.7870/cjcmh-2008-0019

Development and Implementation of a Collaborative Mental Health Care Program in a Primary Care Setting: The Ottawa Share Program

2008· article· en· W2258269725 on OpenAlexaffvenueabout
J. Robert Swenson, Tim Aubry, Katharine Gillis, Colleen MacPhee, Nicholas Busing, Nick Kates, Sarah Pantin, Vivien Runnels

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2008
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsMcMaster UniversityOttawa HospitalHamilton Health SciencesUniversity of Ottawa
Fundersnot available
KeywordsMental healthCollaborative CareMultidisciplinary approachEconomic shortageNursingMedicinePrimary careMental health careFamily medicineService (business)Mental health servicePrimary health careHealth carePsychiatry

Abstract

fetched live from OpenAlex

This article presents the results of a needs assessment of family physicians and residents concerning the provision of mental health care and an implementation evaluation of a multidisciplinary mental health service demonstration project, linking 2 family practices with mental health services of a general hospital. Family physicians and residents reported that collaborative mental health care provision would enhance but not replace their management of patients with mental health problems. The implementation evaluation found that collaborative care provided by a multidisciplinary mental health team co-located with family physicians was accepted by patients and valued by family physicians. Because of a shortage of family physicians, few patients from the mental health system who lacked family physicians were able to gain access to primary care through this project.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.936

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0060.003
Scholarly communication0.0020.001
Open science0.0030.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.052
GPT teacher head0.436
Teacher spread0.384 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations12
Published2008
Admission routes3
Has abstractyes

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