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Record W2162605236 · doi:10.1080/10398560802444044

Shared Mental Health Care for a Marginalized Community in Inner-City Canada

2009· article· en· W2162605236 on OpenAlexaffabout
Pamela Chisholm

Bibliographic record

VenueAustralasian Psychiatry · 2009
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsCapital District Health AuthorityNova Scotia Health AuthorityDalhousie University
Fundersnot available
KeywordsMental healthOutreachNova scotiaNursingCollaborative CareMedicineShared careTelepsychiatryMental health serviceService (business)PopulationHealth carePsychologyFamily medicinePrimary carePsychiatryGeographyEnvironmental healthPolitical scienceBusinessTelemedicine

Abstract

fetched live from OpenAlex

OBJECTIVES: This paper describes the experience and evaluation of a shared care project targeted at marginalized individuals living in the North End of Halifax, Nova Scotia. This population has high rates of psychiatric disorder, often comorbid with chronic medical conditions, and people have difficulty in obtaining the help they need. This primary care liaison service covers all ages and includes outreach to emergency shelters, transitional housing and drop-in centres. Collaborative care improved access, satisfaction and outcomes for marginalized individuals in urban settings. Primary care providers with access to the service reported greater comfort in dealing with mental health problems, and satisfaction with collaborative care, as well as mental health services in general. Results were significantly better than those of control practices when such data were available. The median wait time was 6 days in comparison with 39.5 days for the comparison site. CONCLUSIONS: This model can complement other initiatives to improve the health of marginalized populations, and may be relevant to Australia.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.055
Threshold uncertainty score0.289

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0170.003
Scholarly communication0.0030.001
Open science0.0020.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.368
Teacher spread0.336 · 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

Citations11
Published2009
Admission routes2
Has abstractyes

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