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Record W2563974045 · doi:10.7870/cjcmh-2016-042

Client Outcomes Associated With Interprofessional Care in a Community Mental Health Outpatient Program

2016· article· en· W2563974045 on OpenAlexaffvenueabout
Gregory K. Tippin, K. Amanda Maranzan, Mary Mountain

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2016
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsSt. Joseph's Care GroupLakehead University
Fundersnot available
KeywordsPsychosocialMental healthMedicinePsychopathologyCohortComorbidityPsychiatry

Abstract

fetched live from OpenAlex

Interprofessional care (IPC) represents a high degree of collaboration among health professionals to provide comprehensive treatment to clients. Despite increased uptake of IPC in mental health care, few studies have examined its clinical effectiveness in actual practice. A retrospective cohort study examined the treatment outcomes for 183 outpatients with chronic and comorbid mental health difficulties treated with IPC in a community mental health setting. Multilevel modelling demonstrated that clients reported statistically significant improvement in mental health symptoms and functioning during IPC, relative to a waitlist interval. Furthermore, fewer clients reported clinically significant difficulty with symptoms and functioning over the course of treatment with IPC. Findings suggest that IPC may be an effective treatment in outpatient community mental health settings for Canadian adults presenting with chronic and comorbid psychopathology and affected psychosocial functioning.

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)0.011
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.343

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.450
Teacher spread0.403 · 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

Citations6
Published2016
Admission routes3
Has abstractyes

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