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Record W2561525822 · doi:10.15173/m.v1i22.808

A Gap Analysis of Mental Health and Addictions Support Services in Richmond, British Columbia — A Community-Based Research Study

2013· article· en· W2561525822 on OpenAlexaffvenueabout
Shelly Chopra

Bibliographic record

VenueThe Meducator · 2013
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMental healthAddictionPopulation healthCommunity healthTherapeutic communityGerontologyPsychiatryPsychologyEnvironmental healthPublic healthMedicineGeographyPopulationNursing

Abstract

fetched live from OpenAlex

Across Canada, mental health and addictions (MHA) has become an area of concern for health providers: it is estimated that one in five adults is affected by a mental illness or addiction. In line with the provincial Ministries of Health Services and Child and Family Development ten-year plan to address MHA in BC, a community-based MHA service gap analysis was undertaken in the present study in Richmond, BC. The primary objectives of this research project were to identify and validate gaps in MHA support services in Richmond based on the informed perspectives of MHA community service providers. In addition to independent and consumer informants, a total of 22 administrators and frontline workers from 10 Richmond-based organizations were interviewed for the purposes of gap validation. Analysis of key informant responses for recurring themes elucidated four main areas of improvement: navigation of MHA services, continuum of support, personalized support, and outreach. Following a meeting among key informants to discuss the results of the current gap analysis, the expectation was raised of developing a strategic action plan to address gaps in MHA service in Richmond, BC.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.342
GPT teacher head0.498
Teacher spread0.155 · 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

Citations0
Published2013
Admission routes3
Has abstractyes

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