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Record W4411551470 · doi:10.1371/journal.pone.0323199

Compass—Canada’s first child psychiatry access program: Implementation and lessons learned

2025· article· en· W4411551470 on OpenAlexaffabout
Vivian W. L. Tsang, Michelle CQ Lin, Natalie Huang, Sally Tsoi, Dora Juan Juan Hu, Priya Watson, S. Baer, Roberto B. Sassi

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsBC Children's HospitalMcMaster UniversityUniversity of British Columbia
Fundersnot available
KeywordsCompassChild and adolescent psychiatryMedicinePsychiatryLibrary scienceComputer scienceGeographyCartography

Abstract

fetched live from OpenAlex

BACKGROUND: There is a lack of mental health and substance use providers for youth in BC, particularly in rural and remote areas. To address these gaps, Canada's first child psychiatry access program, BC Children's Hospital Compass Program, was developed in 2018 to support providers across the province in providing evidence-based mental health and substance use care to youth under 25. This article describes the program's first five years and provides an overview of its creation, utilization, and clinical uses. METHODS: Quantitative data collected by the Compass Program from September 2018 through September 2023 were analyzed. Participation and utilization of the service by providers in the province were analyzed and descriptive statistics, including means with standard deviations for quantitative variables have been used to describe demographic and other medical factors related to participants. FINDINGS: A total of 2336 new providers have been enrolled since Compass' inception. Number of clinical calls into Compass remained steady over the five-year period with an average of 1085 individual providers served per year. Service use is highest in Vancouver Coastal Region (27.3%), followed by Northern Health (21.4%), Interior (15.7%), Vancouver Island (14.5%), and Fraser (13.4%), and Yukon (0.3%). General practitioners make up over a third of all encounters (34.6%), followed closely by pediatrician encounters making up 27.5% of total encounters from 2018-2023. These two provider types comprise over 60% of all encounters over the 5-year timespan. Encounters with other provider types were less common, with the third most common encounter being Child and Youth Mental Health (CYMH) clinicians, totalling 8.6% of total encounters. 37.6% of encounters were for male patients and 42.9% for female patients with 6.8% reporting "Other" genders and 12.7% declining to answer. Medication concerns are the most common reason for accessing Compass, regardless of gender. Therapy questions, resource coordination issues, and diagnostic clarification followed in frequency, comprising a similar amount of consults. Compass consultations have the potential to benefit three groups of people: the specific patient being consulted on, the provider requesting the consultation, as well as the provider's colleagues who might benefit from peer consultation. CONCLUSIONS: Capacity building is important given Compass receives calls from rural and remote areas where there are no psychiatrists or child psychiatrists where general practitioners and clinicians regularly work with patients along the entire spectrum of mental health and substance use disorders.

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)0.005
metaresearch head score (Gemma)0.008
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: none
Teacher disagreement score0.053
Threshold uncertainty score0.356

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0050.002
Scholarly communication0.0030.001
Open science0.0040.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.083
GPT teacher head0.366
Teacher spread0.283 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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