Implementing Foundry: A cohort study describing the regional and virtual expansion of a youth integrated service in British Columbia, Canada
Bibliographic record
Abstract
AIM: Integrated youth services (IYS) have been identified as a national priority in response to the youth mental health and substance use (MHSU) crisis in Canada. In British Columbia (BC), an IYS initiative called Foundry expanded to 11 physical centres and launched a virtual service. The aim of the study was to describe the demographics of Foundry clients and patterns of service utilization during this expansion, along with the impact of the COVID-19 pandemic. METHODS: Data were analysed for all youth (ages 12-24) accessing both in-person (April 27th, 2018-March 31st, 2021) and virtual (May 1st, 2020-March 31st, 2021) services. Cohorts containing all clients from before (April 27th, 2018-March 16th, 2020) and during (March 17th, 2020-March 31st, 2021) the COVID-19 pandemic were also examined. RESULTS: A total of 23 749 unique youth accessed Foundry during the study period, with 110 145 services provided. Mean client age was 19.54 years (SD = 3.45) and 62% identified as female. Over 60% of youth scored 'high' or 'very high' for distress and 29% had a self-rated mental health of 'poor', with similar percentages seen for all services and virtual services. These ratings stayed consistent before and during the COVID-19 pandemic. CONCLUSIONS: Foundry has continued to reach the target age group, with a 65% increase in number of clients during the study period compared with the pilot stage. This study highlights lessons learned and next steps to promote youth-centred data capture practices over time within an integrated youth services context.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".