An Approach to Providing Timely Mental Health Services to Diverse Youth Populations
Bibliographic record
Abstract
Importance: Accessing mental health care is challenging for youths, especially those facing intersectional disadvantages, but whether enhancing youth services increases reach and timeliness has rarely been investigated. ACCESS Open Minds (ACCESS-OM) transformed services at urban, rural, and Indigenous sites in Canada using 5 principles (early identification, rapid access, appropriate care, no age-based transitions from 11-25 years, and youth and family engagement). Objective: To evaluate whether the number of youths referred (hypothesis 1), offered evaluation appointments within 72 hours of referral (hypothesis 2), and receiving services within 30 days of the first appointment (hypothesis 3) increased over the course of ACCESS-OM's implementation. Design, Setting, and Participants: This cohort study included youths (aged 11-25 years) at 11 sites referred between March 2016 and December 2020. Data were analyzed from April 2022 to April 2024. Exposure: Existing primary and/or community services implemented ACCESS-OM's core components: broad-spectrum mental health services, outreach, youth-friendly walk-in spaces, open systems accepting referrals from multiple sources, and response-time benchmarks (72 hours to evaluation and 30 days to start treatment). Main Outcomes and Measures: Outcomes were the referral rate and the probability of being offered a first evaluation within 72 hours and receiving services within 30 days. Dates of referral and/or help-seeking, first offered appointment, first evaluation, and first services received were recorded. Multilevel negative binomial regression was used for hypothesis 1, and time-to-event analyses followed by multilevel accelerated failure time (AFT) models were used for hypotheses 2 and 3. Results: A total of 7889 youths were referred; 4519 (mean [SD] age, 19.3 [3.4] years; 2440 [54%] cisgender women; 1049 [23.21%] Indigenous; 991 [21.93%] Visible Minority [Arab, Black, Chinese, Filipino, Japanese, Korean, Latin American, South Asian, Southeast Asian, West Asian, other ethnicity, and multiple ethnicities]; and 1525 [49.10%] White) were evaluated before March 2020. Each 6-month progression after implementation was associated with a 10% increase in referral rates (IRR, 1.10; 95% CI, 1.07-1.13). The probability of being offered an initial appointment (χ22 = 20.30; P < .001) and receiving services (χ22 = 4.48; P = .01) after any given delay differed significantly over the 3 years. In adjusted AFT models, each 6-month progression was associated with a 3% decrease in time to offered evaluation (time ratio [TR], 0.97; 95% CI, 0.95-0.99) and first services (TR, 0.97; 95% CI, 0.94-1.00). Moderate to severe mental health problems were associated with longer delays to offered first appointments (TR, 1.14; 95% CI, 1.06-1.24) and services (TR, 1.11; 95% CI, 1.01-1.22). Conclusions and Relevance: As hypothesized, after ACCESS-OM implementation, more youths sought help, and the timeliness of initial response and services improved over time. These findings suggest that core principles, benchmarks, and implementation supports are valuable in organizing youth mental health care. Future efforts should make benefits equitable for those with severe problems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".