Health System-Level Evaluation of Tele-Mental Health Services Among Children and Adolescents in Ontario, Canada
Bibliographic record
Abstract
Objective To describe the characteristics of children and adolescents receiving tele-mental health services in Ontario, Canada and examine access to a psychiatrist, in-person or via tele-mental health services, following a mental health and addictions (MHA)-related emergency department (ED) visit or hospitalization. Method Using linked health and administrative data, we described two cohorts: (1) children and adolescents (1–18 years) who used a provincial tele-mental health programme from January 1, 2013 to March 31, 2017, comparing their MHA-related service use (outpatient, ED, hospitalization) in the 1 year prior to and the 1 year following initial consultation; (2) children and adolescents with high mental health service needs, defined as those with an incident MHA-related ED visit or hospitalization between January 1, 2013 and December 31, 2016, examining their 1-year follow-up with telemedicine and other health care utilization. Results In the first cohort, 7,216 children and adolescents (mean age 11.8 [±3.8] years) received tele-mental health services. The proportion of MHA-related ED visits [15.1% pre vs. 12.6% post (test statistic 23.57, P < 0.001)] or hospitalizations [10.2% pre vs. 8.7% post (test statistic 11.96, P < 0.001)] declined in the year following tele-mental health consultation, while local psychiatry visits increased [8.4% pre vs. 17.0% post (test statistic 298.69, P < 0.001)]. In the second cohort ( n = 84,033), only 1.5% received tele-mental health services, 40.7% saw a psychiatrist in-person, and 32.5% received no MHA-related outpatient care in follow-up. Conclusions Tele-mental health services were rarely used in Ontario, even among high-needs children and adolescents, despite their association with increased access to care and less need for acute mental health care.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".