RESEARCH ARTICLE The State of Inpatient Psychiatry for Youth in Ontario: Results of the ONCAIPS Benchmarking Survey
Bibliographic record
Abstract
Objective: Little is known about inpatient psychiatry settings and the services they provide for children and adolescents in Ontario. This paper provides the first broad description of unit characteristics, services provided, and patient characteristics in these settings. Method: Nominated representatives from Ontario hospitals with generic mental health beds (i.e., providing inpatient care across diagnostic groups) for children and adolescents were surveyed regarding data from April 2009 to March 2010. Response rate was 93%. Additional data were extracted from the Ontario Network of Child and Adolescent Inpatient Psychiatry Services (ONCAIPS) Directory and Ministry of Health and Long Term Care (MOHLTC) website. Results: Settings provided primarily crisis services with some planned elective admissions. Higher rates of involuntary admissions, briefer stays, lower interdisciplinary diversity, and lower occupancy were typical of settings with higher proportions of crisis admissions. Services most commonly provided included stabilization, assessment, pharmacotherapy, and mental health education. Bed numbers provincially, beds per staff, and prominence of suicide risk, mood disorders, and utilization of cognitive and behavioural approaches were comparable to trends internationally. Inter-setting disparities were observed in access to inpatient services for different age and diagnostic groups, and availability of psychiatry and different professions. Conclusions: Lack of consistent performance and outcome evaluation, common measures, availability of psychiatry and interdisciplinary supports, and dissimilar treatments provincially, suggest the need
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 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".