A preliminary investigation of wait times for child and adolescent mental health services in Canada.
Bibliographic record
Abstract
OBJECTIVES: THE OBJECTIVES OF THIS STUDY WERE TO: 1) describe wait times at agencies providing child and adolescent mental health services (CAMHS) in Canada; and 2) determine whether agency and waiting list characteristics are associated with wait times for different clinical priority levels. METHOD: A web-based survey was distributed to 379 agencies providing CAMHS in Canada. The survey contained questions about agency characteristics, waiting list characteristics and agency wait times. Pearson's correlations were used to determine the bivariate relationship between agency and waiting list characteristics and wait times. RESULTS: The response rate was 30.6% (n=116). Only 8.6% of agencies reported no waiting lists for their programs or services. Estimated mean wait times for initial assessment decreased with increasing levels of clinical priority. However, the ranges of wait times at each clinical priority level were substantial. In addition, only 31.4% of agencies reported being "mostly" or "always" able to meet the Canadian Psychiatric Association's wait time benchmark for scheduled care for psychiatric services. Wait times were positively correlated with size of the waiting list for those considered at lower clinical priority. CONCLUSIONS: The findings confirm concerns about the prevalence of wait times for CAMHS in Canada, and also note marked variability. Though shorter wait times for higher priority children and youth is appropriate, current practice does not meet proposed standards of care as they relate to wait times. Future research should determine the impact of service reform efforts on reducing wait times for children with differing clinical priority levels.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".