Mental Health Services for Individuals with Intellectual Disabilities in Canada: Findings from a National Survey
Bibliographic record
Abstract
Background People with intellectual disabilities are known to have a high prevalence of mental health problems but few studies have considered how such mental health problems are addressed in Canada. The purpose of the present study was to document both the range of mental health services available to individuals with intellectual disabilities across Canada and the perceived service gaps. Material and Methods A 30‐item questionnaire was developed that included questions on mental healthcare services for children, adolescents and adults with intellectual disabilities. This survey was sent to key informants in the 10 Canadian provinces and three territories. Results More than half of the respondents reported that generic mental health providers were poorly equipped to meet the needs of individuals with intellectual disabilities and mental health issues. Certain specialized services (inpatient treatment, emergency room expertise) were reported to exist by less than half of the respondents. Waitlists for specialized services were typically 4 months or longer. Respondents thought that training for staff and professionals was very important. Conclusion Some specialized services for individuals with intellectual disabilities and mental health issues were reported to exist in Canada but the need for more specialized services and further training was identified. Documentation of these service gaps should lead to further efforts in Canada for the improvement in services and developing policy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".