A comparison of patients with intellectual disability receiving specialised and general services in Ontario's psychiatric hospitals
Bibliographic record
Abstract
BACKGROUND: Over the years, the closure of institutions has meant that individuals with intellectual disabilities (IDs) must access mainstream (i.e. general) mental health services. However, concern that general services may not adequately meet the needs of patients with ID and mental illness has led to the development and implementation of more specialised programmes. This study compares patients with ID receiving specialised services to patients with ID receiving general services in Ontario's tertiary mental healthcare system in terms of demographics, symptom profile, strengths and resources and clinical service needs. METHOD: A secondary analysis of Colorado Client Assessment Record data collected from all tertiary psychiatric hospitals in the province was completed for all 371 inpatients with ID, from both specialised and general programmes. RESULTS: Inpatients in specialised programmes were more likely to have a diagnosis of mood disorder and were less likely to have a substance abuse or psychotic disorder. Individuals receiving specialised services had higher ratings of challenging behaviour than those in more general programmes. The two groups did not differ significantly in terms of recommended level of care, although more inpatients from specialised programmes were rated as requiring Level 4 care than inpatients from general programmes. CONCLUSIONS: In Ontario, inpatients in specialised and general programmes have similar overall levels of need but unique clinical profiles that should be taken into consideration when designing interventions for them.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| 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".