Substance-related and addictive disorders among adults with intellectual and developmental disabilities (IDD): an Ontario population cohort study
Bibliographic record
Abstract
OBJECTIVES: Describe the prevalence of substance-related and addictive disorders (SRAD) in adults with intellectual and developmental disabilities (IDD) and compare the sociodemographic and clinical characteristics of adults with IDD and SRAD to those with IDD or SRAD only. DESIGN: Population-based cohort study (the Health Care Access Research and Development Disabilities (H-CARDD) cohort). SETTING: All legal residents of Ontario, Canada. PARTICIPANTS: 66 484 adults, aged 18-64, with IDD identified through linked provincial health and disability income benefits administrative data from fiscal year 2009. 96 589 adults, aged 18-64, with SRAD but without IDD drawn from the provincial health administrative data. MAIN OUTCOME MEASURES: Sociodemographic (age group, sex, neighbourhood income quintile, rurality) and clinical (psychiatric and chronic disease diagnoses, morbidity) characteristics. RESULTS: The prevalence of SRAD among adults with IDD was 6.4%, considerably higher than many previous reports and also higher than found for adults without IDD in Ontario (3.5%). Among those with both IDD and SRAD, the rate of psychiatric comorbidity was 78.8%, and the proportion with high or very high overall morbidity was 59.5%. The most common psychiatric comorbidities were anxiety disorders (67.6%), followed by affective (44.6%), psychotic (35.8%) and personality disorders (23.5%). These adults also tended to be younger and more likely to live in the poorest neighbourhoods compared with adults with IDD but no SRAD and adults with SRAD but no IDD. CONCLUSIONS: SRAD is a significant concern for adults with IDD. It is associated with high rates of psychiatric and other comorbidities, indicating that care coordination and system navigation may be important concerns. Attention should be paid to increasing the recognition of SRAD among individuals with IDD by both healthcare and social service providers and to improving staff skills in successfully engaging those with both IDD and SRAD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".