Need and use of services by persons with co-occurring substance use and mental disorders within a community mental health system
Bibliographic record
Abstract
Persons with co-occurring mental and substance use disorders are known to have high needs. However, no study has simultaneously calculated the ‘fit’ between need and use of services for this population using a standardized methodology across a comprehensive community mental health system. The aim of this study was to compare persons with and without co-occurring disorders in terms of their current and recommended levels of care and their need for, and use of, specific mental health, psychosocial and rehabilitative supports within a provincial community mental health system.Trained clinical staff across 407 programs completed 5051assessments representing 41,051 individuals. Assessments consisted of the Colorado Client Assessment Record and a Support and Service Profile from which co-occurring disorder status and global indices of current and recommended levels of care were derived. Using these data, the mismatch between current and recommended levels of care, and for each of 19 categories of support, were calculated.Without exception, persons with co-occurring disorders, and in particular, those with more severe substance use problems, demonstrated significantly more need and had greater unmet need across a range of service categories. In terms of overall level of care, more than twice as many of the individuals with co-occurring disorders were receiving care at two or more levels below recommended compared to persons without co-occurring disorders. Findings highlight the need for integrated mental health and addictions services to address the needs of persons with co-occurring disorders and reinforce the idea that certain subgroups are particularly vulnerable.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".