Use of Mental Health Care Services by Canadians With Co-occurring Substance Dependence and Mental Disorders
Bibliographic record
Abstract
OBJECTIVES: This study contributes to knowledge of the processes underlying help seeking by those with mental and substance use disorders by examining relationships among need, service use, and satisfaction with mental health care in a population-based sample. METHODS: Secondary data analyses were performed on responses to the 2002 Canadian Community Health Survey (N=36,984). Diagnostic algorithms classified respondents by past-year diagnostic status, including substance dependence and selected mood and anxiety disorders. Logistic regressions examined associations between diagnostic status and service use, satisfaction, and unmet need for care. RESULTS: Ten percent of Canadians and 39% of Canadians with a mental disorder or substance dependence sought services in the year preceding data collection. Although those with co-occurring substance dependence and mental disorders reported the poorest mental health and were most likely to seek care, the presence of a mental disorder, regardless of co-occurring substance dependence, contributed primarily to help seeking. Among those who sought services, the use of informal sources of care, including self-help groups, was more common among those with substance dependence. Those with co-occurring disorders reported the lowest satisfaction with care and the greatest prevalence of unmet need. CONCLUSIONS: The differential use of services, satisfaction, and unmet need across diagnostic status allowed for speculation on differing levels of disability and stigma in the help-seeking process for different types of disorders. The strong association between co-occurring disorders and unmet need for care, including a large proportion of respondents who stated they preferred to self-manage their symptoms, is particularly troubling and deserves future research attention.
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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 | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".