Mental Health, Concurrent Disorders, and Health Care Utilization in Homeless Women
Bibliographic record
Abstract
PURPOSE: This study assessed lifetime and current prevalence rates of mental disorders and concurrent mental and substance use disorders in a sample of homeless women. Current suicide risk and recent health service utilization were also examined in order to understand the complex mental health issues of this population and to inform the development of new treatment strategies that better meet their specific needs. METHODS: A cross-sectional survey of 196 adult homeless women in three different Canadian cities was done. Participants were assessed using DSM-IV-based structured clinical interviews. Current diagnoses were compared to available mental health prevalence rates in the Canadian female general population. RESULTS: Current prevalence rates were 63% for any mental disorder, excluding substance use disorders; 17% for depressive episode; 10% for manic episode; 7% for psychotic disorder; 39% for anxiety disorders, 28% for posttraumatic stress disorder; and 19% for obsessive-compulsive disorder; 58% had concurrent substance dependence and mental disorders. Lifetime prevalence rates were notably higher. Current moderate or high suicide risk was found in 22% of the women. Participants used a variety of health services, especially emergency rooms, general practitioners, and walk-in clinics. CONCLUSION: Prevalence rates of mental disorders among homeless participants were substantially higher than among women from the general Canadian population. The percentage of participants with moderate or high suicide risk and concurrent disorders indicates a high severity of mental health symptomatology. Treatment and housing programs need to be accompanied by multidisciplinary, specialized interventions that account for high rates of complex mental health conditions.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".