Psychosocial stressors contributing to emergency psychiatric service utilization in a sample of ethno-culturally diverse clients with psychosis in Toronto
Bibliographic record
Abstract
BACKGROUND: Understanding the psychosocial stressors of people with psychoses from minority ethnic groups may help in the development of culturally appropriate services. This study aimed to compare psychosocial factors associated with attendance at an emergency department (ED) for six ethnic groups. Preventing crises or supporting people better in the community may decrease hospitalization and improve outcomes. METHOD: A cohort was created by retrospective case note analysis of people of East-Asian, South-Asian, Black-African, Black-Caribbean, White-North American and White-European origin groups attending a specialized psychiatric ED in Toronto with a diagnosis of psychosis between 2009 and 2011. The psychological or social stressors which were linked to the presentation at the ED that were documented by the attending physicians were collected for this study. Logistic regression models were constructed to analyze the odds of presenting with specific stressors. RESULTS: Seven hundred sixty-five clients were included in this study. Forty-four percent of the sample did not have a psychiatrist, and 53% did not have a primary care provider. Social environmental stressors were the most frequent psychosocial stressor across all six groups, followed by issues in the primary support group, occupational and housing stressors. When compared to White-North American clients, East-Asian and White-European origin clients were less likely to present with a housing stressor, while Black-African clients had decreased odds of presenting with primary support group stressor. Having a primary care provider or psychiatrist were predominantly protective factors. CONCLUSION: In Toronto, moving people with chronic mental health conditions out of poverty, increasing the social safety net and improving access to primary care and community based mental health services may decrease many of the stressors which contribute to ED attendance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".