Pathways to First-Episode Care for Psychosis in African-, Caribbean-, and European-Origin Groups in Ontario
Bibliographic record
Abstract
OBJECTIVE: To compare the pathways to care and duration of untreated psychosis (DUP) for people of Black-African, Black-Caribbean, or White-European origin with first-episode psychosis (FEP). METHODS: We recruited a sample of 171 patients with FEP of Black-African, Black-Caribbean, and White-European origin from hospital- and community-based early intervention services (EIS) in the cities of Toronto and Hamilton. We compared the 3 groups on DUP and key indicators of the pathway to care. RESULTS: We observed differences in pathways to care across the 3 groups. Black-Caribbean participants had an increased odds of referral from an inpatient unit to EIS (OR 3.33; 95% CI 1.46 to 7.60) and a decreased odds of general practitioner involvement on the pathway to care (OR 0.17; 95% CI 0.07 to 0.46), as well as fewer total contacts (exp[β] 0.77; 95% CI 0.60 to 0.99) when compared with White-European participants. Black-African participants had an increased odds of contact with the emergency department at first contact (OR 3.78; 95% CI 1.31 to 10.92). The differences in the DUP between groups were not statistically significant. CONCLUSIONS: Our findings suggest that there are significant differences in the pathways to EIS for psychosis for people of African and Caribbean origin in our Canadian context. It is essential to gain a comprehensive understanding of the pathways that different population groups take to mental health services, and the reasons behind observed differences, to inform the development of equitable services, targeting patients in the critical early stages of psychotic disorder.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".