Immigrants' outcome after a first‐episode psychosis
Bibliographic record
Abstract
AIM: Immigration is a risk factor for psychosis emergence, and previous studies show that immigrants are less likely to engage in treatment for psychosis. However, the literature on outcome is scant and heterogeneous. This study was designed to compare first-generation (FGI) and second-generation immigrants (SGI) to non-immigrants' symptomatic and functional outcomes 2 years after a first-episode psychosis (FEP). METHODS: A 2-year prospective longitudinal study of 223 FEP patients between 18 and 30 years took place in two early intervention services (EIS) in Montreal, Canada. RESULTS: Forty-two per cent of the sample were immigrants (FGI (n = 56), SGI (n = 38)). Compared with non-immigrants, immigrants had similar symptomatic and functioning profiles at baseline, 1 and 2 years, except that fewer SGI had a history of homelessness and more were living with their families. FGI were less likely to have a substance use disorder but more likely to pursue their studies and to present depressive symptoms. CONCLUSIONS: Even if immigrants are known to be at greater risk of developing psychosis, probably secondary to stress related to immigration, their symptomatic and functional outcomes, once engaged in EIS treatment, are similar to or sometimes better than non-immigrants' outcomes. Because immigrants tend to be less engaged in their follow-up, understanding why they disengage from treatment is crucial to develop better therapeutic approaches to better engage them as EIS treatment can improve their outcomes effectively.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".