Comparing the Clinical Presentation of First-Episode Psychosis across Different Migrant and Ethnic Minority Groups in Montreal, Quebec
Bibliographic record
Abstract
OBJECTIVE: To explore differences in severity and nature of symptoms of first-episode psychosis (FEP) according to ethnic group and migrant status. METHOD: We administered rating scales to assess positive and negative symptoms, as well as general psychopathology, to 301 consecutive patients presenting with an FEP within a defined catchment area in Montreal, Quebec, classified according to ethnicity and migrant status. Symptom scores of Euro-Canadian patients without a recent history of migration, that is, the reference group (n = 145), were compared with those of African and Afro-Caribbean (n = 39), Asian (n = 27), Central and South American (n = 15), Middle Eastern and North African (n = 24), and European and North American (n = 39) patients. RESULTS: Except for referral source, there were no significant differences between ethnic groups on any demographic variables. The African and Afro-Caribbean group had a higher level of negative symptoms (especially alogia) and general psychopathology scores on the Positive and Negative Syndrome Scale (especially, uncooperativeness, preoccupation, and poor attention), compared with the reference group. Ethnic groups did not differ on the Scale for the Assessment of Positive Symptoms scores. CONCLUSIONS: A comparison of FEP patients from different ethnic groups and native-born Euro-Canadians revealed no significant differences in the nature of positive symptoms at first presentation or in age at onset, suggesting that there was no evidence for the hypothesis that ethnic minorities are misdiagnosed as psychotic. Increased severity of negative symptoms and general psychopathology, specifically among the black ethnic minority group, may have implications for the role of ethnicity for the treatment and outcome of the initial episode of psychotic disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".