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Record W2180073912 · doi:10.1111/eip.12302

Immigrants' outcome after a first‐episode psychosis

2015· article· en· W2180073912 on OpenAlexaffabout
Amal Abdel‐Baki, Clairélaine Ouellet‐Plamondon, Sofia Medrano, Luc Nicole, Cécile Rousseau

Bibliographic record

VenueEarly Intervention in Psychiatry · 2015
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversité de MontréalMcGill UniversityInstitut Universitaire en Santé Mentale de QuébecCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsImmigrationPsychosisPsychiatryEarly psychosisMedicineIntervention (counseling)PsychologyClinical psychologyPolitical science

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.028
GPT teacher head0.339
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2015
Admission routes2
Has abstractyes

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