S243. RACIAL AND ETHNIC DIFFERENCES IN PATHWAY TO CARE AND BASELINE CHARACTERISTICS IN EARLY INTERVENTION SERVICES FOR PSYCHOSIS IN NEW YORK STATE
Bibliographic record
Abstract
Abstract Background The racial and ethnic background of individuals with psychosis may shape their pathway to early intervention services and clinical presentation at admission. Studies from Europe and Canada demonstrate that black minority patients with first-episode psychosis experience a more adverse and coercive pathway to care. The extent to which these findings can be extrapolated to the US context is unknown. The aims of this study are (1) to compare baseline contextual and clinical characteristics, and (2) to examine care pathways by race and ethnicity among young people with psychosis in early intervention services. Methods This study included individuals with a recent-onset (<2 years) psychosis aged 16 to 30 years enrolled at 19 early intervention programs across New York State. Clinicians collected data on pathway to care, demographic, social and clinical variables at program entry. Level of functioning was assessed using the social, occupational and symptomatic functioning subscales of the MIRECC GAF. Results The sample included 767 individuals with a non-Hispanic white (n=209, 27.2%), non-Hispanic black (277, 36.1%), Hispanic (218, 28.4%), or Asian (63, 8.2%) racial/ethnic background. Compared to non-Hispanic white, minority individuals were more likely to have public or no insurance and, overall, had a lower level of completed education. In terms of pathway to care, a lower proportion of non-Hispanic black (65.7%) and Asian (58.7%) participants had previously used mental health services compared to the non-Hispanic white group (78.0%). In contrast, psychiatric hospital or emergency department admissions in the 90 days prior to program enrollment were more frequent among all minority groups in comparison to the non-Hispanic white group. There were no significant differences by race and ethnicity in the level of symptoms or social functioning at baseline. Discussion Our findings suggest a pattern of mental health service use among minority groups with psychosis characterized by less mental health contacts but more inpatient and emergency care prior to the initiation of early intervention services. This trend could be partly explained by racial and ethnic patterning at the contextual level, including financial barriers to care, less so by racial/ethnic differences in illness severity. Our findings are consistent with evidence demonstrating an overrepresentation of minority individuals, especially African-Americans, in psychiatric emergency services suggesting a gap in unmet mental health need among minority populations in the US.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".