Mental Health Service Use by Chinese Immigrants with Severe and Persistent Mental Illness
Bibliographic record
Abstract
OBJECTIVE: To investigate whether recent Chinese immigrants in British Columbia diagnosed with severe and persistent mental illness used mental health services at a lower rate than a similar group of nonimmigrants and longer-term immigrants. METHOD: Subjects were selected from linked immigration and health administrative databases. Their health service use records for the years 1992 to 2001 were extracted. Rates and rate ratios of use for severe psychiatric disorders for Chinese immigrants and the comparison group were calculated for 4 types of health services: mental health visits to general practitioners (GPs), visits to psychiatrists, psychiatric hospitalizations, and use of psychiatric medications. Rates and rate ratios of use for any mental health condition were calculated for the above 4 types of services, plus community mental health service and nonmental health visits to GPs. RESULTS: The Chinese immigrants (n = 786) and comparison subjects (n = 3962) having severe and persistent mental illness were identified. For serious mental disorders, Chinese immigrants were more likely to visit psychiatrists (RR = 1.36) but less likely to use the other types of services, with rate ratios ranging from 0.51 to 0.81. Including all mental health conditions, Chinese immigrants were less likely to use all 6 types of services, with rate ratios ranging from 0.41 to 0.90. CONCLUSIONS: Except for psychiatric visits for serious disorders, recent Chinese immigrants diagnosed with severe and persistent mental illness used fewer mental health services than subjects from the comparison group. Seriously ill Chinese immigrants may experience problems with access to mental health services.
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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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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".