Use of mental health care for nonpsychotic conditions by immigrants in different admission classes and by refugees in Ontario, Canada.
Bibliographic record
Abstract
BACKGROUND: Most Canadian newcomers are admitted in the economic, family, or refugee class, each of which has its own selection criteria and experiences. Evidence has shown various risks for mental health disorders across admission classes, but the respective service-use patterns for people in these classes are unknown. In this study, we compared service use for nonpsychotic mental health disorders by newcomers in various admission classes with that of long-term residents (i.e., Canadian-born persons or immigrants before 1985) in urban Ontario. METHODS: In this population-based matched cross-sectional study, we linked health service databases to the Ontario portion of the Citizenship and Immigration Canada database. Outcomes were mental health visits to primary care physicians, mental health visits to psychiatrists, and emergency department visits or hospital admissions. We measured service use for recent immigrants (those who arrived in Ontario between 2002 and 2007; n = 359 673). We compared service use by immigrants in each admission class during the first 5 years in Canada with use by age- and sex-matched long-term residents. We measured likelihood of access to each service and intensity of use of each service using conditional logistic regression and negative binomial models. RESULTS: Economic and family class newcomers were less likely than long-term residents to use primary mental health care. The use of primary mental health care by female refugees did not differ from that of matched long-term residents, but use of such care by male refugees was higher (odds ratio 1.14, 95% confidence interval 1.09-1.19). Immigrants in all admission classes were less likely to use psychiatric services and hospital services for mental health care. Exceptions were men in the economic and family classes, whose intensity of hospital visits was similar to that of matched long-term residents. INTERPRETATION: Immigrants in all admission classes generally used less care for nonpsychotic disorders than longterm residents, although male refugees used more primary care. Future research should examine how mental health needs align with service use, particularly for more vulnerable groups such as refugees.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".