Mental Health Status, Health Care Utilisation, and Service Satisfaction among Immigrants in Montreal: An Epidemiological Comparison
Bibliographic record
Abstract
OBJECTIVE: To examine variations between immigrants and nonimmigrants in 1) prevalence of common mental disorders and other mental health variables; 2) health service utilisation for emotional problems, mental disorders, and addictions, and 3) health service satisfaction. METHODS: This article is based on a longitudinal cohort study conducted from May 2007 to the present: the Epidemiological Catchment Area Study of Montreal South-West (ZEPSOM). Participants were followed up at 4 time points (T1, n = 2433; T4, n = 1095). Core exposure variables include immigrant status (immigrant vs. nonimmigrant), duration of residence, and region of origin. Key outcome variables included mental health status, health service utilisation, and health service satisfaction. Data were analysed both cross-sectionally and longitudinally. RESULTS: Immigrants had been in Canada for 20 years on average. Immigrants had significantly lower rates of high psychological distress (32.6% vs. 39.1%, P = 0.016), alcohol dependence (1.4% vs. 3.9%, P =0.010), depression (5.2% vs. 9.2%, P = 0.008), and various other mental disorders. They had significantly higher scores of mental well-being (48.9 vs. 47.1 score, P = 0.014) and satisfaction with social (34.0 vs. 33.4 score, P = 0.021) and personal relationships (16.7 vs. 15.6 score, P < 0.001). Immigrants had significantly lower rates of health service utilisation for emotional problems, mental disorders, and addictions and significantly higher rates of health service satisfaction at all time points. Asian and African immigrants had particularly low rates of utilisation and high rates of satisfaction. CONCLUSIONS: Immigrants had better overall mental health than nonimmigrants.
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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 | 0.001 | 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".