The mental health of immigrants and refugees: Canadian evidence from a nationally linked database
Bibliographic record
Abstract
BACKGROUND: Few studies of the healthy immigrant effect (HIE) have examined the mental health outcomes of Canadian-born individuals on a national scale compared with immigrants by admission category. This study fills this gap by examining the self-reported mental health (SRMH) of immigrants by admission category and other immigration dimensions (e.g., source world region and duration since landing) and making comparisons with Canadian-born respondents to a population-based survey. DATA AND METHODS: Based on four cycles (2011 to 2014) of the Canadian Community Health Survey (CCHS) linked to the Longitudinal Immigration Database (IMDB), odds ratios of high (i.e., excellent or very good) SRMH among Canadian-born respondents and IMDB-linked immigrants are compared using logistic regression. Among the IMDB immigrant population, high SRMH was also examined according to the above-mentioned immigration dimensions. Adjusted results were hierarchically controlled for age, sex, social and economic factors, and sense of belonging. RESULTS: Age-sex adjusted results show that immigrants, especially refugees, are less likely than the Canadian-born population to report high mental health levels, but these differences disappeared after full adjustment. The odds of immigrants having high SRMH differed more by source world region and duration since landing. For example, fully adjusted results show support for the HIE, with recent immigrants (interviewed within 10 years of landing) more likely to report high SRMH than either the Canadian-born population or established immigrants. Greater odds of high SRMH among recent immigrants also holds across admission classes and for selected world regions. DISCUSSION: This study provides new evidence on differences in mental health between Canadian-born individuals and immigrants by various characteristics. Results support a deterioration of the HIE in SRMH and identify factors significantly associated with SRMH. This study can also serve as a baseline for further studies on the impact of COVID-19 on immigrants' mental health by immigrant category.
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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".