Suicidality in first-generation, second-generation and non-immigrant youth in Canada
Bibliographic record
Abstract
Background: The number of people migrating globally has drastically increased in the last two decades and continues to rise. Although adult migrants are typically in better health than the population they migrate to, the evidence regarding migrant children's health, and especially their mental health, is mixed. Objectives: To assess whether the prevalence of suicidal ideation and suicide attempt differs between first- and second-generation immigrant youth, compared to non-immigrants, and whether other sociodemographic factors moderate any associations. Methods: We analyzed a subsample of youth aged 15-17 years from the 2019 Canadian Health Survey on Children and Youth - a national, representative, cross-sectional survey. We conducted multivariable logistic regression analysis, with past-year suicidal ideation and suicide attempt as outcomes and migrant status as exposure. We also investigated whether sociodemographic factors (including sex, family income, parental divorce) moderated these associations using interaction terms. Results: Second-generation immigrants had almost twice the risk of first-generation immigrants and non-immigrants of having attempted suicide (OR 1.68, 95%CI: 1.07, 2.63). The association between second-generation immigrant status and suicide attempt was stronger among those not from low-income households (OR 2.04, 95%CI: 1.30, 3.21) and those with divorced parents (OR 5.19, 95%CI: 1.41, 19.12). The association between second-generation immigrant status and suicidal ideation was stronger among males (OR 1.78, 95% CI: 1.04, 3.07) and those with divorced parents (OR 4.13, 95%CI 1.40, 12.14). Additionally, some effects among first-generation immigrants varied by time since arrival. Relevance: The healthy immigrant effect with respect to suicidality does not appear to pass from the first-generation to the second-generation. The magnitude of effect among second generation immigrant youth varies according to other sociodemographic factors.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".