The Mental Health of Refugee and Migrant Youth after Settlement: Outcomes of a Multinational Study
Bibliographic record
Abstract
Being of immigrant background is a risk factor for poor mental health among youth. In OECD countries such as Australia, Canada and the United States, both immigration and youth are a policy-focus as these countries are popular destinations for immigrants. The purpose of this study was to investigate the mental health of immigrant youth to better support their acculturation and mental health. This study compared the mental health of immigrant youth in Australia, Canada and the United States, and refugee and migrant youth within each country. It also explored numerous factors that were previously reported to impact the mental health of immigrant youth needing to acculturate to their settlement country. The Strengths and Difficulties Questionnaire, a global mental health screen, was used to evaluate 1063 participants recruited through communities in California, Ontario and South Australia. Twenty-four predictor variables were explored, and multivariable linear regression models accounted for substantial proportions of variance in the mental health of immigrant youth in each country. Perceived discrimination, family functioning and resilience were predictive of the mental health of immigrant youth across Australia, Canada and the United States. Additional predictors differed between each settlement country. Similarities and differences in the findings between Australia, Canada and the United States were discussed, and the study provided specific recommendations for policy and practice related to the needs of immigrant youth in the three settlement countries. This study was a timely contribution to the area of youth mental health, whose purpose was to support the acculturation and mental health of youth in OECD countries where great diversity exists due to immigration.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".