Trauma, Resilience, and Mental Health in Migrant and Non-Migrant Youth: An International Cross-Sectional Study Across Six Countries
Bibliographic record
Abstract
Resilience is a dynamic process of positive adaptation to significant adversity. While there has been substantial focus on risks and negative outcomes associated with youth migrancy, there is limited evidence of the relationship between the adversity of migration, and resilience, wellbeing, and positive mental health in adolescents. This international study aimed to explore the differences in resilience, wellbeing, and mental health behaviors in migrant and non-migrant adolescents tested across six countries (Australia, New Zealand, UK, China, South Africa, and Canada) with varying levels of trauma exposure. The study was a cross-sectional survey design with a convenience sample of 194 10-17 year old migrants and non-migrants. The migrant sample included both "internal" migrants (change of residence within a country) and "external" migrants (change of residence across national borders) for comparison. Across the sites, migrants reported a higher mean number of traumatic events for the past year than non-migrants, with internal migrants reporting more events than external migrants overall. South African adolescents reported a higher mean number of traumatic events for the past year than all other sites. External migrants reported higher resilience scores yet reduced prosocial behaviors relative to internal migrants and non-migrants, whereas both internal and external migrants reported higher peer problems than non-migrants. When considering the interacting effects of trauma, the presence or absence of trauma did not appear to impact migrant scores in terms of resilience, wellbeing, or conduct problems. In comparison, trauma-exposed non-migrants showed detriments relative to trauma-exposed migrant peers for all of these measures. In conclusion, the survey tool was found to be reliable and acceptable for use in international studies of different samples of adolescent migrants. Overall, migrant adolescents showed greater resilience resources than non-migrants and, although the migrants experienced more traumatic events, the impact of trauma on mental health outcomes was greater in the non-migrants. There is a need for further research with larger prospective sample sizes to investigate how levels of resilience and wellbeing vary over time and across countries, and the ways resilience can be promoted in adolescents exposed to trauma, regardless of migrancy status.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".