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Record W7046594552

Disparities in the mental health of migrant children and youth: an analysis of determinants and unmet need

2025· dissertation· en· W7046594552 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2025
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthPopulationEthnic groupPsychological interventionImmigrationContext (archaeology)Work (physics)
DOInot available

Abstract

fetched live from OpenAlex

Background: Global migration has significantly increased in recent decades, emphasizing the need to understand and address the mental health needs of migrant populations, particularly children and youth who face unique challenges pre-, during-, and post-migration. Despite these challenges, evidence suggests conflicting mental health patterns. Some studies suggest migrant children and youth experience fewer mental health difficulties compared to their non-migrant peers – a pattern often referred to as the “healthy migrant paradox,” while other studies challenge the phenomenon. This thesis examines differences in mental health problems and access to care between migrant and non-migrant children and youth, and identifies social and contextual factors that may mitigate or attenuate group differences. Methods: Three manuscripts address key objectives: (1) a systematic review and meta-analysis of 59 studies quantifying differences in mental health outcomes among migrant and non-migrant children and youth in high-income countries; (2) an analysis of differences in mental health-related service contacts between migrant and non-migrant children and youth, and social and economic factors that account for between group differences using a large, representative sample of children and youth in Ontario, and (3) an investigation into the moderating effect of migrant concentration in schools and the mediating role of school processes (loneliness and belonging at school) in the association between migrant background and mental health symptoms, using advanced epidemiologic methods including structural equation modelling and multilevel moderated mediation models. Results: Overall, the fundamental findings of this body of work are: 1) substantial heterogeneity exists in current evidence, influenced by substantive and study methodological factors; 2) after accounting for mental health symptoms and perceptions of need, migrant children and youth, compared to their non-migrant peers, were significantly less likely to have mental health-related service contacts; 3) adjusting for social and economic factors did not fully account for between group differences in mental health-related service contacts; 4) the concentration of migrants in schools is associated with lower levels of externalizing symptoms for migrant youth when migrant concentration is high, and this effect is mediated by youth feelings of loneliness at school. Conclusions: Together, these papers provide a comprehensive understanding of migrant mental health among children and youth. They underscore evident heterogeneity in mental health outcomes among migrant and non-migrant children and youth, influenced by a number of socio-contextual and economic factors. The findings highlight consistent evidence of mental health service shortfalls for migrant children and youth.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.008
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.245
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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