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Mental Health of Refugee Children and Youth: Epidemiology, Interventions, and Future Directions

2020· article· en· W2999518331 on OpenAlexaff
Rochelle L. Frounfelker, Diana Miconi, Jordan Farrar, Mohamad Adam Brooks, Cécile Rousseau, Theresa S. Betancourt

Bibliographic record

VenueAnnual Review of Public Health · 2020
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsMcGill University
FundersNational Institute on Minority Health and Health Disparities
KeywordsRefugeeMental healthPsychological interventionEpidemiologyCriminologyPoliticsIntervention (counseling)Political scienceConstructiveExtant taxonPublic relationsSociologyEconomic growthPsychologyMedicinePsychiatryLaw

Abstract

fetched live from OpenAlex

The number of refugee youth worldwide receives international attention and is a top priority in both academic and political agendas. This article adopts a critical eye in summarizing current epidemiological knowledge of refugee youth mental health as well as interventions aimed to prevent or reduce mental health problems among children and adolescents in both high- and low-to-middle-income countries. We highlight current challenges and limitations of extant literature and present potential opportunities and recommendations in refugee child psychiatric epidemiology and mental health services research for moving forward. In light of the mounting xenophobic sentiments we are presently witnessing across societies, we argue that, as a first step, all epidemiological and intervention research should advocate for social justice to guarantee the safety of and respect for the basic human rights of all refugee populations during their journey and resettlement. A constructive dialogue between scholars and policy makers is warranted.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.765
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.095
GPT teacher head0.436
Teacher spread0.342 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations155
Published2020
Admission routes1
Has abstractyes

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