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Record W7112834476

Risk and Resilience of Refugee Children Surviving War and Displacement

2021· article· en· W7112834476 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Access to Scholarship at Harvard (DASH) (Harvard University) · 2021
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeMental healthPsychological resilienceDisplacement (psychology)StressorQualitative researchInternally displaced personFeeling
DOInot available

Abstract

fetched live from OpenAlex

Armed conflict and its aftermath cause undeniable harm to the mental health and education of children, posing multiple ongoing threats to their survival and rights. The average length of displacement for a refugee today is over 25 years, meaning that millions of children will carry a “dual burden” of war traumas as well as daily displacement stressors through childhood and beyond. Yet the exact mechanisms through which refugee children’s experiences of different conflict-related adversities influence their mental health and education outcomes remain unclear. This three-paper dissertation draws from methods of psychology, neuroscience, and education and uses a risk and resilience theoretical framework to illuminate these mechanisms. Using both quantitative and qualitative methods and primary and secondary data, I examine layers of refugee children’s socioecological contexts during sensitive periods of early childhood and adolescence (a) to describe how distinct dimensions of war trauma and displacement stress shape their developmental outcomes and (b) to discern how factors such as caregivers, peers, schools, legal status, and others contribute to their risk and/or resilience. Paper 1 studies Syrian adolescent refugees (n=240) displaced to and living in Jordan in 2015. Using an innovative neuropsychology tablet assessment to gauge executive functioning, this quantitative research found that adolescents’ greater feelings of insecurity significantly predicted poor inhibitory control, that PTSD significantly predicted poorer working memory, but cumulative trauma exposures did not predict poorer cognition. Paper 2 studies Syrian, Afghan, Palestinian, and Iraqi primary caregivers (n=50) of refugee infants and toddlers displaced to Lebanon and Greece in 2016-2018. Through interviews, this qualitative study formed a typology of war and displacement adversities and identified four pathways through which caregivers reported connections between such adversities and their compromised mental health and negative parenting behaviors. Paper 3 examines 19 existing studies featuring multinational adolescent unaccompanied refugee minors (URMs) displaced to the United States, Canada, and Europe from 1990-2019. Through integrative metasynthesis, this qualitative study found that the literature describes URMs’ educational resilience primarily as derived from their individual strengths, whereas risk factors were largely identified in their microsystem, exosystem, and macrosystem. The literature shows systemic barriers such as denied legal asylum status, withdrawn mental health services, and discriminatory school bureaucracies to have cascading negative consequences for URMs’ educational pursuit, persistence, and success. Together, my results indicate that risk and resilience are not mutually exclusive for refugee children, that displacement stressors matter in addition to war traumas in shaping developmental outcomes, and that ultimately, prolonged resilience in a context of protracted displacement may hold future risks for children. Findings suggest the need to address risk factors at multiple levels of children’s socioecological environments to improve outcomes for refugee child mental health and education.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.000
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 head0.016
GPT teacher head0.274
Teacher spread0.258 · 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.

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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueDigital Access to Scholarship at Harvard (DASH) (Harvard University)Same topicMigration, Health and TraumaFrench-language works237,207