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“We are all under the same roof”: Coping and meaning-making among older Bhutanese with a refugee life experience

2020· article· en· W3080601148 on OpenAlexafffund
Rochelle L. Frounfelker, Tej Mishra, Srishity Dhesi, Bhuwan Gautam, Narad Adhikari, Theresa S. Betancourt

Bibliographic record

VenueSocial Science & Medicine · 2020
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersNational Institute on Minority Health and Health DisparitiesCanadian Institutes of Health ResearchNational Institute on AgingNational Institutes of HealthMcGill University Health Centre
KeywordsRefugeeCoping (psychology)SociologyGerontologyMeaning (existential)PsychologyPolitical scienceMedicineClinical psychologyPsychotherapist

Abstract

fetched live from OpenAlex

OBJECTIVE: Refugees have elevated risk of psychological distress and mental health disorders compared to the general population. The majority of research has been conducted with youth and younger adults, and little is known about the mental health of older refugees. We apply the theoretical framework of meaning making to understand how older Bhutanese with a refugee life experience cope with migratory traumas and grief. METHOD: We conduct semi-structured individual interviews with 41 ethnic-Nepali Bhutanese aged 50 and over with a refugee life experience resettled in the United States and analyze data using thematic content analysis. RESULTS: Forced expulsion from Bhutan was viewed as a violation of core ethnic-Nepali beliefs and sense of purpose related to collective identity. Throughout their 30-year refugee life trajectory, participants utilized coping strategies, including interpersonal support, reappraisal of experiences of trauma and loss, and helping oneself by helping others, that were informed by, and strengthened, this collective identity. These strategies served to both reaffirm worldviews and make new, positive meaning out of a refugee life experience. Individuals who were unable to leverage these strategies struggled to find meaning. CONCLUSIONS: We discuss study implications for psychosocial services for older refugees and contribution to theory on meaning making among diverse, vulnerable populations who experience multiple traumas and loss.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.005
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.002
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 head0.051
GPT teacher head0.378
Teacher spread0.327 · 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 designQualitative
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

Citations32
Published2020
Admission routes2
Has abstractyes

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