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Record W3206030462 · doi:10.1037/aap0000235

A qualitative study of perceptions of risk and protective factors for suicide among Bhutanese refugees.

2021· article· en· W3206030462 on OpenAlexaboutno aff
Jonah Meyerhoff, Praise Iyiewuare, Luna Acharya Mulder, Kelly J. Rohan

Bibliographic record

VenueAsian American Journal of Psychology · 2021
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
FundersNational Institute of Mental Health
KeywordsRefugeePsychologyPerceptionQualitative researchClinical psychologyPolitical scienceSociology

Abstract

fetched live from OpenAlex

century. The Lhotshampa people were forced to flee their homes in southern Bhutan and enter refugee camps in Nepal for over 20 years. As of this writing, most Bhutanese refugees have been resettled in other countries (primarily the United States, Canada, and Australia). As the two remaining Nepalese refugee camps prepare to close, a growing suicide crisis is developing among many Bhutanese refugees. Bhutanese refugees resettled in the United States are dying by suicide at approximately twice the rate of the general U.S. population. It is crucial to examine, qualitatively, the nature of both risk and protective factors from the perspective of Bhutanese refugees, themselves. Our study included 15 Bhutanese refugees (8 men, 7 women) recruited from a community sample as part of a parent project examining culturally responsive suicide risk assessment. Mean age across both genders was 38.4 years (range of 22-55 years). Participants in our study were asked open-ended questions about suicide risk and prevention. We conducted a thematic analysis, synthesized risk and protective themes, and applied a socio-ecological framework to the data. We found risk themes included psychological distress and vulnerability, substance use, social and familial discord, interpersonal violence, isolation, and postmigration stressors. Protective themes included low levels of substance use, de-stigmatization of mental health concerns, strong social connections, reduced postmigration stressors, increased access to mental health care, and strong awareness within the host community of migration-related challenges.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.282
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.033
GPT teacher head0.448
Teacher spread0.415 · 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 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

Citations4
Published2021
Admission routes1
Has abstractyes

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