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Record W2138185089 · doi:10.3109/09638237.2012.734651

Suicide among East Asians in North America: A scoping review

2013· review· en· W2138185089 on OpenAlexaffabout
Christina Han, John L. Oliffe, John S. Ogrodniczuk

Bibliographic record

VenueJournal of Mental Health · 2013
Typereview
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAcculturationEthnic groupPopulationMainstreamSuicide preventionThematic analysisPoison controlGeographyQualitative researchMedicineDemographySociologyPolitical scienceEnvironmental healthSocial scienceAnthropology

Abstract

fetched live from OpenAlex

BACKGROUND: Suicide is among the leading causes of death in North America for various age groups. Given the far-reaching impacts of suicide on families and societies, there is growing research on this phenomenon; yet, most focus primarily on mainstream populations (i.e. Caucasian, native-born Americans or Canadians) and/or aggregated population data. As a result cultural considerations within multi-cultural milieus and increasing globalization can be overlooked. AIMS: This scoping review reports findings drawn from 11 studies examining suicide among East Asian (EA) population in North America. METHOD: A web-based literature search was performed to identify original research articles published from January 2002 to December 2011, addressing suicide among EAs living in North America, specifically in the USA and Canada. RESULTS: Four prominent thematic findings were identified in the literature related to: (1) rates of suicidal ideation and behavior among EAs in North America; (2) acculturation; (3) family support and conflict; and (4) other cultural and ethnic considerations. CONCLUSIONS: Further research, particularly qualitative and/or mixed methods, is needed to provide a more complete understanding of suicide among this under-studied population. This article concludes with a list of recommendations for future research based on the review.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.916
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.123
GPT teacher head0.452
Teacher spread0.329 · 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 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

Citations19
Published2013
Admission routes2
Has abstractyes

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