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Record W2132738795 · doi:10.7870/cjcmh-2014-036

Korean-Canadian Immigrants’ Help-Seeking and Self-Management of Suicidal Behaviours

2015· article· en· W2132738795 on OpenAlexaffvenueabout
Christina Han, John L. Oliffe

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2015
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHelp-seekingMental healthPsychologyImmigrationClinical psychologySocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

Suicidal behaviours are intricately connected to culture, oftentimes reflecting traditional norms and attitudes to health help-seeking and self-management. To describe Korean-Canadian immigrants’ help-seeking and self-management for their suicidal behaviours, 15 participants completed individual semistructured indepth interviews. Using constant comparison analysis, participants’ narratives were analysed to inductively derive two themes: 1) resisting professional help; and, 2) developing effective self-management strategies. The study findings suggest that most participants preferred and opted for self-management strategies rather than seeking professional help. Most participants’ reluctance to seek professional or peer help was underpinned by a fear of the stigma associated with traversing cultural norms by harbouring a mental illness and seeking help for that ailment. In addition, a lack of knowledge about available professional health care services, along with language and cultural barriers, led some participants to perceive mental health services as ineffectual. Participants’ determination to self-manage their suicidality was influenced by cultural norms around honouring and protecting family, and a range of spiritual and religious beliefs also emerged to counter impulses for acting on suicidal thoughts. By shedding light on Korean-Canadian immigrants’ experiences with suicidal behaviours, the findings offer some guidance toward developing culture-sensitive suicide prevention programs.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.069
GPT teacher head0.341
Teacher spread0.272 · 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 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

Citations17
Published2015
Admission routes3
Has abstractyes

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