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Record W2135174764 · doi:10.1177/1363461509351374

Why do Chinese Canadians not Consult Mental Health Services: Health Status, Language or Culture?

2009· article· en· W2135174764 on OpenAlexafffundabout
Alice W. Chen, Arminée Kazanjian, Hubert Wong

Bibliographic record

VenueTranscultural Psychiatry · 2009
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsUniversity of British ColumbiaSimon Fraser University
FundersCanadian Institutes of Health ResearchHealth CanadaSimon Fraser University
KeywordsMental healthImmigrationEthnic groupDepression (economics)MedicineChinese americansChinese peoplePsychiatryGerontologyPsychologyChinaGeographySociology

Abstract

fetched live from OpenAlex

Data from the Canadian Community Health Survey Cycle 1.1 showed that Chinese immigrants to Canada and Chinese individuals born in Canada were less likely than other Canadians to have contacted a health professional for mental health reasons in the previous year in the province of British Columbia. The difference persisted among individuals at moderate to high risk for depressive episode. Both immigrant and Canadian-born Chinese showed similar characteristics of mental health service use. The demographic and health factors that significantly affected their likelihood to consult mental health services included Chinese language ability, restriction in daily activities, frequency of medical consultations, and depression score. Notwithstanding lower levels of mental illness in ethnic Chinese communities, culture emerged as a major factor explaining differences in mental health consultation between Chinese and non-Chinese Canadians.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.048
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.362
Teacher spread0.348 · 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 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

Citations94
Published2009
Admission routes3
Has abstractyes

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