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Record W2055630345 · doi:10.1037/1099-9809.14.3.215

Cultural influences on willingness to seek treatment for social anxiety in Chinese- and European-heritage students.

2008· article· en· W2055630345 on OpenAlexafffund
Lorena Hsu, Lynn E. Alden

Bibliographic record

VenueCultural Diversity & Ethnic Minority Psychology · 2008
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaBritish Columbia Medical Services FoundationMichael Smith Health Research BC
KeywordsAcculturationAnxietyPsychologySocial anxietyMental healthCultural heritageClinical psychologyPsychiatryEthnic groupPolitical science

Abstract

fetched live from OpenAlex

We examined culture-related influences on willingness to seek treatment for social anxiety in first- and second-generation students of Chinese heritage (Ns=65, 47, respectively), and their European-heritage counterparts (N=60). Participants completed measures that assessed their willingness to seek treatment for various levels of social anxiety. Results showed that participants were similar on willingness to seek treatment at low- and high-severity levels of social anxiety; however, at moderate levels, first-generation Chinese participants were significantly less willing to seek treatment compared to their European-heritage counterparts. The reluctance of first-generation Chinese participants to seek treatment was associated with greater Chinese-heritage acculturation, and was not related to perceiving symptoms of social anxiety as less impairing. The findings support the general contention that Asians in North America tend to delay treatment for mental health problems.

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)0.005
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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.168
GPT teacher head0.440
Teacher spread0.271 · 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

Citations69
Published2008
Admission routes2
Has abstractyes

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