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Record W2011641973 · doi:10.11114/ijsss.v1i1.36

Support, Depressive Symptoms, and the Stigma towards Seeking Mental Health Help

2013· article· en· W2011641973 on OpenAlexafffund
Miki Talebi, Kimberly Matheson, Hymie Anisman

Bibliographic record

VenueInternational Journal of Social Science Studies · 2013
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsCarleton University
FundersCanadian Institutes of Health Research
KeywordsShameMental healthHelp-seekingStigma (botany)PsychologyDepressive symptomsClinical psychologySocial supportMental illnessPerceptionPsychiatrySocial stigmaDepression (economics)MedicineSocial psychologyCognitionHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

Although many individuals are affected by psychological disorders, few will seek professional help. Cultural perceptions might complicate this, as emotional suppression and shame of mental illness predominate in some cultures. This online study investigated factors contributing to the stigma of seeking help among Asian ( n =81) and Euro-Caucasian ( n =472) students. Depressive symptoms mediated relations between social support and self-stigma for seeking help for mental health problems, as well as for academic problems. The role of depression in the relation between social support and other-stigma of seeking mental health and academic help differed by cultural group, in that the relation between depressive symptoms and stigma was more pronounced among Asians, suggesting that targeted efforts may need to be directed at specific populations.

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 score0.005
Threshold uncertainty score0.010

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 head0.038
GPT teacher head0.439
Teacher spread0.401 · 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

Citations6
Published2013
Admission routes2
Has abstractyes

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