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Record W2429720976

Gender Differences in Mental Health Literacy of University Students

2016· article· en· W2429720976 on OpenAlexaff
Kyleen Wong

Bibliographic record

VenueScholarship@Western (Western University) · 2016
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsWestern University
Fundersnot available
KeywordsMental healthMental health literacyPsychologyAffect (linguistics)SocializationLiteracyHealth literacyDevelopmental psychologyClinical psychologyMental illnessPsychiatryHealth carePedagogy
DOInot available

Abstract

fetched live from OpenAlex

This article aimed to describe gender differences in the mental health literacy of university students in western societies and to provide a brief overview of how gender socialization might contribute to these differences. A review of studies providing information on gender differences in university students’ mental health literacy was carried out. The literature showed that the importance of mental health literacy lay in its positive association with better mental health status through the enabling of help-seeking behaviours. University students have some knowledge of mental health and a majority were able to recognize common disorders. However, the ability to recognize disorders did not guarantee adequate knowledge. Similar to adults, young people were more likely to correctly identify depressive symptoms than they were to correctly label schizophrenic symptoms. Males consistently demonstrated less awareness of disorders compared to females, but gender differences did not exist in all circumstances. In terms of help-seeking, young adults preferred informal help from friends and family over professional services, a trend that was especially pronounced in young men. This review suggested that gender does affect mental health literacy in post-secondary students. Although mechanisms to explain how gender mediates literacy can be proposed, gender is not a categorical predictor of differences in university students’ mental health literacy. More comprehensive research in young people’s knowledge of and attitudes toward mental health is needed.

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)0.000
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 score0.013
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.152
GPT teacher head0.412
Teacher spread0.261 · 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

Citations16
Published2016
Admission routes1
Has abstractyes

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