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Record W2070407112 · doi:10.1111/jocn12346

Towards the development of a gender‐sensitive measure of women's mental health

2013· article· en· W2070407112 on OpenAlexaff
Yuming Wang, Joy L. Johnson, Bih‐Ching Shu, Shih‐Ming Li

Bibliographic record

VenueJournal of Clinical Nursing · 2013
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMental healthScale (ratio)PsychologyClinical psychologyConcurrent validityPsychiatryPsychometricsInternal consistency

Abstract

fetched live from OpenAlex

AIMS AND OBJECTIVES: To develop a gender-sensitive measure of women's mental health and to evaluate the measure's psychometric properties. BACKGROUND: Mental health problems are a leading global burden of disease, and gender differences in the prevalence of these problems are well documented. Improving mental health is as important as resolving mental health problems. Although many mental health scales have been developed, few measure women's positive mental health from a gender perspective. DESIGN: Instrument development and psychometric evaluation were used. METHODS: First, a new mental health scale (Women's Mental Health Scale) grounded in women's subjective experiences was formulated from the narratives of four female focus groups (n = 23). The new scale was evaluated using principal component analysis and internal consistency reliability in a sample of female participants (n = 106). Next, the Women's Mental Health Scale, the Chinese version of Beck Depression Inventory-II and Social Adjustment Scale Self-Report were used in a survey of female undergraduate students (n = 163) for examining the concurrent criterion-related validity. Finally, gender differences were examined by assessing the discriminated validity of the Women's Mental Health Scale in a sample of male and female undergraduate students (n = 357). All participants were recruited from communities and universities in middle and south Taiwan. RESULTS: A 50-item Women's Mental Health Scale with four concepts of self, interpersonal, family and social domains was developed. It revealed that the Women's Mental Health Scale had acceptable psychometric properties. There was a significant negative correlation between scores of the Women's Mental Health Scale and the Chinese version of Beck Depression Inventory-II and a significant positive correlation between scores of the Women's Mental Health Scale and Social Adjustment Scale Self-Report. There were significant gender differences in the family domain and social domain. Women reported greater mental health in the family domain and social domain than men. CONCLUSIONS: The Women's Mental Health Scale is a promising gender-sensitive tool to measure women's mental health. RELEVANCE TO CLINICAL PRACTICE: The Women's Mental Health Scale appears to be a gender-sensitive measure to assess the positive mental health potentials among women population.

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)0.011
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.165
GPT teacher head0.495
Teacher spread0.330 · 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 designTheoretical or conceptual
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

Citations1
Published2013
Admission routes1
Has abstractyes

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