ArticlePatient preference and adherence2023
Factors Associated with Prevention of Metabolic Syndrome Among Middle-Aged Postmenopausal Korean Women: A Study Based on the Information, Motivation, Behavioral Skills (IMB) Model.
Article in Patient preference and adherence, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Effectiveness of WeChat Public Account Intervention Based on the Information-Motivation-Behavioral Skills Model Among College Students With Internet Addiction: Randomized Controlled Trial.Journal of medical Internet research · 2026Trial
- Path analysis of cardiovascular disease preventive health behavior in postmenopausal Korean women based on the I-Change model.Scientific reports · 2026Article
- Structural model of health-promoting behavior in middle-aged Korean women with hypertension based on the Information-Motivation-Behavioral Skills model: a cross sectional study.Women's health nursing (Seoul, Korea) · 2026Article
- Patterns of proactive health behaviors and associated factors among middle-aged and older women in China: a latent class analysis.BMC nursing · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Metabolic syndrome (MetS) is a significant risk factor for cardiovascular disease. Middle-aged women, in particular, have been reported to have significantly increased cardiovascular disease rates after menopause; however, their adherence to health behaviors is lower than that of other populations. This study examined the factors associated with health behaviors for MetS prevention based on the Information-Motivation-Behavior skills model and described the relationships between the components of the model in middle-aged women. Patients and Methods: This investigative study used an online self-report questionnaire survey that included 241 middle-aged postmenopausal women aged 45-64 years. The collected data were analyzed using descriptive statistics with SPSS 28.0, independent Results: After controlling for age, time since menopause, and comorbidities, knowledge of MetS, social support, self-efficacy, and attitudes explained 42% of the variance in health behaviors for MetS prevention (F=18.38, p<0.001). Among these variables, self-efficacy (β=0.33, p<0.001), attitudes toward health behaviors (β=0.26, p<0.001), and knowledge of MetS (β=0.13, p=0.005) had a significant impact on health behaviors for MetS prevention. Conclusion: Significant associations were found between knowledge, self-efficacy, and attitudes toward health behaviors for MetS prevention among middle-aged women. The results of this study suggest that it is essential for healthcare provider to consider the components of the Information-Motivation-Behavior skills model when developing interventions aimed at improving health behaviors for MetS prevention among middle-aged postmenopausal women.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.