Evidence map›Paper›PMID 37727146›Full record

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.

Yoonjung Kim, Sooyeon Park

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Trial
  2. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yoonjung KimCollege of Nursing, Konyang University, Daejeon, Republic of Korea.ORCID 0000-0003-0104-3865
Sooyeon ParkCollege of Nursing, Konyang University, Daejeon, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

health behaviorlifestyle behaviormenopausemetabolic syndromewomen

Identifiers

PMID37727146
PMCPMC10506598

What OpenQuestion holds

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Registered trials

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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.