ArticleBMC pregnancy and childbirth2025
A latent profile analysis of heterogeneity in self-management behavior of gestational diabetes mellitus patients.
Article in BMC pregnancy and childbirth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Article
- Potential Profile of Self-Management and Associated Factors Among Patients with Nonalcoholic Fatty Liver Disease.Patient preference and adherence · 2026Article
- Fear of Complications Among Patients with Type 2 Diabetes: A Latent Profile Analysis.Patient preference and adherence · 2026Article
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5 authors.
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Abstract
objectiveTo identify latent profiles of self-management behaviors among patients with Gestational Diabetes Mellitus (GDM) and develop targeted interventions.
methods Between July 2023 and October 2023, 320 GDM patients were surveyed using a self-management behavior questionnaire. Latent profile analysis (LPA) was employed to identify subgroups of GDM patients. Subsequent multinomial latent variable regressions were used to identify factors associated with self-management behavior.
results23.0%, 47.0%, and 29.9% of respondents were classified into high, moderate, and low self-management groups, respectively, based on the results of the latent profile analysis. The three different categories demonstrated statistically significant differences across scale scores and dimensions (all p < 0.001). The findings showed that age was a predictor of class 2 (OR:0.93,95%CI:0.872-0.994)and was associated with reduced self-management behavior. The higher BIPS(OR:1.03,95%CI:1.007-1.044;OR:1.04,95%CI:1.015-1.057) and QOL(OR:1.05,95%CI:1.028-1.077;OR:1.06,95%CI:1.036-1.092) mean scores were significantly more likely to be in class2 and class3. Patients with a sleep disorder (OR:0.32,95%CI:0.167-0.599; OR:0.27,95%CI:0.130-0.544)were significantly more likely to be class 2 and class 3. Having a blood glucose normal before pregnancy(OR:4.17,95%CI:1.013-17.295) was significantly more likely to be in class 3.
conclusionThe GDM patient population is heterogeneous, with distinct subtypes that may benefit from tailored, multi-level interventions.
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