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Updated: Jun 10, 2025

A Zebrafish Model of Diabetes Mellitus and Metabolic Memory
Published on: February 28, 2013
Effect of shared decision-making model on the management of diabetes high-risk groups
Qiu-Shi Wang1, Xiao-Dong Yue2, Yan Ma1
1Department of Public Health, The No.2 People's Hospital Of Xiangcheng District, Suzhou, Jiangsu, China.
Objective:
A shared decision-making (SDM) model-based intervention programme was implemented for a population at high risk for diabetes to explore its effectiveness in intervening with blood glucose levels in this population.
Methods:
One hundred residents were selected according to the principle of voluntary participation and divided into the intervention group (n = 50) and the control group (n = 50) by using multistage cluster sampling. The control group received only brief diabetes knowledge education through a disease brochure issued by the hospital; the intervention group implemented a SDM model based on large classroom and individualised education for 4 months. Univariate analysis and generalised estimating equation fitting model were used to analyse the effect of intervention on blood glucose parameters in the study subjects.
Results:
Univariate analysis showed that after 4 months of intervention, fasting blood glucose was lower in the intervention group than in the control group (5.57 ± 0.56 vs. 6.07 ± 0.77, F = 45.721, p < 0.001); glycosylated hemoglobin was lower in the intervention group than in the control group (5.91 ± 0.28 vs. 6.02 ± 0.24, F = 25.998, p < 0.001), decreased by 0.26% in the intervention group and increased by 0.01% in the control group. One-way analysis of variance (ANOVA) showed that fasting blood glucose and glycosylated hemoglobin in the intervention group decreased to different extents from baseline. The generalised estimation equation was fitted with the intervention programme, gender, hypertension, smoking, alcohol consumption, physical activity, age, waist circumference, body mass index, baseline fasting blood glucose, and baseline glycosylated hemoglobin as independent variables, and fasting blood glucose and baseline glycosylated hemoglobin as dependent variables. Results showed that compared with the control group, fasting blood glucose and glycosylated hemoglobin levels were significantly different between the two groups (p < 0.001).
Conclusion:
Applying an intervention programme based on SDM model to people at high risk of diabetes can improve patients' adherence to self-management and establish a good lifestyle, thus contributing to their good glycemic control.
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