{"title":"接受个性化患者教育的CAPDCA模型的糖尿病患者血糖轨迹:一项聚类随机对照试验。","authors":"Jie Li, YuJiang Liu, Wei Xing, Yue Jiang","doi":"10.1111/dom.70119","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>The CAPDCA (Collection, Assessment, Plan, Do, Check, Aggrandisement) Model is a structured and individualised health education framework designed for dynamic adjustment and continuous improvement. This study evaluated its efficacy in diabetes management.</p><p><strong>Methods: </strong>A cluster randomised controlled trial was conducted across 6 community health centres, involving 178 patients with type 2 diabetes. The intervention group (n = 90) received CAPDCA model education, while the control group (n = 88) received traditional education. The intervention spanned 18 months, with HbA1c collected at baseline and study end. Blood glucose was collected at each follow-up. Analysis used Group-Based Trajectory Model (GBTM).</p><p><strong>Results: </strong>Compared with the control group, the intervention group showed: lower HbA1c (t = 6.356, p < 0.01) and greater HbA1c reduction (t = -6.117, p < 0.01). GBTM revealed distinct glucose trajectories: FBG had two trajectories (Steady descent group and rebound group). The 2 h-PG had three trajectories (High BG-high descent group, Medium BG-low descent group, and low BG-high descent group). All trajectories demonstrated that blood glucose levels reached clinically target ranges post-intervention. Baseline HbA1c influenced FBG trajectories, while baseline HbA1c and medication adherence influenced 2 h-PG trajectories. Age, gender, education, and disease duration showed no significant association with trajectories.</p><p><strong>Conclusions: </strong>The CAPDCA model can effectively improve the control of HbA1c. The analysis of influencing factors of different trajectories suggested that the model was suitable for patients with different ages, genders, education levels, and disease duration. Further studies would be needed in exploring the application to various diseases and integrating the CAPDCA model with technologies such as artificial intelligence.</p>","PeriodicalId":158,"journal":{"name":"Diabetes, Obesity & Metabolism","volume":" ","pages":""},"PeriodicalIF":5.7000,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Blood glucose trajectories in diabetes patients receiving CAPDCA model of personalised patient education: A cluster randomised controlled trial.\",\"authors\":\"Jie Li, YuJiang Liu, Wei Xing, Yue Jiang\",\"doi\":\"10.1111/dom.70119\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>The CAPDCA (Collection, Assessment, Plan, Do, Check, Aggrandisement) Model is a structured and individualised health education framework designed for dynamic adjustment and continuous improvement. This study evaluated its efficacy in diabetes management.</p><p><strong>Methods: </strong>A cluster randomised controlled trial was conducted across 6 community health centres, involving 178 patients with type 2 diabetes. The intervention group (n = 90) received CAPDCA model education, while the control group (n = 88) received traditional education. The intervention spanned 18 months, with HbA1c collected at baseline and study end. Blood glucose was collected at each follow-up. Analysis used Group-Based Trajectory Model (GBTM).</p><p><strong>Results: </strong>Compared with the control group, the intervention group showed: lower HbA1c (t = 6.356, p < 0.01) and greater HbA1c reduction (t = -6.117, p < 0.01). GBTM revealed distinct glucose trajectories: FBG had two trajectories (Steady descent group and rebound group). The 2 h-PG had three trajectories (High BG-high descent group, Medium BG-low descent group, and low BG-high descent group). All trajectories demonstrated that blood glucose levels reached clinically target ranges post-intervention. Baseline HbA1c influenced FBG trajectories, while baseline HbA1c and medication adherence influenced 2 h-PG trajectories. Age, gender, education, and disease duration showed no significant association with trajectories.</p><p><strong>Conclusions: </strong>The CAPDCA model can effectively improve the control of HbA1c. The analysis of influencing factors of different trajectories suggested that the model was suitable for patients with different ages, genders, education levels, and disease duration. Further studies would be needed in exploring the application to various diseases and integrating the CAPDCA model with technologies such as artificial intelligence.</p>\",\"PeriodicalId\":158,\"journal\":{\"name\":\"Diabetes, Obesity & Metabolism\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2025-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Diabetes, Obesity & Metabolism\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/dom.70119\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diabetes, Obesity & Metabolism","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/dom.70119","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Blood glucose trajectories in diabetes patients receiving CAPDCA model of personalised patient education: A cluster randomised controlled trial.
Objective: The CAPDCA (Collection, Assessment, Plan, Do, Check, Aggrandisement) Model is a structured and individualised health education framework designed for dynamic adjustment and continuous improvement. This study evaluated its efficacy in diabetes management.
Methods: A cluster randomised controlled trial was conducted across 6 community health centres, involving 178 patients with type 2 diabetes. The intervention group (n = 90) received CAPDCA model education, while the control group (n = 88) received traditional education. The intervention spanned 18 months, with HbA1c collected at baseline and study end. Blood glucose was collected at each follow-up. Analysis used Group-Based Trajectory Model (GBTM).
Results: Compared with the control group, the intervention group showed: lower HbA1c (t = 6.356, p < 0.01) and greater HbA1c reduction (t = -6.117, p < 0.01). GBTM revealed distinct glucose trajectories: FBG had two trajectories (Steady descent group and rebound group). The 2 h-PG had three trajectories (High BG-high descent group, Medium BG-low descent group, and low BG-high descent group). All trajectories demonstrated that blood glucose levels reached clinically target ranges post-intervention. Baseline HbA1c influenced FBG trajectories, while baseline HbA1c and medication adherence influenced 2 h-PG trajectories. Age, gender, education, and disease duration showed no significant association with trajectories.
Conclusions: The CAPDCA model can effectively improve the control of HbA1c. The analysis of influencing factors of different trajectories suggested that the model was suitable for patients with different ages, genders, education levels, and disease duration. Further studies would be needed in exploring the application to various diseases and integrating the CAPDCA model with technologies such as artificial intelligence.
期刊介绍:
Diabetes, Obesity and Metabolism is primarily a journal of clinical and experimental pharmacology and therapeutics covering the interrelated areas of diabetes, obesity and metabolism. The journal prioritises high-quality original research that reports on the effects of new or existing therapies, including dietary, exercise and lifestyle (non-pharmacological) interventions, in any aspect of metabolic and endocrine disease, either in humans or animal and cellular systems. ‘Metabolism’ may relate to lipids, bone and drug metabolism, or broader aspects of endocrine dysfunction. Preclinical pharmacology, pharmacokinetic studies, meta-analyses and those addressing drug safety and tolerability are also highly suitable for publication in this journal. Original research may be published as a main paper or as a research letter.