糖尿病行为与生活方式干预展望

doi:10.12114/j.issn.1007-9572.2025.0587

中国全科医学 ›› 2026, Vol. 29 ›› Issue (31): 4513-4520.DOI: 10.12114/j.issn.1007-9572.2025.0587

• 述评 •

糖尿病行为与生活方式干预展望

田向阳¹, 周迎生²^,^*(), 高莹³

1．100011　北京市，中国健康教育中心
2．101118　北京市，首都医科大学附属北京安贞医院内分泌科
3．100034　北京市，北京大学第一医院内分泌科

收稿日期:2025-12-16 修回日期:2026-06-03 出版日期:2026-11-05 发布日期:2026-10-10
通讯作者: 周迎生
作者贡献：
田向阳负责资料的收集与整理、论文撰写与修订，对文章整体负责；周迎生、高莹参与论文构思与修订。
基金资助:
国家科技重大专项资助项目(2024ZD0524303，2024ZD0524300); 首都卫生发展科研专项项目(2022-1g-2064)

Prospects of Behavioral and Lifestyle Interventions for Diabetes Mellitus

TIAN Xiangyang¹, ZHOU Yingsheng²^,^*(), GAO Ying³

1. Chinese Center for Health Education, Beijing 100011, China
2. Department of Endocrinology, Beijing Anzhen Hospital, Capital Medical University, Beijing 101118, China
3. Department of Endocrinology, Peking University First Hospital, Beijing 100034, China

Received:2025-12-16 Revised:2026-06-03 Published:2026-11-05 Online:2026-10-10
Contact: ZHOU Yingsheng

摘要/Abstract

摘要： 行为与生活方式干预（BLIs）是2型糖尿病预防和治疗的基础，并逐渐走向定制化、剂量化、个性化和精准化。面对面干预在建立医患互信、融洽医患关系和提升行为干预效果方面是远程干预不可替代的。通过糖尿病自我管理教育与支持（DSMES），指导患者进行自我管理，既能增加行为与生活方式干预的有效性，也可大幅减轻医护人员的工作负担。行为改变理论（BCT）和行为改变技术（BCTs）可提高BLIs的效率，建议在2型糖尿病防治中予以推广和应用。人工智能（AI）大语言模型（LLMs）在糖尿病发病风险预测、个性化生活方式指导、远程监测与自我管理和临床决策支持系统应用方面将发挥重要作用。

关键词: 行为与生活方式干预, 2型糖尿病, 面对面干预, 自我管理教育与支持, 行为改变理论, 行为改变技术, 人工智能

Abstract:

Behavioral and lifestyle interventions (BLIs) form the cornerstone of preventing and treating type 2 diabetes mellitus (T2DM), and are increasingly moving toward customization, dosing, personalization, and precision. Face-to-face interventions are irreplaceable by remote interventions in building doctor-patient trust, fostering harmonious doctor-patient relationships, and enhancing the effectiveness of behavioral interventions. Through diabetes self-management education and support (DSMES), guiding patients in self-management not only improves the efficacy of BLIs but also significantly reduces the workload of healthcare professionals. Behavioral change theory (BCT) and techniques (BCTs) can enhance the efficiency of such interventions and will be widely promoted and applied. Large language models (LLMs) in artificial intelligence (AI) will play a pivotal role in predicting the risk of diabetes onset, providing personalized lifestyle guidance, enabling remote monitoring and self-management, and supporting AI-driven clinical decision-making systems.

Key words: Behavioral and lifestyle interventions, Type 2 diabetes mellitus, Face-to-face interventions, Self-management education and support, Behavioral change theories, Behavioral change techniques, Artificial intelligence

中图分类号:

R 587.1

田向阳,周迎生,高莹. 糖尿病行为与生活方式干预展望[J]. 中国全科医学, 2026, 29(31): 4513-4520. DOI: 10.12114/j.issn.1007-9572.2025.0587.
TIAN Xiangyang,ZHOU Yingsheng,GAO Ying. Prospects of Behavioral and Lifestyle Interventions for Diabetes Mellitus[J]. Chinese General Practice, 2026, 29(31): 4513-4520. DOI: 10.12114/j.issn.1007-9572.2025.0587.

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糖尿病行为与生活方式干预展望

Prospects of Behavioral and Lifestyle Interventions for Diabetes Mellitus

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