DPPFit: Developing and Testing a Technology-Based Adaptation of the Diabetes Prevention Program (DPP) to Address Prediabetes in a Primary Care Setting

JOURNAL OF THE AMERICAN BOARD OF FAMILY MEDICINE(2022)

引用 4|浏览1
暂无评分
摘要
Objective: The objective of this study was to adapt the National Diabetes Prevention Program (N-DPP) into a pragmatic tool for primary care settings by using daily text messaging to deliver all N-DPP content, supplemented by Fitbit technology to provide behavioral strategies typically delivered by personnel in traditional programs. Test the mobile health (mHealth), technology-based N-DPP adaptation (DPPFit) in primary care patients with prediabetes using a remote intervention based on the traditional 16 core sessions of the DPP. Methods: A pilot study with pre/post survey analysis of aggregate data were used to determine changes in weight, physical activity, sedentary behavior, and associated diabetes risk outcomes among study participants (n = 33). In this study, participants were issued Fitbit devices and provided the remote intervention over 16 weeks via automated text messaging technology, which followed the content of the DPP core education sessions. Results: Data analysis from baseline to 6-month follow-up demonstrate mean weight loss of 3.3 kg (95% CI: -6.2 to -0.5; P =.026), reduction in body mass index by 1.25 points (95% CI: -2.1 to -0.4; P =.005), a significant average increase of 2 days in self-reported physical activity per week (95% CI :0.4 to 3.6; P =.015) and an average 10% decrease in sedentary time (P =.007). Conclusions: The remote DPPFit intervention demonstrates a promising and practical approach to the management of prediabetes in a primary care setting. The results support the use of the DPPFit program and application to achieve meaningful outcomes in a population with prediabetes. A randomized controlled trial with a larger sample is warranted.
更多
查看译文
关键词
Diabetes Prevention Program (DPP), Lifestyle, Metabolic Syndrome, mHealth, Primary Health Care, Technology, Telemedicine, Translational Research
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要