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使用移动医疗生酮饮食应用程序干预和与超重或肥胖成年人减肥相关的用户行为:一项随机临床试验的二次分析。

Use of an mHealth Ketogenic Diet App Intervention and User Behaviors Associated With Weight Loss in Adults With Overweight or Obesity: Secondary Analysis of a Randomized Clinical Trial.

机构信息

School of Health and Exercise Sciences, The University of British Columbia Okanagan, Kelowna, BC, Canada.

Department of Kinesiology, Brock University, St. Catherines, ON, Canada.

出版信息

JMIR Mhealth Uhealth. 2022 Mar 14;10(3):e33940. doi: 10.2196/33940.

Abstract

BACKGROUND

Low-carbohydrate ketogenic diets are a viable method to lose weight that have regained popularity in recent years. Technology in the form of mobile health (mHealth) apps allows for scalable and remote delivery of such dietary interventions and are increasingly being used by the general population without direct medical supervision. However, it is currently unknown which factors related to app use and user behavior are associated with successful weight loss.

OBJECTIVE

First, to describe and characterize user behavior, we aim to examine characteristics and user behaviors over time of participants who were enrolled in a remotely delivered clinical weight loss trial that tested an mHealth ketogenic diet app paired with a breath acetone biofeedback device. Second, to identify variables of importance to weight loss at 12 weeks that may offer insight for future development of dietary mHealth interventions, we aim to explore which app- and adherence-related user behaviors characterized successful weight loss.

METHODS

We analyzed app use and self-reported questionnaire data from 75 adults with overweight or obesity who participated in the intervention arm of a previous weight loss study. We examined data patterns over time through linear mixed models and performed correlation, linear regression, and causal mediation analyses to characterize diet-, weight-, and app-related user behavior associated with weight loss.

RESULTS

In the context of a low-carbohydrate ketogenic diet intervention delivered remotely through an mHealth app paired with a breath acetone biofeedback device, self-reported dietary adherence seemed to be the most important factor to predict weight loss (β=-.31; t=-2.366; P=.02). Furthermore, self-reported adherence mediated the relationship between greater app engagement (from c=-0.008, 95% CI -0.014 to -0.0019 to c'=-0.0035, 95% CI -0.0094 to 0.0024) or higher breath acetone levels (from c=-1.34, 95% CI -2.28 to -0.40 to c'=-0.40, 95% CI -1.42 to 0.62) and greater weight loss, explaining a total of 27.8% and 28.8% of the variance in weight loss, respectively. User behavior (compliance with weight measurements and app engagement) and adherence-related aspects (breath acetone values and self-reported dietary adherence) over time differed between individuals who achieved a clinically significant weight loss of >5% and those who did not.

CONCLUSIONS

Our in-depth examination of app- and adherence-related user behaviors offers insight into factors associated with successful weight loss in the context of mHealth interventions. In particular, our finding that self-reported dietary adherence was the most important metric predicting weight loss may aid in the development of future mHealth dietary interventions.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04165707; https://clinicaltrials.gov/ct2/show/NCT04165707.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/19053.

摘要

背景

低碳水化合物生酮饮食是一种可行的减肥方法,近年来重新流行起来。移动健康 (mHealth) 应用程序形式的技术可以对这种饮食干预进行可扩展和远程传递,并且越来越多地被没有直接医疗监督的普通民众使用。然而,目前尚不清楚与应用程序使用和用户行为相关的哪些因素与成功减肥有关。

目的

首先,为了描述和描述用户行为,我们旨在检查远程提供的临床减肥试验中参与者的特征和随时间变化的用户行为,该试验测试了与呼吸丙酮生物反馈设备配对的 mHealth 生酮饮食应用程序。其次,为了确定 12 周时对体重减轻重要的变量,这些变量可能为未来的膳食 mHealth 干预措施的发展提供见解,我们旨在探索哪些与应用程序和依从性相关的用户行为可以表征成功的体重减轻。

方法

我们分析了 75 名超重或肥胖成年人参与先前减肥研究干预部分的应用程序使用和自我报告问卷数据。我们通过线性混合模型检查了随时间的模式,并进行了相关性、线性回归和因果中介分析,以描述与体重减轻相关的饮食、体重和应用程序相关的用户行为。

结果

在通过 mHealth 应用程序远程提供低碳水化合物生酮饮食干预的背景下,与呼吸丙酮生物反馈设备配对,自我报告的饮食依从性似乎是预测体重减轻的最重要因素(β=-.31;t=-2.366;P=.02)。此外,自我报告的依从性介导了更大的应用程序参与(从 c=-0.008,95%CI-0.014 到-0.0019 到 c'=-0.0035,95%CI-0.0094 到 0.0024)或更高的呼吸丙酮水平(从 c=-1.34,95%CI-2.28 到-0.40 到 c'=-0.40,95%CI-1.42 到 0.62)与更大的体重减轻之间的关系,分别解释了体重减轻的总方差的 27.8%和 28.8%。在实现>5%的临床显著体重减轻的个体和未实现的个体之间,随时间变化的用户行为(体重测量和应用程序参与的依从性)和依从性相关方面(呼吸丙酮值和自我报告的饮食依从性)存在差异。

结论

我们对应用程序和依从性相关用户行为的深入检查为 mHealth 干预措施背景下与成功减肥相关的因素提供了深入了解。特别是,我们发现自我报告的饮食依从性是预测体重减轻的最重要指标,这可能有助于未来 mHealth 饮食干预措施的发展。

试验注册

ClinicalTrials.gov NCT04165707; https://clinicaltrials.gov/ct2/show/NCT04165707.

国际注册报告标识符(IRRID):RR2-10.2196/19053.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62f5/8961343/c843c0add160/mhealth_v10i3e33940_fig1.jpg

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