Abstract：
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.
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.
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.
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; t54=-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.
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.
ClinicalTrials.gov NCT04165707; https://clinicaltrials.gov/ct2/show/NCT04165707.
RR2-10.2196/19053.
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.
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.
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; t54=-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.
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.
ClinicalTrials.gov NCT04165707; https://clinicaltrials.gov/ct2/show/NCT04165707.
RR2-10.2196/19053.
摘要：
低碳水化合物生酮饮食是一种可行的减肥方法，近年来已重新流行。移动健康（mHealth）应用程序形式的技术允许可扩展和远程提供此类饮食干预措施，并且在没有直接医疗监督的情况下越来越多地被普通人群使用。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相关。
首先，描述和表征用户行为，我们的目标是检查参与者的特征和用户行为随时间的变化,这些参与者参与了一项远程实施的临床减肥试验,该试验测试了mHealth生酮饮食应用与呼吸丙酮生物反馈装置配对的应用.第二,确定12周时对减肥重要的变量，这些变量可能为饮食干预措施的未来发展提供见解，我们旨在探讨哪些与应用和依从性相关的用户行为是成功减肥的特征。
我们分析了参与先前减肥研究干预组的75名超重或肥胖成年人的应用程序使用情况和自我报告的问卷调查数据。我们通过线性混合模型检查了一段时间内的数据模式，并进行了相关性，线性回归，和因果中介分析来表征饮食-，weight-,以及与减肥相关的应用程序相关的用户行为。
在通过mHealth应用程序与呼吸丙酮生物反馈装置配对远程提供低碳水化合物生酮饮食干预的背景下，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;t54=-2.366;P=.02)。此外，自我报告的依从性介导了更高的应用参与度（从c=-0.008，95％CI-0.014至-0.0019到c\'=-0.0035，95％CI-0.0094至0.0024）或更高的呼吸丙酮水平（从c=-1.34，95％CI-2.28至-0.40到c\'=-0.40，95％CI-1.42至0.62）与更高的体重减轻之间的解释了总共27.8%和28.8%的体重减轻差异，分别。随着时间的推移，用户行为（体重测量和应用程序参与度的依从性）和与依从性相关的方面（呼吸丙酮值和自我报告的饮食依从性）在实现临床显着体重减轻>5％的个体和未实现的个体之间存在差异。
我们对与应用和依从性相关的用户行为的深入检查提供了在mHealth干预背景下与成功减肥相关的因素的见解。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,这可能有助于制定未来的mHealth饮食干预措施.
ClinicalTrials.govNCT04165707;https://clinicaltrials.gov/ct2/show/NCT04165707。
RR2-10.2196/19053。
首先，描述和表征用户行为，我们的目标是检查参与者的特征和用户行为随时间的变化,这些参与者参与了一项远程实施的临床减肥试验,该试验测试了mHealth生酮饮食应用与呼吸丙酮生物反馈装置配对的应用.第二,确定12周时对减肥重要的变量，这些变量可能为饮食干预措施的未来发展提供见解，我们旨在探讨哪些与应用和依从性相关的用户行为是成功减肥的特征。
我们分析了参与先前减肥研究干预组的75名超重或肥胖成年人的应用程序使用情况和自我报告的问卷调查数据。我们通过线性混合模型检查了一段时间内的数据模式，并进行了相关性，线性回归，和因果中介分析来表征饮食-，weight-,以及与减肥相关的应用程序相关的用户行为。
在通过mHealth应用程序与呼吸丙酮生物反馈装置配对远程提供低碳水化合物生酮饮食干预的背景下，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;t54=-2.366;P=.02)。此外，自我报告的依从性介导了更高的应用参与度（从c=-0.008，95％CI-0.014至-0.0019到c\'=-0.0035，95％CI-0.0094至0.0024）或更高的呼吸丙酮水平（从c=-1.34，95％CI-2.28至-0.40到c\'=-0.40，95％CI-1.42至0.62）与更高的体重减轻之间的解释了总共27.8%和28.8%的体重减轻差异，分别。随着时间的推移，用户行为（体重测量和应用程序参与度的依从性）和与依从性相关的方面（呼吸丙酮值和自我报告的饮食依从性）在实现临床显着体重减轻>5％的个体和未实现的个体之间存在差异。
我们对与应用和依从性相关的用户行为的深入检查提供了在mHealth干预背景下与成功减肥相关的因素的见解。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,这可能有助于制定未来的mHealth饮食干预措施.
ClinicalTrials.govNCT04165707;https://clinicaltrials.gov/ct2/show/NCT04165707。
RR2-10.2196/19053。
