Social Mobile Approaches to Reduce Weight (SMART) 2.0

社交移动减肥方法 (SMART) 2.0

基本信息

  • 批准号:
    10348761
  • 负责人:
  • 金额:
    $ 70.59万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-02-19 至 2024-01-31
  • 项目状态:
    已结题

项目摘要

ABSTRACT Approximately 60.3% of those aged 20 to 39 years are overweight or obese, and excess weight gain in young adulthood is associated with future weight gain, cardiovascular disease risk factors, and psychological distress. Consequently, it has been suggested that treating overweight and obesity in young adults may prevent chronic disease in middle age. Relatively little is known about how to promote weight loss in this population without using costly in-person programs that have limited scalability. For several years, our group has investigated the efficacy of interventions that rely on ubiquitous technologies to meet young adults in the virtual spaces they frequently inhabit and use these venues to promote weight loss through physical activity and healthy diet. We now propose to conduct a parallel-group randomized controlled trial among 642 overweight/obese university students aged 18-35 years in San Diego. Participants will be randomly allocated to either 1) SMART 2.0 with technology and personal health coaching; 2) SMART 2.0 with technology alone; or 3) a control group. The interventions will be delivered for 24 months, and they are designed to maximize efficacy in a scalable manner. Intervention content will be delivered using a fully integrated system of modalities: 1) Fitbit, 2) MyFitnessPal, 3) SMS, 4) multiple social media streams, 5) a website with blog, and 6) email. Consumer-level devices and apps will be used to self-monitor behavior, and their data will be passively acquired in real-time. Algorithms will be used to automatically deliver interactive text messages to support individually tailored goal setting, performance feedback, and goal review in a highly dynamic style that reflects participants' behavioral progress towards achieving a minimum goal of 5% weight loss. Participants will be encouraged to share their data and behavioral progress with others via social networking tools built into the apps. Social network mechanisms of influence will be used both within the study-space, to elicit participant-to-participant and health coach-to- participant support, as well as outside the study-space, to invoke social support and accountability from strong ties known to be important for long-term behavior change. Additionally, one group will receive monthly technology-mediated, real-time personal health coaching that is theory- and evidence-based. Our primary aim is to determine the efficacy of the SMART 2.0 interventions to improve weight over 24 months. Our secondary aims are to evaluate to evaluate 1) differences between groups at 6, 12, 18, and 24 months in anthropometric and physiological outcomes, physical activity, diet, sleep, self-esteem, body image, anxiety, depression, and the frequency and composition of participants' online communication about weight-related behaviors; 2) the dose response (i.e., quantified engagement with modalities) of the interventions; 3) the usability and acceptability of the intervention; 4) potential mediators and moderators of the intervention effects (e.g., social network connectivity, contamination, etc.); and 5) patterns of change in physical activity, diet, and sleep.
抽象的 20至39岁人群中约60.3%超重或肥胖,年轻人体重增加过多 成年期与未来体重增加、心血管疾病危险因素和心理困扰有关。 因此,有人建议治疗年轻人的超重和肥胖可以预防慢性 中年时患病。对于如何在不增加体重的情况下促进这一人群减肥,人们知之甚少。 使用成本高昂且可扩展性有限的面对面程序。多年来,我们的团队一直在研究 依靠无处不在的技术在虚拟空间中与年轻人见面的干预措施的有效性 经常居住和使用这些场所,通过体育活动和健康饮食来促进减肥。我们 现提议在 642 所超重/肥胖大学中进行平行组随机对照试验 圣地亚哥 18-35 岁的学生。参与者将被随机分配到 1) SMART 2.0 技术和个人健康指导; 2)仅靠技术的SMART 2.0;或 3) 对照组。这 干预措施将持续 24 个月,旨在以可扩展的方式最大限度地提高疗效。 干预内容将使用完全集成的模式系统提供:1) Fitbit,2) MyFitnessPal,3) 短信、4) 多个社交媒体流、5) 带有博客的网站,以及 6) 电子邮件。消费级设备和应用程序 将用于自我监控行为,他们的数据将被实时被动获取。算法将是 用于自动发送交互式文本消息以支持单独定制的目标设定, 以高度动态的方式进行绩效反馈和目标审查,反映参与者的行为进展 实现减重 5% 的最低目标。将鼓励参与者分享他们的数据和 通过应用程序内置的社交网络工具与他人取得行为进步。社交网络机制 影响力将在研究空间内使用,以引发参与者之间和健康教练之间的交流 参与者的支持以及学习空间之外的支持,以调用强有力的社会支持和问责制 众所周知,关系对于长期行为改变很重要。此外,一组每月将收到 以技术为媒介的、基于理论和证据的实时个人健康指导。我们的首要目标 目的是确定 SMART 2.0 干预措施在 24 个月内改善体重的效果。我们的中学 目的是评估 1) 6、12、18 和 24 个月时各组之间的人体测量差异 和生理结果、体力活动、饮食、睡眠、自尊、身体形象、焦虑、抑郁和 参与者在线交流体重相关行为的频率和构成; 2) 干预措施的剂量反应(即量化参与方式); 3)可用性和 干预措施的可接受性; 4)干预效果的潜在中介者和调节者(例如,社会 网络连接、污染等); 5) 体力活动、饮食和睡眠的变化模式。

项目成果

期刊论文数量(5)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Characterizing and predicting person-specific, day-to-day, fluctuations in walking behavior.
  • DOI:
    10.1371/journal.pone.0251659
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Chevance G;Baretta D;Heino M;Perski O;Olthof M;Klasnja P;Hekler E;Godino J
  • 通讯作者:
    Godino J
Day-to-day associations between sleep and physical activity: a set of person-specific analyses in adults with overweight and obesity.
  • DOI:
    10.1007/s10865-021-00254-6
  • 发表时间:
    2022-03
  • 期刊:
  • 影响因子:
    3.1
  • 作者:
    Chevance G;Baretta D;Romain AJ;Godino JG;Bernard P
  • 通讯作者:
    Bernard P
Social Mobile Approaches to Reducing Weight (SMART) 2.0: protocol of a randomized controlled trial among young adults in university settings.
  • DOI:
    10.1186/s13063-021-05938-7
  • 发表时间:
    2022-01-03
  • 期刊:
  • 影响因子:
    2.5
  • 作者:
    Mansour-Assi SJ;Golaszewski NM;Costello VL;Wing D;Persinger H;Coleman A;Lytle L;Larsen BA;Jain S;Weibel N;Rock CL;Patrick K;Hekler E;Godino JG
  • 通讯作者:
    Godino JG
Impact of the COVID-19 Pandemic on Objectively Measured Physical Activity and Sedentary Behavior Among Overweight Young Adults: Yearlong Longitudinal Analysis.
  • DOI:
    10.2196/28317
  • 发表时间:
    2021-11-24
  • 期刊:
  • 影响因子:
    8.5
  • 作者:
    Lawhun Costello V;Chevance G;Wing D;Mansour-Assi SJ;Sharp S;Golaszewski NM;Young EA;Higgins M;Ibarra A;Larsen B;Godino JG
  • 通讯作者:
    Godino JG
SMART 2.0: A Multimodal Weight Loss Intervention for Young Adults.
SMART 2.0:针对年轻人的多模式减肥干预措施。
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Eric Hekler其他文献

Eric Hekler的其他文献

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{{ truncateString('Eric Hekler', 18)}}的其他基金

Control Systems Engineering to Address the Problem of Weight Loss Maintenance: A System Identification Experiment to Model Behavioral & Psychosocial Factors Measured by Ecological Momentary Assessment
解决减肥维持问题的控制系统工程:行为建模的系统识别实验
  • 批准号:
    10749979
  • 财政年份:
    2023
  • 资助金额:
    $ 70.59万
  • 项目类别:
Advanced data analytics training for behavioral and social sciences research
针对行为和社会科学研究的高级数据分析培训
  • 批准号:
    10402911
  • 财政年份:
    2020
  • 资助金额:
    $ 70.59万
  • 项目类别:
Optimizing Individualized and Adaptive mHealth Interventions via Control Systems Engineering Methods
通过控制系统工程方法优化个性化和适应性移动医疗干预措施
  • 批准号:
    10668422
  • 财政年份:
    2020
  • 资助金额:
    $ 70.59万
  • 项目类别:
Optimizing Individualized and Adaptive mHealth Interventions via Control Systems Engineering Methods
通过控制系统工程方法优化个性化和适应性移动医疗干预措施
  • 批准号:
    10759023
  • 财政年份:
    2020
  • 资助金额:
    $ 70.59万
  • 项目类别:
Advanced data analytics training for behavioral and social sciences research
针对行为和社会科学研究的高级数据分析培训
  • 批准号:
    10160959
  • 财政年份:
    2020
  • 资助金额:
    $ 70.59万
  • 项目类别:
Advanced data analytics training for behavioral and social sciences research
针对行为和社会科学研究的高级数据分析培训
  • 批准号:
    10649605
  • 财政年份:
    2020
  • 资助金额:
    $ 70.59万
  • 项目类别:
Optimizing Individualized and Adaptive mHealth Interventions via Control Systems Engineering Methods
通过控制系统工程方法优化个性化和适应性移动医疗干预措施
  • 批准号:
    10599617
  • 财政年份:
    2020
  • 资助金额:
    $ 70.59万
  • 项目类别:
Optimizing Individualized and Adaptive mHealth Interventions via Control Systems Engineering Methods
通过控制系统工程方法优化个性化和适应性移动医疗干预措施
  • 批准号:
    10456317
  • 财政年份:
    2020
  • 资助金额:
    $ 70.59万
  • 项目类别:
Optimizing Individualized and Adaptive mHealth Interventions via Control Systems Engineering Methods
通过控制系统工程方法优化个性化和适应性移动医疗干预措施
  • 批准号:
    10826070
  • 财政年份:
    2020
  • 资助金额:
    $ 70.59万
  • 项目类别:
Optimizing Individualized and Adaptive mHealth Interventions via Control Systems Engineering Methods
通过控制系统工程方法优化个性化和适应性移动医疗干预措施
  • 批准号:
    10216204
  • 财政年份:
    2020
  • 资助金额:
    $ 70.59万
  • 项目类别:

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