Phase 1 clinical trial to develop a personalized adaptive text message intervention using control systems engineering tools to increase physical activity in early adulthood
Phase 1 clinical trial to develop a personalized adaptive text message intervention using control systems engineering tools to increase physical activity in early adulthood
批准号:
10152695
负责人:
DAVID E. CONROY
金额:
$55.72万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-07-01 至 2023-04-30
关键词:
AccelerometerAdultAlgorithmsBehaviorBehavior TherapyBehavioralBehavioral ModelCardiovascular DiseasesCaringCellular PhoneChronicChronic DiseaseComplexComputer ModelsDataDevelopmentDiabetes MellitusDietEngineeringEnsureFrequenciesFutureGoalsHealthHealthcare SystemsIndividualInterventionLocationMalignant NeoplasmsMethodsModelingParticipantPerformancePeriodicityPhase I Clinical TrialsPhysical activityPopulationPosturePreventiveProblem SolvingRandomizedRisk FactorsRunningSamplingSmokingSpecific qualifier valueSystemText MessagingTimeUncertaintyUnderinsuredUpdateWeatherWeight GainWorkacceptability and feasibilityadaptive interventionbasebehavior changebehavioral responsecardiovascular disorder riskcardiovascular healthcontextual factorscostdesigndisorder riskemerging adultexercise interventionexperiencefallsindexinginterestintervention effectlifestyle factorsmathematical modelnovel strategiespersonalized decisionpersonalized interventionpersonalized medicinepersonalized strategiesphase II trialphysical inactivityphysical modelprecision medicinepredictive modelingpreservationpreventpublic health relevancerecruitresponseservice interventionsuccesstext messaging interventiontooltreatment effecttreatment responsewearable devicewearable sensor technologyyoung adult
中文摘要
项目摘要
缺乏身体活动是导致体重增加的一系列生活方式因素的一部分--吸烟和饮食
在成年早期获得。危害心血管健康的风险因素开始积累,
过渡到成年。在此期间,预防体力活动(PA)减少的干预措施可以
降低长期慢性病风险。短信干预显示出一致的积极影响,
但通过量身定制、针对性或个性化来提高这些干预效果的努力尚未实现
他们的潜力已经出现了新的方法,根据治疗反应或
背景因素(例如,阶梯式护理,及时适应性干预),但他们采用单一的决策规则
对所有参与者都一样。行为是复杂的,多方面决定的,因此治疗可能
反应是特殊的,需要个性化的决策规则。基于对精确性的兴趣
医学,我们提出了一种方法来开发个性化的自适应信息干预,使用密集的
纵向数据(来自可穿戴传感器和瞬时天气指数)和控制系统的工具
工程(系统识别和鲁棒控制合成)。在初步工作中,我们开发了一个
计算模型的物理活动响应个人短信。的最大障碍
在干预措施中实施这种方法的关键是预测建模所需的计算模型,
的PA动态具有高度的不确定性,并且过于复杂,无法在智能手机上有效运行,
其他可穿戴设备。我们建议解决这个问题,通过(1)发展一个动力学模型的物理
基于对消息的历史响应、最近的行为、特定位置的天气和时间的活动
特征,以及(2)评估更多与更少积极适应的可接受性和可行性
个性化干预控制器的策略。为了实现这些目标,我们将招募年轻人,
参与PA消息传递干预,并开发不同响应的计算模型
不同条件下的信息。将开发基于模型的控制器,以(a)优化消息
定时、频率和内容选择,以及(B)在变化的情况下实现指定的行为改变目标
条件然后,我们将部署控制器与一个独立的样本的年轻人,以确定如何
在接下来的六个月里,更积极的适应策略与更不积极的适应策略会影响用户体验。本研究
将有助于基于模型的干预控制器和可接受的适应策略,
个性化的自适应消息传递干预,以增加PA。如果成功,它将增加PA和用户
通过选择和定时信息来最大限度地发挥作用,最大限度地减少负担。这种方法可以
应用于开发与预防体重增加相关的其他行为的个性化干预,
保持心血管健康,降低慢性病风险。
英文摘要
Project Summary
Physical inactivity is part of a constellation of lifestyle factors – with smoking and diet – that contribute to weight
gain in early adulthood. Risk factors that compromise cardiovascular health begin to accumulate during the
transition into adulthood. Interventions that prevent decreases in physical activity (PA) during this period can
reduce long-term chronic disease risk. Text message interventions have shown a consistent positive effect on
PA but efforts to increase those intervention effects via tailoring, targeting or personalizing have not realized
their potential. New approaches have emerged for tailoring interventions based on treatment responses or
contextual factors (e.g., stepped care, just-in-time adaptive interventions) but they apply a single decision rule
uniformly for all participants. Behavior is complex and multiply determined so it is possible that treatment
responses are idiosyncratic, necessitating personalized decision rules. Building on interest in precision
medicine, we propose a method to develop personalized adaptive messaging interventions using intensive
longitudinal data (from wearable sensors and momentary weather indices) and tools from control systems
engineering (system identification and robust control synthesis). In preliminary work, we developed a
computational model of physical activity responses to individual text messages. The greatest barrier to
implementing that approach in interventions is that the computational models required for predictive modeling
of PA dynamics have a high degree of uncertainty and are too complex to run efficiently on smartphones and
other wearable devices. We propose to solve that problem by (1) developing a dynamical model of physical
activity based on historical responses to messages, recent behavior, location-specific weather, and temporal
features, and (2) evaluating the acceptability and feasibility of more versus less aggressive adaptation
strategies for personalizing an intervention controller. To accomplish these aims, we will recruit young adults to
participate in a PA messaging intervention and develop a computational model of responses to different
messages under different conditions. A model-based controller will be developed to (a) optimize message
timing, frequency, and content selection, and (b) achieve specified behavior change goals under varying
conditions. We will then deploy that controller with an independent sample of young adults to determine how
more versus less aggressive adaptation strategies over the next six months impact user experience. This study
will contribute a model-based intervention controller and an acceptable adaptation strategy to use in a
personalized adaptive messaging intervention for increasing PA. If successful, it will increase both PA and user
engagement by selecting and timing messages to maximize effects and minimize burden. This approach can
be applied to develop personalized interventions for other behaviors relevant for preventing weight gain,
preserving cardiovascular health, and reducing chronic disease risk.
期刊论文(16)
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DOI:
10.1002/rnc.4968
发表时间:
2020-10-01
期刊:
International journal of robust and nonlinear control
影响因子:
3.9
作者:
[Hojjatinia S, Lagoa CM, Dabbene F]
通讯作者:
Dabbene F
DOI:
10.1038/s41746-021-00532-2
发表时间:
2021-11-23
期刊:
NPJ digital medicine
影响因子:
15.2
作者:
[Hojjatinia S, Daly ER, Hnat T, Hossain SM, Kumar S, Lagoa CM, Nahum-Shani I, Samiei SA, Spring B, Conroy DE]
通讯作者:
Conroy DE
Wearable device adherence among insufficiently-active young adults is independent of identity and motivation for physical activity.
活动不足的年轻人对可穿戴设备的依从性与身体活动的身份和动机无关。
DOI:
10.1007/s10865-023-00444-4
发表时间:
2024
期刊:
Journal of behavioral medicine
影响因子:
3.1
作者:
[Wu,Jingchuan, Olson,JennyL, Brunke-Reese,Deborah, Lagoa,ConstantinoM, Conroy,DavidE]
通讯作者:
Conroy,DavidE
DOI:
10.1093/abm/kaac051
发表时间:
2022-11-05
期刊:
ANNALS OF BEHAVIORAL MEDICINE
影响因子:
3.8
作者:
[Hojjatinia, Sahar, Lee, Alexandra M., Hojjatinia, Sarah, Lagoa, Constantino M., Brunke-Reese, Deborah, Conroy, David E.]
通讯作者:
Conroy, David E.
DOI:
10.1109/cdc40024.2019.9029381
发表时间:
2019-12
期刊:
Proceedings of the ... IEEE Conference on Decision & Control. IEEE Conference on Decision & Control
影响因子:
--
作者:
[Bardakci IE, Lagoa CM]
通讯作者:
Lagoa CM
共 8 条
Efficacy of Precision Text Messaging to Increase Physical Activity in Insufficiently-Active Young Adults
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批准号:10508980
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项目类别:
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资助金额:$72.45万
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财政年份:2022
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负责人:DAVID E. CONROY
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依托单位:
Society of Behavioral Medicine 2022 Annual Meeting & Scientific Sessions
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批准号:10661113
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资助金额:$0.41万
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财政年份:2022
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负责人:DAVID E. CONROY
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Efficacy of sipIT Intervention for Increasing Urine Output in Patients with Urolithiasis
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批准号:10452545
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资助金额:$62.08万
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财政年份:2020
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负责人:DAVID E. CONROY
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依托单位:
Efficacy of sipIT Intervention for Increasing Urine Output in Patients with Urolithiasis
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批准号:10679033
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资助金额:$59.72万
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财政年份:2020
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负责人:DAVID E. CONROY
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依托单位:
Efficacy of sipIT Intervention for Increasing Urine Output in Patients with Urolithiasis
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批准号:10264150
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资助金额:$61.13万
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财政年份:2020
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负责人:DAVID E. CONROY
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依托单位:
Efficacy of sipIT Intervention for Increasing Urine Output in Patients with Urolithiasis
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批准号:10831605
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项目类别:
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资助金额:$40.14万
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财政年份:2020
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负责人:DAVID E. CONROY
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依托单位:
Efficacy of sipIT Intervention for Increasing Urine Output in Patients with Urolithiasis
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批准号:10119792
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项目类别:
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资助金额:$65.07万
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财政年份:2020
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负责人:DAVID E. CONROY
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依托单位:
Phase 1 clinical trial to develop a personalized adaptive text message intervention using control systems engineering tools to increase physical activity in early adulthood
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批准号:9922375
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项目类别:
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资助金额:$59.21万
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财政年份:2018
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负责人:DAVID E. CONROY
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依托单位:
MOTIVATION AND LEARNING
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批准号:7203564
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项目类别:
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资助金额:$1.16万
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财政年份:2005
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负责人:DAVID E. CONROY
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依托单位:
Coach Training to Promote Social Development
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批准号:6610121
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项目类别:
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资助金额:$7.2万
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财政年份:2003
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负责人:DAVID E. CONROY
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依托单位:
Coach Training to Promote Social Development
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批准号:6729010
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项目类别:
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资助金额:$7.2万
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财政年份:2003
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负责人:DAVID E. CONROY
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依托单位:
INDIVIDUAL DIFFERENCE REGULATION OF INTERPERSONAL FIELDS
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批准号:6456924
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项目类别:
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资助金额:$6.81万
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财政年份:2001
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负责人:DAVID E. CONROY
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依托单位:
海外基金