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Phase 1 clinical trial to develop a personalized adaptive text message intervention using control systems engineering tools to increase physical activity in early adulthood

第一阶段临床试验，利用控制系统工程工具开发个性化自适应短信干预，以增加成年早期的体力活动

基本信息

批准号：
10152695
负责人：
DAVID E. CONROY
金额：
$ 55.72万
依托单位：
PENNSYLVANIA STATE UNIVERSITY, THE
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：
2018-07-01 至 2023-04-30
项目状态：
已结题

项目摘要

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.

项目总结

项目成果

期刊论文数量（16）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Identification of switched autoregressive exogenous systems from large noisy datasets.

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

Dynamic models of stress-smoking responses based on high-frequency sensor data.

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

Physical Activity Dynamics During a Digital Messaging Intervention Changed After the Pandemic Declaration.

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.

Distributionally Robust Portfolio Optimization.