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

被引:5
作者
Hojjatinia, Sahar [1 ]
Lee, Alexandra M. [2 ]
Hojjatinia, Sarah [3 ]
Lagoa, Constantino M. [1 ]
Brunke-Reese, Deborah [2 ]
Conroy, David E. [2 ,4 ]
机构
[1] Penn State Univ, Sch Elect Engn & Comp Sci, University Pk, PA 16802 USA
[2] Penn State Univ, Dept Kinesiol, University Pk, PA 16802 USA
[3] Aptiv, Adv Safety & User Experience, Troy, MI USA
[4] Northwestern Univ, Dept Prevent Med, Chicago, IL 60611 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
COVID-19; fitness trackers; exercise; patient-specific modeling; social environment; precision medicine;
D O I
10.1093/abm/kaac051
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Background The COVID-19 pandemic adversely impacted physical activity, but little is known about how contextual changes following the pandemic declaration impacted either the dynamics of people's physical activity or their responses to micro-interventions for promoting physical activity. Purpose This paper explored the effect of the COVID-19 pandemic on the dynamics of physical activity responses to digital message interventions. Methods Insufficiently-active young adults (18-29 years; N = 22) were recruited from November 2019 to January 2020 and wore a Fitbit smartwatch for 6 months. They received 0-6 messages/day via smartphone app notifications, timed and selected at random from three content libraries (Move More, Sit Less, and Inspirational Quotes). System identification techniques from control systems engineering were used to identify person-specific dynamical models of physical activity in response to messages before and after the pandemic declaration on March 13, 2020. Results Daily step counts decreased significantly following the pandemic declaration on weekdays (Cohen's d = -1.40) but not on weekends (d = -0.26). The mean overall speed of the response describing physical activity (dominant pole magnitude) did not change significantly on either weekdays (d = -0.18) or weekends (d = -0.21). In contrast, there was limited rank-order consistency in specific features of intervention responses from before to after the pandemic declaration. Conclusions Generalizing models of behavioral dynamics across dramatically different environmental contexts (and participants) may lead to flawed decision rules for just-in-time physical activity interventions. Periodic model-based adaptations to person-specific decision rules (i.e., continuous tuning interventions) for digital messages are recommended when contexts change. Lay Summary Physical inactivity is recognized as one of the major risk factors for cardiovascular disease, diabetes, and many cancers. Most American adults fail to achieve recommended levels of physical activity. Interventions to promote physical activity in young adults are needed to reduce long-term chronic disease risk. The COVID-19 pandemic declaration abruptly changed many individuals' environments and lifestyles. These contextual changes adversely impacted physical activity levels but little is known about how these changes specifically impacted the dynamics of people's physical activity or responses to micro-interventions for promoting physical activity. Using data collected from Fitbit smartwatches before and after the pandemic declaration, we applied tools from control systems engineering to develop person-specific dynamic models of physical activity responses to messaging interventions, and investigated how physical activity dynamics changed from before to after the pandemic declaration. Step counts decreased significantly on weekdays. The average speed of participants' responses to intervention messages did not change significantly, but intervention response dynamics had limited consistency from before to after the pandemic declaration. In short, participants changed how they responded to interventions after the pandemic declaration but the magnitude and patterns of change varied across participants. Person-specific, adaptive interventions can be useful for promoting physical activity when behavioral systems are stimulated to reorganize by external factors.
引用
收藏
页码:1188 / 1198
页数:11
相关论文
共 32 条
[1]  
Barkley Jacob E, 2020, Int J Exerc Sci, V13, P1326
[2]   Correlates of physical activity: why are some people physically active and others not? [J].
Bauman, Adrian E. ;
Reis, Rodrigo S. ;
Sallis, James F. ;
Wells, Jonathan C. ;
Loos, Ruth J. F. ;
Martin, Brian W. .
LANCET, 2012, 380 (9838) :258-271
[3]   COVID-19 Impacts Mental Health Outcomes and Ability/Desire to Participate in Research Among Current Research Participants [J].
Cardel, Michelle I. ;
Manasse, Stephanie ;
Krukowski, Rebecca A. ;
Ross, Kathryn ;
Shakour, Rebecca ;
Miller, Darci R. ;
Lemas, Dominick J. ;
Hong, Young-Rock .
OBESITY, 2020, 28 (12) :2272-2281
[4]   Characterizing and predicting person-specific, day-to-day, fluctuations in walking behavior [J].
Chevance, Guillaume ;
Baretta, Dario ;
Heino, Matti ;
Perski, Olga ;
Olthof, Merlijn ;
Klasnja, Predrag ;
Hekler, Eric ;
Godino, Job .
PLOS ONE, 2021, 16 (05)
[5]   Innovative methods for observing and changing complex health behaviors: four propositions [J].
Chevance, Guillaume ;
Perski, Olga ;
Hekler, Eric B. .
TRANSLATIONAL BEHAVIORAL MEDICINE, 2021, 11 (02) :676-685
[6]   Engineering Person-Specific Behavioral Interventions to Promote Physical Activity [J].
Conroy, David E. ;
Lagoa, Constantino M. ;
Hekler, Eric ;
Rivera, Daniel E. .
EXERCISE AND SPORT SCIENCES REVIEWS, 2020, 48 (04) :170-179
[7]   Personalized models of physical activity responses to text message micro-interventions: A proof-of-concept application of control systems engineering methods [J].
Conroy, David E. ;
Hojjatinia, Sarah ;
Lagoa, Constantino M. ;
Yang, Chih-Hsiang ;
Lanza, Stephanie T. ;
Smyth, Joshua M. .
PSYCHOLOGY OF SPORT AND EXERCISE, 2019, 41 :172-180
[8]   A Daily Process Analysis of Intentions and Physical Activity in College Students [J].
Conroy, David E. ;
Elavsky, Steriani ;
Doerksen, Shawna E. ;
Maher, Jaclyn P. .
JOURNAL OF SPORT & EXERCISE PSYCHOLOGY, 2013, 35 (05) :493-502
[9]  
Division of Nutrition Physical Activity and Obesity National Center for Chronic Disease Prevention and Health Promotion, 2021, TRENDS M 2008 PHYS A
[10]   Trends in Adherence to the Physical Activity Guidelines for Americans for Aerobic Activity and Time Spent on Sedentary Behavior Among US Adults, 2007 to 2016 [J].
Du, Yang ;
Liu, Buyun ;
Sun, Yangbo ;
Snetselaar, Linda G. ;
Wallace, Robert B. ;
Bao, Wei .
JAMA NETWORK OPEN, 2019, 2 (07)