TY - JOUR
T1 - Exploring Behavioral Markers of Long-Term Physical Activity Maintenance
T2 - A Case Study of System Identification Modeling Within a Behavioral Intervention
AU - Hekler, Eric B.
AU - Buman, Matthew
AU - Poothakandiyil, Nikhil
AU - Rivera, Daniel
AU - Dzierzewski, Joseph M.
AU - Aiken Morgan, Adrienne
AU - McCrae, Christina S.
AU - Roberts, Beverly L.
AU - Marsiske, Michael
AU - Giacobbi, Peter R.
N1 - Funding Information:
This work was supported in part by a Research Opportunity Fund in the College of Health and Human Performance at the University of Florida (PRG), an Age Network Multidisciplinary Research Enhancement grant at the University of Florida (CSM), a Mentorship Opportunity Grant from the Graduate Student Council at the University of Florida (MPB), institutional (T32-AG-020499, JMD; T32-AG-000029, AAM) and individual (F31AG032802, JMD; 1R36AG029664, AAM) training grants awarded to the University of Florida and Duke University School of Medicine, and grants (R21DA024266, DER; K25 DA021173, DER) awarded to Arizona State University.
Funding Information:
This article is published in the Health Education & Behavior supplement, Systems Science Applications in Health Promotion and Public Health, which was supported under contract HHSN276201200329P by the National Institutes of Health Office of Behavioral and Social Sciences Research, the Fogarty International Center, the National Cancer Institute, the National Institute on Dental and Craniofacial Research, and the National Institute on Aging.
PY - 2013
Y1 - 2013
N2 - Efficacious interventions to promote long-term maintenance of physical activity are not well understood. Engineers have developed methods to create dynamical system models for modeling idiographic (i.e., within-person) relationships within systems. In behavioral research, dynamical systems modeling may assist in decomposing intervention effects and identifying key behavioral patterns that may foster behavioral maintenance. The Active Adult Mentoring Program was a 16-week randomized controlled trial of a group-based, peer-delivered physical activity intervention targeting older adults. Time-intensive (i.e., daily) physical activity reports were collected throughout the intervention. We explored differential patterns of behavior among participants who received the active intervention (N = 34; 88% women, 64.1 ± 8.3 years of age) and either maintained 150 minutes/week of moderate to vigorous intensity physical activity (MVPA; n = 10) or did not (n = 24) at 18 months following the intervention period. We used dynamical systems modeling to explore whether key intervention components (i.e., self-monitoring, access to an exercise facility, behavioral initiation training, behavioral maintenance training) and theoretically plausible behavioral covariates (i.e., indoor vs. outdoor activity) predicted differential patterns of behavior among maintainers and nonmaintainers. We found that maintainers took longer to reach a steady-state of MVPA. At week 10 of the intervention, nonmaintainers began to drop whereas maintainers increased MVPA. Self-monitoring, behavioral initiation training, percentage of outdoor activity, and behavioral maintenance training, but not access to an exercise facility, were key variables that explained patterns of change among maintainers. Future studies should be conducted to systematically explore these concepts within a priori idiographic (i.e., N-of-1) experimental designs.
AB - Efficacious interventions to promote long-term maintenance of physical activity are not well understood. Engineers have developed methods to create dynamical system models for modeling idiographic (i.e., within-person) relationships within systems. In behavioral research, dynamical systems modeling may assist in decomposing intervention effects and identifying key behavioral patterns that may foster behavioral maintenance. The Active Adult Mentoring Program was a 16-week randomized controlled trial of a group-based, peer-delivered physical activity intervention targeting older adults. Time-intensive (i.e., daily) physical activity reports were collected throughout the intervention. We explored differential patterns of behavior among participants who received the active intervention (N = 34; 88% women, 64.1 ± 8.3 years of age) and either maintained 150 minutes/week of moderate to vigorous intensity physical activity (MVPA; n = 10) or did not (n = 24) at 18 months following the intervention period. We used dynamical systems modeling to explore whether key intervention components (i.e., self-monitoring, access to an exercise facility, behavioral initiation training, behavioral maintenance training) and theoretically plausible behavioral covariates (i.e., indoor vs. outdoor activity) predicted differential patterns of behavior among maintainers and nonmaintainers. We found that maintainers took longer to reach a steady-state of MVPA. At week 10 of the intervention, nonmaintainers began to drop whereas maintainers increased MVPA. Self-monitoring, behavioral initiation training, percentage of outdoor activity, and behavioral maintenance training, but not access to an exercise facility, were key variables that explained patterns of change among maintainers. Future studies should be conducted to systematically explore these concepts within a priori idiographic (i.e., N-of-1) experimental designs.
KW - dynamical systems
KW - maintenance
KW - physical activity
KW - system identification
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U2 - 10.1177/1090198113496787
DO - 10.1177/1090198113496787
M3 - Article
C2 - 24084400
AN - SCOPUS:84890932011
SN - 1090-1981
VL - 40
SP - 51S-62S
JO - Health Education and Behavior
JF - Health Education and Behavior
IS - 1 SUPPL.
ER -