Using a Mobile Phone App to Analyze the Relationship Between Planned and Performed Physical Activity in University Students: Observational Study
- PMID: 33913812
- PMCID: PMC8120422
- DOI: 10.2196/17581
Using a Mobile Phone App to Analyze the Relationship Between Planned and Performed Physical Activity in University Students: Observational Study
Abstract
Background: The relationship between intention and behavior has been well researched, but most studies fail to capture dynamic, time-varying contextual factors. Ecological momentary assessment through mobile phone technology is an innovative method for collecting data in real time, including time-use data. However, only a limited number of studies have examined day-level plans to be physically active and subsequent physical activity behavior using real-time time-use data to better understand this relationship.
Objective: This study aims to examine whether plans to be physically active (recorded in advance on an electronic calendar) were associated with objectively assessed physical activity (accelerometry), to identify activities that replaced planned periods of physical activity by using the mobile app Life in a Day (LIAD), and to test the feasibility and acceptability of LIAD for collecting real-time time-use data.
Methods: The study included 48 university students who were randomly assigned to 1 of 3 protocols, which were defined by 1, 3, or 5 days of data collection. Participants were asked to record their planned activities on a Google Calendar and were provided with mobile phones with LIAD to complete time-use entries in real time for a set of categories (eg, exercise or sports, eating or cooking, school, or personal care). Participants were instructed to wear an accelerometer on their nondominant wrist during the protocol period. A total of 144 days of protocol data were collected from the 48 participants.
Results: Protocol data for 123 days were eligible for analysis. A Fisher exact test showed a statistically significant association between plans and physical activity behavior (P=.02). The congruence between plans and behavior was fair (Cohen κ=0.220; 95% CI 0.028-0.411). Most participants did not plan to be active, which occurred on 75.6% (93/123) of days. Of these 93 days, no physical activity occurred on 76 (81.7%) days, whereas some physical activity occurred on 17 (18.3%) days. On the remaining 24.4% (30/123) of days, some physical activity was planned. Of these 30 days, no physical activity occurred on 18 (60%) days, whereas some physical activity occurred on 12 (40%) days. LIAD data indicated that activities related to screen time most often replaced planned physical activity, whereas unplanned physical activity was often related to active transport. Feasibility analyses indicated little difficulty in using LIAD, and there were no significant differences in feasibility by protocol length.
Conclusions: Consistent with previous literature, physical activity plans and physical activity behaviors were linked, but not strongly linked. LIAD offers insight into the relationship between plans and behavior, highlighting the importance of active transport for physical activity and the influence of screen-related behaviors on insufficient physical activity. LIAD is a feasible and practical method for collecting time-use data in real time.
Keywords: intention-behavior relationship; mobile phone application; physical activity.
©Matthew T Stewart, Taylor Nezich, Joyce M Lee, Rebecca E Hasson, Natalie Colabianchi. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 29.04.2021.
Conflict of interest statement
Conflicts of Interest: MTS was supported by grant support under award HL137731. JML was a part of the Medical Advisory Board for GoodRX. During the past 5 years, NC has received grant support from the National Institutes of Health under awards HD101752, HL137731, AG057540, HL132979, NS092706, HL091002, CA188481, CA184478, and CA164137; from the Department of Defense under award 11811976; from the Clark R. Smith Family Foundation; and from the University of Michigan. She also received a speaking fee from the University of Alabama at Birmingham. The remaining authors declare no conflicts of interest.
Figures
Similar articles
-
Feasibility and Performance Test of a Real-Time Sensor-Informed Context-Sensitive Ecological Momentary Assessment to Capture Physical Activity.J Med Internet Res. 2016 Jun 1;18(6):e106. doi: 10.2196/jmir.5398. J Med Internet Res. 2016. PMID: 27251313 Free PMC article.
-
A Mobile Ecological Momentary Assessment Tool (devilSPARC) for Nutrition and Physical Activity Behaviors in College Students: A Validation Study.J Med Internet Res. 2016 Jul 27;18(7):e209. doi: 10.2196/jmir.5969. J Med Internet Res. 2016. PMID: 27465701 Free PMC article.
-
Studying Microtemporal, Within-Person Processes of Diet, Physical Activity, and Related Factors Using the APPetite-Mobile-App: Feasibility, Usability, and Validation Study.J Med Internet Res. 2021 Jul 5;23(7):e25850. doi: 10.2196/25850. J Med Internet Res. 2021. PMID: 34342268 Free PMC article.
-
Compliance With Mobile Ecological Momentary Assessment Protocols in Children and Adolescents: A Systematic Review and Meta-Analysis.J Med Internet Res. 2017 Apr 26;19(4):e132. doi: 10.2196/jmir.6641. J Med Internet Res. 2017. PMID: 28446418 Free PMC article.
-
Can Mobile Phone Apps Influence People's Health Behavior Change? An Evidence Review.J Med Internet Res. 2016 Oct 31;18(11):e287. doi: 10.2196/jmir.5692. J Med Internet Res. 2016. PMID: 27806926 Free PMC article. Review.
Cited by
-
Using a smartphone application to capture daily work activities: a longitudinal pilot study in a farming population.Ann Work Expo Health. 2023 Aug 9;67(7):895-906. doi: 10.1093/annweh/wxad034. Ann Work Expo Health. 2023. PMID: 37382523 Free PMC article.
References
-
- Warburton DE, Nicol CW, Bredin SS. Health benefits of physical activity: the evidence. Can Med Assoc J. 2006 Mar 14;174(6):801–9. doi: 10.1503/cmaj.051351. http://www.cmaj.ca/cgi/pmidlookup?view=long&pmid=16534088 - DOI - PMC - PubMed
-
- Blackwell DL, Clarke TC. State variation in meeting the 2008 federal guidelines for both aerobic and muscle-strengthening activities through leisure-time physical activity among adults aged 18-64: United States, 2010-2015. Natl Health Stat Report. 2018 Jun;(112):1–22. http://www.cdc.gov/nchs/data/nhsr/nhsr112.pdf - PubMed
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources