Measuring and Influencing Physical Activity with Smartphone Technology: A Systematic Review
Rapid developments in technology have encouraged the use of smartphones in physical activity research, although little is known regarding their effectiveness as measurement and intervention tools.
This study systematically reviewed evidence on smartphones and their viability for measuring and influencing physical activity.
Research articles were identified in September 2013 by literature searches in Web of Knowledge, PubMed, PsycINFO, EBSCO, and ScienceDirect.
The search was restricted using the terms (physical activity OR exercise OR fitness) AND (smartphone* OR mobile phone* OR cell phone*) AND (measurement OR intervention). Reviewed articles were required to be published in international academic peer-reviewed journals, or in full text from international scientific conferences, and focused on measuring physical activity through smartphone processing data and influencing people to be more active through smartphone applications.
Study Appraisal and Synthesis Methods
Two reviewers independently performed the selection of articles and examined titles and abstracts to exclude those out of scope. Data on study characteristics, technologies used to objectively measure physical activity, strategies applied to influence activity; and the main study findings were extracted and reported.
A total of 26 articles (with the first published in 2007) met inclusion criteria. All studies were conducted in highly economically advantaged countries; 12 articles focused on special populations (e.g. obese patients). Studies measured physical activity using native mobile features, and/or an external device linked to an application. Measurement accuracy ranged from 52 to 100 % (n = 10 studies). A total of 17 articles implemented and evaluated an intervention. Smartphone strategies to influence physical activity tended to be ad hoc, rather than theory-based approaches; physical activity profiles, goal setting, real-time feedback, social support networking, and online expert consultation were identified as the most useful strategies to encourage physical activity change. Only five studies assessed physical activity intervention effects; all used step counts as the outcome measure. Four studies (three pre–post and one comparative) reported physical activity increases (12–42 participants, 800–1,104 steps/day, 2 weeks–6 months), and one case-control study reported physical activity maintenance (n = 200 participants; >10,000 steps/day) over 3 months.
Smartphone use is a relatively new field of study in physical activity research, and consequently the evidence base is emerging.
Few studies identified in this review considered the validity of phone-based assessment of physical activity. Those that did report on measurement properties found average-to-excellent levels of accuracy for different behaviors. The range of novel and engaging intervention strategies used by smartphones, and user perceptions on their usefulness and viability, highlights the potential such technology has for physical activity promotion. However, intervention effects reported in the extant literature are modest at best, and future studies need to utilize randomized controlled trial research designs, larger sample sizes, and longer study periods to better explore the physical activity measurement and intervention capabilities of smartphones.
- 4.Global Mobile Statistics 2013 Home [online]. Available from URL: http://mobithibking.com/mobile-marketing-tool/latest-mobile-stats. Accessed 2013 Jun.
- 5.Vital Wave Consulting. mHealth for development: The opportunity of mobile technology for healthcare in the developing world. Washington, DC, and Berskshire, UK: UN Fundation-Vodafone Fundation Partnership, 2009.Google Scholar
- 6.International Data Corporation [online]. http://www.idc.com/getdoc.jsp?containerId=prUS24302813. Accessed 2013 Nov.
- 7.Intille SS, Lester J, Sallis JF, et al. New horizons in sensor development. Med Sci Sports Exerc 2012; 44 (Suppl. 1): 24–31S.Google Scholar
- 10.Lau PWC, Lau EY, Wong DP, et al. A systematic review of information and communication technology-based interventions for promoting physical activity behavior change in children and adolescents. J Med Internet Res 2011;13(3).Google Scholar
- 13.Ketabdar H, Lyra M. System and methodology for using mobile phones in live remote monitoring of physical activities. In: Proceedings of the IEEE International Symposium on Technology and Society; 2010 Jun 7–9; Wollongong (NSW). IEEE publications; 2010. p. 350–6.Google Scholar
- 14.Sheng Zhong SZ, Li Wang LW, Ana M. Bernardos, et al. An accurate and adaptive pedometer integrated in mobile health application. In: Proceedings of the IET International Conference on Wireless Sensor Network; 2010 Nov 15–17; Beijing (CN). IET Conference Publications; 2010. p. 78–83.Google Scholar
- 16.He Yi, Li Ye. Physical activity recognition utilizing the built-in kinematic sensors of a smartphone. Int J Distrib Sens Netw. 2013;2013:10.Google Scholar
- 18.Anderson I, Maitland J, Sherwood S, et al. Shakra: Tracking and sharing daily activity levels with unaugmented mobile phones. Mob Netw Appl. 2007; 12:185-199.Google Scholar
- 22.Gao C, Kong F, Tan J. HealthAware: Tackling obesity with health aware smart phone systems. In: Proceedings of the IEEE International Conference on Robotics and Biomimetics; 2009 Dec 19–23; Guilin (CN). IEEE publications; 2009. p. 1549–54.Google Scholar
- 26.Toscos T, Faber A, Connelly K, et al. Encouraging physical activity in teens can technology help reduce barriers to physical activity in adolescent girls? In: Proceedings of the Second International Conference on Pervasive Computing Technologies for Healthcare; 2008 Jan 30–Feb 1; Tempere (FI). Pervasive Health. 2008; p. 218–21.Google Scholar
- 29.Mattila J, Ding H, Mattila E, et al. Mobile tools for home-based cardiac rehabilitation based on heart rate and movement activity analysis. In: Proceedings of theAnnual International Conference of the IEEE Engineering in Medicine and Biology Society; 2009 Sept 3–6; Minneapolis (MN). IEEE publications; 2009. p. 6448–52.Google Scholar
- 30.Mattila E, Parkka J, Hermersdorf M, et al. Mobile diary for wellness management—results on usage and usability in two user studies. IEEE Trans Inform Technol Biomed. 2008; 2(4).Google Scholar
- 35.Khalil A, Glal S. StepUp: A step counter mobile application to promote healthy lifestyle. In: Proceedings of the International Conference on the current Trends in Information Technology; 2009 Dec 15–16; Dubai (UAE). IEEE publications; 2009. p. 208–12.Google Scholar
- 37.Kirwan M, Duncan MJ, Vandelanotte C, et al. Using smartphone technology to monitor physical activity in the 10,000 steps program: a matched case-control trial. J Med Internet Res 2012;14 (2).Google Scholar
- 39.The World Bank. Countries and Economies [online]. http://data.worldbank.org/country. Accessed 2013 Jun.
- 43.Intille SS, Albinali F, Mota S, et al. Design of a wearable physical activity monitoring system using mobile phones and accelerometers. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology and Society; 2011 Aug 30–Sept 3; Boston (MA). IEEE Conference Publications. 2011; p. 3636–3639.Google Scholar