The effect of a wearable physical activity monitor (Fitbit One) on physical activity behaviour in women: A pilot study
Introducion. With wearable technology topping both the 2016 and 2017 American College of Sports Medicine (ACSM) Fitness Trends survey, research in this area is needed to help determine the importance of such devices. Purpose. To determine the effect of wearing a popular, commercially-available wearable activity monitor (i.e., Fitbit One) upon physical activity behaviour relative to a group who was not utilizing such a monitor. Methods. A sample of 19 healthy adult women completed the Human Activity Profile survey to assess physical activity behaviour pre – and post – intervention. For the intervention, nine participants received a Fitbit One accelerometer to wear for six weeks, while the remaining participants (control group) did not receive an accelerometer. Results. There were no significant differences (p ≥ 0.16) in physical activity. However, the control group reduced physical activity by ≥20% from pre to post intervention whereas the Fitbit One group was largely unchanged (0.5% - 2.4% decrease). Conclusion. While wearing a physical activity monitor did not increase physical activity behaviour it may help maintain it.
Araiza, P., Hewes, H., Gashetewa, C., Vella, AC., & Burge RM. (2006). Efficacy of a pedometer – based physical activity program on parameters of diabetes control in type 2 diabetes mellitus. Metabolism, 55(10), 1382-1387. https://doi.org/10.1016/j.metabol.2006.06.009
Bastone, A., Moreira, B., Vieira, R., Kirkwood, R., Dias, J., & Dias, R. (2014). Validation of the Human Activity Profile Questionnaire as a Measure of Physical Activity Levels in Older Community-Dwelling Women. Journal Of Aging And Physical Activity, 22(3), 348-356. https://doi.org/10.1123/JAPA.2012-0283
Bilek, LD., Venema, DM., Camp, KL., Lyden, ER., & Meza, JL. (2005). Evaluation of the human activity profile for use with persons with arthritis. Arthritis Care and Research, 53(5). https://doi.org/10.1002/art.21455
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences. New York, NY: Lawrence Erlbaum Associates.
Conroy, DE., Hyde, AL., Doerksen, SE. & Ribeiro, NF. (2010). Implicit Attitudes and Explicit Motivation Prospectively Predict Physical Activity. Annals of Behavior Medicine, 39, 112-118. https://doi.org/10.1007/s12160-010-9161-0
Daughton, DM., Fix, AJ., Kass, I., McDonald, T., & Stevens C. (1983). Relationship between a pulmonary function test (FEV1) and the ADAPT quality -of- life scale. Percept Motor Skills, 57, 359-362. https://doi.org/10.2466/pms.1922.214.171.1249
Diaz, KM., Krupka, DJ., Chang, MJ., et al. (2016). Validation of the Fitbit One® for physical activity measurement at an upper torso attachment site. BMC Research Notes, 9, 1-9. https://doi.org/10.1186/s13104-016-2020-8
Dumith, C. S. Hallal, C. P. Reis, S. R., & Kohl W. H. III. (2011). Worldwide prevalence of physical inactivity and its association with human development index in 76 countries. Preventative Medicine, 53, 24-28. https://doi.org/10.1016/j.ypmed.2011.02.017
Ferguson, T., Rowlands, AV., Olds, T., & Maher, C. (2015). The validity of consumer-level, activity monitors in healthy adults worn in free-living conditions: a cross-sectional study. International Journal of Behavioral Nutrition & Physical Activity, 12, 1-9. https://doi.org/10.1186/s12966-015-0201-9
Fishman, E., Steeves, J., Zipunnikov, V., Koster, A., Berrigan, D., Harris, T., & Murphy, R. (2016). Association between Objectively Measured Physical Activity and Mortality in NHANES. Medicine and Science in Sports and Exercise 48(7), 1303-1311. https://doi.org/10.1249/MSS.0000000000000885
Jakicic, JM, Davis, KK, Rogers, RJ, et al. (2016). Effect of Wearable Technology Combined With a Lifestyle Intervention on Long-term Weight Loss: The IDEA Randomized Clinical Trial. JAMA, 316(11), 1161-1171. https://doi.org/10.1001/jama.2016.12858
Kirsch, I. (1985). Response expectancy as a determinant of experience and behavior. American Psychologist, 40(11), 1189-1202. https://doi.org/10.1037/0003-066X.40.11.1189
Kluger, AN., & DeNisi, A. (1996). The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin, 119(2), 254-284. https://doi.org/10.1037/0033-2909.119.2.254
Lee, JM, Kim Y., & Welk GJ. (2014). Validity of consumer based physical activity monitors. Medicine and Science in Sports and Exercise, 46(9), 1840-48. https://doi.org/10.1249/MSS.0000000000000287
Litt, MD., Iannotti, JR., & Wang, J. (2011). Motivations for adolescent physical activity. Journal of Physical Activity and Health, 8, 220-226. https://doi.org/10.1123/jpah.8.2.220
Lyons, E., Lewis, Z., Mayrsohn, B., & Rowland, J. Behavior change techniques implemented in electronic lifestyle activity monitors: A Systematic Content Analysis. Journal of Medical Internet Research, 16(8): e192, 2014. https://doi.org/10.2196/jmir.3469
McMinn, D., Rowe, AD., Stark, M., & Nicol, L. (2010). Validity of the new Lifestyles NL-1000 accelerometer for measuring time spent in moderate-to-vigorous physical activity in school settings. Measurement in Physical Education and Exercise Science, 14, 67-78. https://doi.org/10.1080/10913671003715516
Nelson, MB., Kaminsky, LA., Dickin, DC., & Montoye, AH. (2016). Validity of Consumer-Based Physical Activity Monitors for Specific Activity Types. Medicine and Science in Sports and Exercise, 48(8), 1619-28. https://doi.org/10.1249/MSS.0000000000000933
Nowicki, M., Murlikiewicz, K., & Jagodizinska, M. Pedometers as a means to increase spontaneous physical activity in hemodialysis patients. Journal of Nephrology, 23(3), 297-305, 2010.
Paschali, A., Goodrick, G., Kalantzi-Azizi, A., Paadatou, D., & Balasubramanyam, A. (2005). Accelerometer feedback to promote physical activity in adults with Type 1. diabetes: A pilot study. Perceptual and Motor Skills, 100(1), 61-68. https://doi.org/10.2466/pms.100.1.61-68
Power, GT., Ullrich-French, CS., Steele, MM., Daratha, BK., & Bindler, CR. (2011). Cardiovascular fitness, and physically active adolescents' motivations for activity: A self-determination theory approach. Psychology of Sport and Exercise, 12, 593-598. https://doi.org/10.1016/j.psychsport.2011.07.002
Piwek, L., Ellis, DA., Andrews, S., & Joinson, A. (2016). The Rise of Consumer Health Wearables: Promises and Barriers. PLoS Medicine, 13(2), e1001953. https://doi.org/10.1371/journal.pmed.1001953
Preston, HS., & Stokes, A. (2011). Contribution of obesity to international differences in life expectancy. American Journal of Public Health, 101(11), 2137-2143. https://doi.org/10.2105/AJPH.2011.300219
Silva, P., Mota, J., Esliger, D., Welk, G. (2010). Technical reliability assessment of the GT1M accelerometer. Measurement in Physical Education and Exercise Science, 14, 79-91. https://doi.org/10.1080/10913671003715524
Teixeira-Salmela, FL., Devaraj, R., & Olney, JS. (2007). Validation of the human activity profile in stroke: a comparison of observed, proxy and self-reported scores. Disability and Rehabilitation, 29(19), 1518-1524. https://doi.org/10.1080/09638280601055733
Takacs, J., Pollock, C., Guenther, J., Bahar, M., Napier, C., & Hunt, M. (2014). Validation of the Fitbit One activity monitor device during treadmill walking. Journal of Science and Medicine In Sport, 17(5), 496-500. https://doi.org/10.1016/j.jsams.2013.10.241
Thompson, WR. (2015). Worldwide survey of fitness trends for 2016: 10th anniversary edition. ACSM's Health & Fitness Journal, 19(6), 9-18.
Thompson, WR. (2016). Worldwide survey of fitness trends for 2017. ACSM's Health & Fitness Journal, 20(6), 8-17.
Copyright (c) 2017 Journal of Human Sport and Exercise
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.