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Gym Usage Behavior & Desired Digital Interventions: An Empirical Study

Published: 02 February 2021 Publication History

Abstract

Understanding individual's exercise motives, participation patterns in a gym and reasons for dropout are essential for designing strategies to help gym-goers with long-term exercise adherence. In this work, we derive insights on various exercise-related behaviors of gym-goers, including evidence of a significant number of individuals exhibiting early dropout and also describing their attitudes towards digital technologies for sustained gym participation. By utilizing gym visitation data logs of 6513 individuals over a longitudinal period of 16 months in a campus gym, we show the retention and dropout rates of gym-goers. Our data indicates that 32% of the people quit their gym activity after initial 1 or 2 visits and about 65% of the users have less than 10 visits during the 16 months period. From this data, we also observed that people attending gym in a group and following a regular visiting time to the gym have a lower chance of ceasing gym activity. Further by surveying 615 individuals across varying demographics, we uncover the key reasons for dropout to be "lack of knowledge in using gym equipment" and "lack of access to a personal trainer", besides the prominent reason of "lack of time". Our survey also indicates the propensity of individuals towards using digital technologies (e.g., fitness apps) to track their gym activity. Somewhat surprisingly, our survey reveals a disinclination among individuals to use obtrusive wearable-based solutions in a gym, with 60% of them preferring a less-invasive and more convenient approach of machine-attached sensors for automated tracking of gym exercises.

References

[1]
James J Annesi. 2001. Effects of music, television, and a combination entertainment system on distraction, exercise adherence, and physical output in adults. Canadian Journal of Behavioural Science/Revue canadienne des sciences du comportement 33, 3 (2001), 193.
[2]
Martin J Barwood, Neil JV Weston, Richard Thelwell, and Jennifer Page. 2009. A motivational music and video intervention improves high-intensity exercise performance. Journal of sports science & medicine 8, 3 (2009), 435.
[3]
BG Berger. 2002. Pargman, d., & Weinberg, RS (2002). Foundations of exercises psychology (2002).
[4]
Fabio Buttussi, Luca Chittaro, and Daniele Nadalutti. 2006. Bringing mobile guides and fitness activities together: a solution based on an embodied virtual trainer. In Proceedings of the 8th conference on Human-computer interaction with mobile devices and services. ACM, 29--36.
[5]
Keng-Hao Chang, Mike Y Chen, and John Canny. 2007. Tracking free-weight exercises. In International Conference on Ubiquitous Computing. Springer, 19--37.
[6]
Simon Condliffe, Ebru Işgm, and Brynne Fitzgerald. 2017. Get thee to the gym! A field experiment on improving exercise habits. Journal of behavioral and experimental economics 70 (2017), 23--32.
[7]
Nick Crossley. 2006. In the gym: Motives, meaning and moral careers. Body & Society 12, 3 (2006), 23--50.
[8]
Sara J Czaja, Neil Charness, Arthur D Fisk, Christopher Hertzog, Sankaran N Nair, Wendy A Rogers, and Joseph Sharit. 2006. Factors predicting the use of technology: findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE). Psychology and aging 21, 2 (2006), 333.
[9]
Han Ding, Longfei Shangguan, Zheng Yang, Jinsong Han, Zimu Zhou, Panlong Yang, Wei Xi, and Jizhong Zhao. 2015. Femo: A platform for free-weight exercise monitoring with rfids. In Proc. of ACM SenSys'15. ACM, 141--154.
[10]
Thomas Fritz, Elaine M Huang, Gail C Murphy, and Thomas Zimmermann. 2014. Persuasive technology in the real world: a study of long-term use of activity sensing devices for fitness. In Proc. of CHI'14. ACM.
[11]
Shannon E Gray and Caroline F Finch. 2015. The causes of injuries sustained at fitness facilities presenting to Victorian emergency departments-identifying the main culprits. Injury epidemiology 2, 1 (2015), 6.
[12]
Timothy C Havens, Gregory L Alexander, Carmen Abbott, James M Keller, Marjorie Skubic, and Marilyn Rantz. 2009. Contour tracking of human exercises. In Computational Intelligence for Visual Intelligence, 2009. CIVI'09. IEEE Workshop on. IEEE, 22--28.
[13]
Jennifer L Huberty, Lynda B Ransdell, Cara Sidman, Judith A Flohr, Barry Shultz, Onie Grosshans, and Lynne Durrant. 2008. Explaining long-term exercise adherence in women who complete a structured exercise program. Research Quarterly for exercise and Sport 79, 3 (2008), 374--384.
[14]
Jefit Inc. [US]. [n.d.]. JEFIT. https://www.jefit.com/; Last Accessed: May 2019.
[15]
L Karvitz. 2011. Exercise Motivation: What Starts and Keeps People Exercising. University of New Mexico (2011).
[16]
Navin Kaushal and Ryan E Rhodes. 2015. Exercise habit formation in new gym members: a longitudinal study. Journal of Behavioral Medicine 38, 4 (2015), 652--663.
[17]
Rushil Khurana, Karan Ahuja, Zac Yu, Jennifer Mankoff, Chris Harrison, and Mayank Goel. 2018. GymCam: Detecting, Recognizing and Tracking Simultaneous Exercises in Unconstrained Scenes. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, 4 (2018), 185.
[18]
Abby C King, Eric B Hekler, Lauren A Grieco, Sandra J Winter, Jylana L Sheats, Matthew P Buman, Banny Banerjee, Thomas N Robinson, and Jesse Cirimele. 2016. Effects of three motivationally targeted mobile device applications on initial physical activity and sedentary behavior change in midlife and older adults: a randomized trial. PloS one 11, 6 (2016), e0156370.
[19]
Emily Knight, Melanie I Stuckey, Harry Prapavessis, and Robert J Petrella. 2015. Public health guidelines for physical activity: is there an app for that? A review of android and apple app stores. JMIR mHealth and uHealth 3, 2 (2015), e43.
[20]
Liqian Ma, Qianru Sun, Stamatios Georgoulis, Luc Van Gool, Bernt Schiele, and Mario Fritz. 2018. Disentangled Person Image Generation. In 2018 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2018, Salt Lake City, UT, USA, June 18-22, 2018. 99--108.
[21]
Behavioral Medicine. 2010. Automatic and motivational correlates of physical activity: Does intensity moderate the relationship?. In Proceedings of the 2013 conference on Computer supported cooperative work companion, Vol. 36. 44--52.
[22]
Susan Michie, Michelle Richardson, Marie Johnston, Charles Abraham, Jill Francis, Wendy Hardeman, Martin P Eccles, James Cane, and Caroline E Wood. 2013. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Annals of behavioral medicine 46, 1 (2013), 81--95.
[23]
Dan Morris, T Scott Saponas, Andrew Guillory, and Ilya Kelner. 2014. RecoFit: using a wearable sensor to find, recognize, and count repetitive exercises. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 3225--3234.
[24]
David T Neal, Wendy Wood, Jennifer S Labrecque, and Phillippa Lally. 2012. How do habits guide behavior? Perceived and actual triggers of habits in daily life. Journal of Experimental Social Psychology 48, 2 (2012), 492--498.
[25]
Taiwoo Park, Uichin Lee, Bupjae Lee, Haechan Lee, Sanghun Son, Seokyoung Song, and Junehwa Song. 2013. ExerSync: interpersonal synchrony in social exergames. In Proceedings of the 2013 conference on Computer supported cooperative work companion. ACM, 27--30.
[26]
Misha Patel and Aisling Ann O'Kane. 2015. Contextual influences on the use and non-use of digital technology while exercising at the gym. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, 2923--2932.
[27]
Lisa Pridgeon and Sarah Grogan. 2012. Understanding exercise adherence and dropout: an interpretative phenomenological analysis of men and women's accounts of gym attendance and non-attendance. Qualitative research in sport, Exercise and Health 4, 3 (2012), 382--399.
[28]
Md Fazlay Rabbi, Taiwoo Park, Biyi Fang, Mi Zhang, and Youngki Lee. 2018. When Virtual Reality Meets IoT in the Gym: Enabling Immersive and Interactive Machine Exercise. ACM.
[29]
Colin D Rehm, José L Peñalvo, Ashkan Afshin, and Dariush Mozaffarian. 2016. Dietary intake among US adults, 1999--2012. Jama 315, 23 (2016), 2542--2553.
[30]
Ariel Rubin and Jacques Ophoff. 2018. Investigating Adoption Factors of Wearable Technology in Health and Fitness. In 2018 Open Innovations Conference (OI). IEEE, 176--186.
[31]
Stephanie Schoeppe, Stephanie Alley, Wendy Van Lippevelde, Nicola A Bray, Susan L Williams, Mitch J Duncan, and Corneel Vandelanotte. 2016. Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour: a systematic review. International Journal of Behavioral Nutrition and Physical Activity 13, 1 (2016), 127.
[32]
Christian Seeger, Kristof Van Laerhoven, and Alejandro Buchmann. 2015. My-HealthAssistant: An event-driven middleware for multiple medical applications on a smartphone-mediated body sensor network. IEEE journal of biomedical and health informatics 19, 2 (2015), 752--760.
[33]
Rebecca A Seguin, Christina D Economos, Ruth Palombo, Raymond Hyatt, Julia Kuder, and Miriam E Nelson. 2010. Strength training and older women: a cross-sectional study examining factors related to exercise adherence. Journal of aging and physical activity 18, 2 (2010), 201--218.
[34]
Chenguang Shen, Bo-Jhang Ho, and Mani Srivastava. 2018. Milift: Efficient smartwatch-based workout tracking using automatic segmentation. IEEE Transactions on Mobile Computing 17, 7 (2018), 1609--1622.
[35]
Statista 2019. [n.d.]. U.S. fitness center / health club memberships 2000--2017. https://www.statista.com/statistics/236123/us-fitness-center--health-club-memberships/; Last Accessed: May 2019.
[36]
Maarten Stiggelbout, Marijke Hopman-Rock, Erwin Tak, Lilian Lechner, and Willem van Mechelen. 2005. Dropout from exercise programs for seniors: a prospective cohort study. Journal of Aging and Physical Activity 13, 4 (2005), 409--421.
[37]
Kelley Strohacker, Omar Galarraga, and David M Williams. 2013. The impact of incentives on exercise behavior: a systematic review of randomized controlled trials. Annals of Behavioral Medicine 48, 1 (2013), 92--99.
[38]
Stewart G Trost, Neville Owen, Adrian E Bauman, James F Sallis, and Wendy Brown. 2002. Correlates of adults' participation in physical activity: review and update. Medicine & Science in Sports & Exercise 34, 12 (2002), 1996--2001.
[39]
Eduardo Velloso, Andreas Bulling, Hans Gellersen, Wallace Ugulino, and Hugo Fuks. 2013. Qualitative activity recognition of weight lifting exercises. In Proc. of ACM AH'13.
[40]
Vimo Labs Inc. [n.d.]. TrackMyFitness. http://trackmy.fit; Last Accessed: May 2019.
[41]
Diane E Whaley and Agnes F Schrider. 2005. The process of adult exercise adherence: Self-perceptions and competence. The Sport Psychologist 19, 2 (2005), 148--163.
[42]
Janet Withall, Russell Jago, and Kenneth R Fox. 2011. Why some do but most don't. Barriers and enablers to engaging low-income groups in physical activity programmes: a mixed methods study. BMC public health 11, 1 (2011), 507.
[43]
George Zarotis, Ioannis Athanailidis, Vasileia Arvanitidou, and Christos Mourtzios. 2017. Age-specific reasons for dropping out of the Fitness-Sport. Journal of Physical Education and Sport 17, 2 (2017), 916.

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  1. Gym Usage Behavior & Desired Digital Interventions: An Empirical Study

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      cover image ACM Other conferences
      PervasiveHealth '20: Proceedings of the 14th EAI International Conference on Pervasive Computing Technologies for Healthcare
      May 2020
      446 pages
      ISBN:9781450375320
      DOI:10.1145/3421937
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      New York, NY, United States

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      Published: 02 February 2021

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      Author Tags

      1. Digital Intervention
      2. Gym Exercises
      3. Personalized Coaching
      4. Physical Activity
      5. Quantified Self
      6. Retention

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      • National Research Foundation, Singapore

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      PervasiveHealth '20 Paper Acceptance Rate 55 of 116 submissions, 47%;
      Overall Acceptance Rate 55 of 116 submissions, 47%

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