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Barriers to Physical Activity: A Study of Self-Revelation in an Online Community

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The importance of regular physical activity to overall health has been well established, yet adults in the United States are leading increasingly sedentary lives. Research suggests that lowering perceived barriers to exercise is an effective strategy for encouraging physical activity. This article describes the top barriers that emerged from a qualitative analysis of message board traffic from a three-month healthy lifestyle intervention that promoted physical activity and healthy eating. The findings further elaborate known barriers to physical activity—two of which are not reported as key barriers in prior research—and illustrate the value of a grounded approach to studying health and fitness behaviors. Based on our analysis, we identify design considerations for technologies that encourage and support physical activity. Understanding the needs of a population is a critical step in the design process, and this paper offers unique insights for those working in this growing domain.

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  1. 4 and 19 report on the same study

  2. Barriers from the various studies may overlap in some cases due to an inconsistency in their naming (e.g., care-giving duties is often related to a lack of time; lack of energy may be synonymous with too tired).

  3. {link verified 13 January 2011}

  4. Pseudonyms are used for the magazine and health intervention names to protect the identities of message board posters, expert contributors, and the magazine.

  5. Experts, who were arranged by BeFit, included two psychologists, an obstetrician/gynecologist, a registered dietitian, two personal trainers (one was a former professional athlete and the other was also a track and field coach), two gym owners, a personal finance columnist, and a spa chef.

  6. BMI, which has been shown to strongly correlate with body fatness, is calculated based on an individual’s height and weight. It is used to classify people as being underweight (BMI < 18.5 kg/m2), normal weight (18.5 to 24.9), overweight (25.0 to 29.9), or obese (BMI ≥ 30.0).


  1. Dishman, R. K., Exercise adherence. In: Singer, R. N., Murphey, M., and Tennant, L. K. (Eds.), Handbook of sports psychology. Macmillan, NY, 1993.

    Google Scholar 

  2. Sallis, J. F., and Owen, N., Physical activity and behavioral medicine. Sage, Thousand Oaks, 1999.

    Google Scholar 

  3. Trost, S. G., et al., Correlates of adults’ participation in physical activity: Review and update. Med & Science in Sports & Exercise 34(12):1996–2001, 2002.

    Article  Google Scholar 

  4. Booth, M. L., Bauman, A., Owen, N., and Gore, C. J., Physical activity preferences, preferred sources of assistance, and perceived barriers to increased activity among physically active Australians. Preventative Medicine 26(1):131–7, 1997.

    Article  Google Scholar 

  5. Chinn, D. J., et al., Barriers to physical activity and socioeconomic position: implications for health promotion. J Epidem Comm Health 53(3):191–2, 1999.

    Article  Google Scholar 

  6. King, A. C., et al., Personal and environmental factors associated with physical inactivity among different racial-ethnic groups of U.S. middle-ages and older-aged women. Health Psych 19(4):354–64, 2000.

    Article  Google Scholar 

  7. Wilcox, S., et al., Determinants of leisure time physical activity in rural compared with urban older and ethnically diverse women in the United States. J of Epidemiology Community Health 54(9):667–72, 2000.

    Article  Google Scholar 

  8. Janz, N. K., and Becker, M. H., The health belief model: A decade later. Health Educ Quart 11:1–47, 1984.

    Article  Google Scholar 

  9. Ransdell, L. G., et al., Can physical activity interventions change perceived exercise benefits and barriers. Am J of Health Studies 19(4):195–204, 2004.

    Google Scholar 

  10. Sharp, H., Rogers, Y., and Preece, J., Interaction design: Beyond human-computer interaction, 2nd edition. Wiley, West Sussex, 2007.

    Google Scholar 

  11. Bickmore TW, Caruso L, Clough-Gorr K (2005) Acceptance and usability of a relational agent interface by urban older adults. In Proc. CHI’05, pp 1212–1215

  12. Consolvo S, Everitt K, Smith I, Landay JA (2006) Design requirements for technologies that encourage physical activity. In Proc. of CHI’06, pp 457–466

  13. Consolvo S, McDonald DW, Toscos T, Chen MY, Froehlich J, Harrison B, Klasnja P, LaMarca A, LeGrand L, Libby R, Smith I, Landay JA (2008) Activity sensing in the wild: a field trial of UbiFit Garden. In Proc. of CHI’08, pp 1797–1806

  14. Fogg BJ, Eckles D (Eds.) (2007) Mobile persuasion: 20 perspectives on the future of behavior change. Stanford Captology Media

  15. Gasser R, Brodbeck D, Degen M, Luthiger J, Wyss R, Reichlin S (2006) Persuasiveness of a mobile lifestyle coaching application using social facilitation. In Proc of Persuasive ‘06, pp 27–38

  16. Lin JJ, et al. (2006) Fish‘n’Steps: encouraging physical activity with an interactive computer game. In Proc of UbiComp ‘06, pp 261–278

  17. Maitland J, et al. (2006) Increasing the awareness of daily activity levels with pervasive computing. In Proc. of Pervasive Healthcare’06

  18. Mamykina L, Mynatt ED, Davidson PR, Greenblatt D (2008) MAHI: investigation of social scaffolding for reflective thinking in diabetes management. In Proc. of CHI’08, pp 477–86

  19. Toscos T, Faber A, Connelly K, Mutsuddi-Upoma A (2008) Encouraging Physical Activity in Teens: Can technology help reduce barriers to physical activity in adolescent girls. In Proc. of Pervasive Healthcare’08, pp 218–221

  20. Brown, P., et al., Perceived constraints and social support for active leisure among mothers with young children. Leis Sciences 23(3):131–44, 2001.

    Article  Google Scholar 

  21. Brownson, R. C., et al., Environmental and policy determinants of physical activity in the United States. Am J Public Health 91(12):1995–2003, 2001.

    Article  Google Scholar 

  22. Eyler, A. A., et al., Physical activity and minority women: A qualitative study. Health Education & Behavior 25(5):640–51, 1998.

    Article  Google Scholar 

  23. Fahrenwald, N. L., and Walker, S. N., Application of the transtheoretical model of behavior change to the physcial activity behavior of WIC mothers. Public Health Nursing 20(4):307–17, 2003.

    Article  Google Scholar 

  24. Finch, C., Owen, N., and Price, R., Current injury or disability as a barrier to being more physically active. Medicine & Science in Sports & Exercise 33(5):778–82, 2001.

    Article  Google Scholar 

  25. Hall, A. E., Perceived barriers to and benefits of physical activity among Black and White women. Women in Sport & Phys Act Journal 7(2):1–32, 1998.

    Google Scholar 

  26. Sallis, J. F., et al., A multivariate study of determinants of vigorous exercise in a community sample. Preventive Medicine 18(1):20–34, 1989.

    Article  Google Scholar 

  27. Williams, B. R., et al., The effect of a walking program on perceived benefits and barriers to exercise in postmenopausal African American women. Journal of Geriatric Physical Therapy 29(2):43–9, 2006.

    Article  Google Scholar 

  28. Zunft, H. F., et al., Perceived benefits and barriers to physical activity in a nationally representative sample in the European Union. Public Health Nutrition 2(1A):153–60, 1999.

    Article  Google Scholar 

  29. U.S. Dept of Health & Human Svcs, Pub Health Svc, Centers for Dis Control & Prev, Nat’l Ctr for Chronic Dis Prev & Health Prom, & Div of Nut and Phys Act, Promoting physical activity: A guide for community action. Human Kinetics, Champaign, 1999.

    Google Scholar 

  30. Goffman, E., The presentation of self in everyday life. Doubleday Anchor, New York, 1959.

    Google Scholar 

  31. Festinger, L., A theory of cognitive dissonance. Stanford Univ Press, Stanford, 1957.

    Google Scholar 

  32. Landis, J. R., and Koch, G. G., The measurement of observer agreement for categorical data. Biometrics 33:159–74, 1977.

    Article  MATH  MathSciNet  Google Scholar 

  33. Viera, A. J., and Garrett, J. M., Understanding interobserver agreement: The kappa statistic. Family Medicine 37(5):360–3, 2005.

    Google Scholar 

  34. Arguello J, et al. (2006) Talk to Me: Foundations for Successful Individual-Group Interactions in Online Communities. Proc CHI ‘06, pp 959–968

  35. Preece, J., Empathic communities: Balancing emotional and factual communication. Interacting with Computers 12:63–77, 1999.

    Article  Google Scholar 

  36. Farnham S, et al. (2002) HutchWorld: clinical study of computer-mediated social support for cancer patients and their caregivers. Proc. CHI ‘02, pp 375–382

  37. National Institute of Health. Retrieved from

  38. Fogg, B. J., Persuasive technology: Using computers to change what we think and do. Morgan Kaufmann Publishers, San Francisco, 2003.

    Google Scholar 

  39. Christakis, N. A., and Fowler, J. H., The spread of obesity in a large social network over 32 years. New England J of Medicine 357:370–379, 2007.

    Article  Google Scholar 

  40. U.S. Department of Health & Human Services Physical Activity Fundamental to Preventing Disease (2003) Retrieved from

  41. Dworkin, S., “Holding Back”: Negotiating a glass ceiling on women's muscular strength. Sociological Perspectives 44(3):333–50, 2001.

    Article  Google Scholar 

  42. Ionescu A (2010) Bedsider. Presented at Mobile Health, Stanford, CA, USA (May 25, 2010).

  43. Golder SA, Donath J (2004) Social roles in electronic communities. Presented at Association of Internet Researchers 5.0, Brighton, England. Sept. 19–22

  44. Maloney-Krichmar, D., and Preece, J., A multilevel analysis of sociability, usability, and community dynamics in an online health community. ACM Transactions on Computer-Human Interaction 12(2):201–232, 2005.

    Article  Google Scholar 

  45. Benne, K. D., and Sheats, P., Functional roles of group members. J. Social Iss 4(2):41–19, 1948.

    Article  Google Scholar 

  46. Leary, M. R., Tchividjian, L. R., and Kraxberger, B. E., Self-presentation can be hazardous to your health: Impression mangement and health risk. Health Psychology 13(6):461–70, 1994.

    Article  Google Scholar 

  47. Seefeldt, V., Malina, R. M., and Clark, M. A., Factors affecting levels of physical activity in adults. Sports Medicine 32(3):143–68, 2002.

    Article  Google Scholar 

  48. Consolvo S, et al. (2008) Flowers or a Robot Army? Encouraging Awareness & Activity with Personal, Mobile Displays. In Proc. of UbiComp’08, (Sep 2008), pp 54–63.

  49. Rachlin, H., The science of self-control. Harvard University Press, Cambridge, 2000.

    Google Scholar 

  50. Ali-Hasan N, Gavales D, Peterson A, Raw M (2006) Fitster: Social fitness information visualizer. In Extended Abstracts of CHI’06, pp 1795–1800

  51. Toscos T, Connelly K (2010) Chapter 10: Using Behavior Change Theory to Understand and Guide Technological Interventions. In B. Hayes and W. Aspray (Eds.) Health Informatics: A Patient-Centered Approach to Diabetes, MIT Press

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We would like to thank Intel Labs Seattle for supporting this research. We would also like to extend a special thanks to Hooria Bittlingmayer, Jeff Stein, Wanda Pratt, and Steve Gribble.

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Correspondence to Tammy Toscos.

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Toscos, T., Consolvo, S. & McDonald, D.W. Barriers to Physical Activity: A Study of Self-Revelation in an Online Community. J Med Syst 35, 1225–1242 (2011).

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