Personal and Ubiquitous Computing

, Volume 18, Issue 7, pp 1705–1719 | Cite as

Deconstructing gamification: evaluating the effectiveness of continuous measurement, virtual rewards, and social comparison for promoting physical activity

  • Oren ZuckermanEmail author
  • Ayelet Gal-Oz
Original Article


Game design elements are often implemented in persuasive systems aimed to promote physical activity, a process called “gamification.” Gamification is believed to motivate users to become more active, and is commonly implemented in commercial products. However, relatively few studies rigorously evaluated the effectiveness of gamification, and they yielded contradicting findings. We set out to evaluate the effectiveness of virtual rewards and social comparison—two game elements prevalent in persuasive systems. We developed a research prototype, called “StepByStep,” aimed to promote routine walking. We created different versions of StepByStep, implemented as an application on Android-based mobile devices, and compared their effectiveness in two field studies. Study 1 showed that a quantified version of the application—offering continuous measurement of walking time, a daily goal, and real-time feedback on progress toward this goal—facilitated reflection on activity and significantly increased walking time over baseline level. Study 2 showed that gamified versions offering virtual rewards and social comparison were only as effective as the quantified version. Thus, we advise designers to facilitate reflection on meaningful aspects of physical activity by developing novel ubiquitous measures. Furthermore, our findings highlight the importance of systematic comparisons between quantified and gamified elements for better understanding their motivational affordances.


Persuasive technology Behavior change Gamification Virtual reward Social comparison Physical activity 



We would like to thank Meytal Abo, Michal Gilon-Yanai, Orad Weisberg, Dr. Yaniv Kanat-Mymon, Dr. Guy Hoffman, and Dr. Guy Doron for their assistance with conceptualizing StepByStep; Shai Yagur, Roy Ofer, Omri Baumer, and Yair Halevi for their assistance with developing the different versions of the StepByStep prototype; Dr. Ofer Bergman for his suggestions on an early draft of the manuscript, and two anonymous reviewers for their constructive comments that helped improve the final paper.


  1. 1.
    Fogg B (2002) Persuasive technology: using computers to change what we think and do. Morgan Kaufmann, San FranciscoGoogle Scholar
  2. 2.
    Oinas-Kukkonen H, Harjumaa M (2008) A systematic framework for designing and evaluating persuasive systems. In: Proceedings of the 3rd international conference on persuasive technology (PERSUASIVE 2008). Springer Berlin Heidelberg, pp 164–176. doi: 10.1007/978-3-540-68504-3_15
  3. 3.
    Ertin E, Stohs N, Kumar S, Raij A, al’Absi M, Shah S (2011) AutoSense: unobtrusively wearable sensor suite for inferring the onset, causality, and consequences of stress in the field. In: Proceedings of the 9th ACM conference on embedded networked sensor systems (SenSys 2011). ACM, New York, pp 274–287. doi: 10.1145/2070942.2070970
  4. 4.
    Gay V, Leijdekkers P, Barin E (2009) A mobile rehabilitation application for the remote monitoring of cardiac patients after a heart attack or a coronary bypass surgery. In: Proceedings of the 2nd international conference on pervasive technologies related to assistive environments (PETRA 2009). ACM, New York, Article no. 21. doi: 10.1145/1579114.1579135
  5. 5.
    Grimes A, Kantroo V, Grinter RE (2010) Let’s play! mobile health games for adults. In: Proceeding of the 12th ACM international conference on ubiquitous computing (Ubicomp 2010). ACM, New York, pp 241–250. doi: 10.1145/1864349.1864370
  6. 6.
    Tsai CC, Lee G, Raab F, Norman GJ, Sohn T, Griswold WG, Patrick K (2007) Usability and feasibility of PmEB: a mobile phone application for monitoring real time caloric balance. Mob Netw Appl 12:173–184. doi: 10.1007/s11036-007-0014-4 CrossRefGoogle Scholar
  7. 7.
    Biddle SJH, Asare M (2011) Physical activity and mental health in children and adolescents: a review of reviews. Br J Sports Med 45:886–895. doi: 10.1136/bjsports-2011-090185 CrossRefGoogle Scholar
  8. 8.
    Fogelholm M (2010) Physical activity, fitness and fatness: relations to mortality, morbidity and disease risk factors: a systematic review. Obes Rev 11:202–221. doi: 10.1111/j.1467-789X.2009.00653.x CrossRefGoogle Scholar
  9. 9.
    Janssen I, LeBlanc AG (2010) Systematic review of the health benefits of physical activity and fitness in school-aged children and youth. Int J Behav Nutr Phys 7:1–16. doi: 10.1186/1479-5868-7-40 CrossRefGoogle Scholar
  10. 10.
    Vogel T, Brechat P-H, Leprêtre P-M, Kaltenbach G, Berthel M, Lonsdorfer J (2009) Health benefits of physical activity in older patients: a review. Int J Clin Pract 63:303–320. doi: 10.1111/j.1742-1241.2008.01957.x CrossRefGoogle Scholar
  11. 11.
    Bauman A, Ainsworth BE, Sallis JF, Hagströmer M, Craig CL, Bull FC, Pratt M, Venugopal K, Chau J, Sjöström M, the IPS Group (2011) The descriptive epidemiology of sitting. Am J Prev Med 41:228–235. doi: 10.1016/j.amepre.2011.05.003 CrossRefGoogle Scholar
  12. 12.
    Lakdawalla D, Philipson T (2009) The growth of obesity and technological change. Econ Hum Biol 7:283–293. doi: 10.1016/j.ehb.2009.08.001 CrossRefGoogle Scholar
  13. 13.
    Koch S, Marschollek M, Wolf KH, Plischke M, Haux R (2009) On health-enabling and ambient-assistive technologies. Methods Inf Med 48:29–37. doi: 10.33414/ME9136 Google Scholar
  14. 14.
    Klasnja P, Consolvo S, Pratt W (2011) How to evaluate technologies for health behavior change in HCI research. In: Proceedings of the SIGCHI conference on human factors in computing systems (CHI 2011). ACM, New York, pp 3063–3072. doi: 10.1145/1978942.1979396
  15. 15.
    Ahtinen A, Mattila E, Vaatanen A, Hynninen L, Salminen J, Koskinen E, Laine K (2009) User experience of mobile wellness applications in health promotion: user study of wellness diary, mobile coach and selfrelax. In: Proceeding of the 3rd international conference on pervasive computing technologies for healthcare (Pervasive Health 2009). IEEE, pp 1–8. doi: 10.4108/ICST.PERVASIVEHEALTH2009.6007
  16. 16.
    Dantzig S, Geleijnse G, Halteren AT (2013) Toward a persuasive mobile application to reduce sedentary behavior. Pers Ubiquit Comput 17(6):1237–1246. doi: 10.1007/s00779-012-0588-0 CrossRefGoogle Scholar
  17. 17.
    Li I, Dey A, Forlizzi J (2010) A stage-based model of personal informatics systems. In: Proceedings of the SIGCHI conference on human factors in computing systems (CHI 2010). ACM, New York, pp 557–566. doi: 10.1145/1753326.1753409
  18. 18.
    Ploderer B, Reitberger W, Oinas-Kukkonen H, van Gemert-Pijnen J (2014) Social interaction and reflection for behaviour change. Pers Ubiquit Comput (this issue). doi: 10.1007/s00779-014-0779-y
  19. 19.
    Campbell T, Ngo B, Fogarty J (2008) Game design principles in everyday fitness applications. In: Proceedings of the 2008 ACM conference on computer supported cooperative work (CSCW 2008). ACM, New York, pp 249–252. doi: 10.1145/1460563.1460603
  20. 20.
    Deterding S, Dixon D, Khaled R, Nacke L (2011) From game design elements to gamefulness: defining “gamification”. In: Proceedings of the 15th international academic MindTrek conference: envisioning future media environments (MindTrek 2011). ACM, New York, pp 9–15. doi: 10.1145/2181037.2181040
  21. 21.
    Hamari J, Koivisto J, Sarsa H (2014) Does gamification work? A literature review of empirical studies on gamification. In: Proceedings of the 47th Hawaii international conference on system sciencesGoogle Scholar
  22. 22.
    Mekler ED, Brühlmann F, Opwis K, Tuch AN (2013) Disassembling gamification: the effects of points and meaning on user motivation and performance. In: CHI ‘13 extended abstracts on human factors in computing systems (CHI EA 2013). ACM, New York, pp 1137–1142. doi: 10.1145/2468356.2468559
  23. 23.
    Oduor M, Alahäivälä T, Oinas-Kukkonen H (2014) Persuasive software design patterns for social influence. Pers Ubiquit Comput (this issue). doi: 10.1007/s00779-014-0778-z
  24. 24.
    Deterding S (2013) Skill atoms as design lenses for user-centered gameful design. In: Proceedings of CHI ‘13 workshop “Designing gamification”Google Scholar
  25. 25.
    Deterding S, Björk SL, Nacke LE, Dixon D, Lawley E (2013) Designing gamification: creating gameful and playful experiences. In CHI’13 extended abstracts on human factors in computing systems (CHI EA 13). ACM, New York, pp 3263–3266. doi: 10.1145/2468356.2479662
  26. 26.
    Consolvo S, Everitt K, Smith I, Landay JA (2006) Design requirements for technologies that encourage physical activity. In: Proceedings of the SIGCHI conference on human factors in computing systems (CHI 2006). ACM, New York, pp 457–466. doi: 10.1145/1124772.1124840
  27. 27.
    Murphy MH, Blair SN, Murtagh EM (2009) Accumulated versus continuous exercise for health benefit. Sports Med 39:29–43. doi: 10.2165/00007256-200939010-00003 CrossRefGoogle Scholar
  28. 28.
    Woolf-May K, Kearney EM, Owen A, Jones DW, Davison RCR, Bird SR (1999) The efficacy of accumulated short bouts versus single daily bouts of brisk walking in improving aerobic fitness and blood lipid profiles. Health Educ Res 14:803–815. doi: 10.1093/her/14.6.803 CrossRefGoogle Scholar
  29. 29.
    Schön DA (1983) The reflective practitioner: how professionals think in action. Basic Books, New YorkGoogle Scholar
  30. 30.
    Tudor-Locke C (2002) Taking steps toward increased physical activity: using pedometers to measure and motivate. President’s Council on Physical Fitness and Sports: Research Digest Series 3, No. 17Google Scholar
  31. 31.
    Bravata DM, Smith-Spangler C, Sundaram V, Gienger AL, Lin N, Lewis R, Stave CD, Olkin I, Sirard JR (2007) Using Pedometers to increase physical activity and improve health. JAMA 298:2296–2304. doi: 10.1001/jama.298.19.2296 CrossRefGoogle Scholar
  32. 32.
    Richardson CR, Newton TL, Abraham JJ, Sen A, Jimbo M, Swartz AM (2008) A meta-analysis of pedometer-based walking interventions and weight loss. Ann Fam Med 6:69–77. doi: 10.1370/afm.761 CrossRefGoogle Scholar
  33. 33.
    Tudor-Locke C, Lutes L (2009) Why do pedometers work? Sports Med 39:981–993. doi: 10.2165/11319600-000000000-00000 CrossRefGoogle Scholar
  34. 34.
    Locke EA, Latham GP (2002) Building a practically useful theory of goal setting and task motivation: a 35-year odyssey. Am Psychol 57:705–717. doi: 10.1037/0003-066X.57.9.705 CrossRefGoogle Scholar
  35. 35.
    Consolvo S, Klasnja P, McDonald DW, Landay JA (2009) Goal-setting considerations for persuasive technologies that encourage physical activity. In: Proceedings of the 4th international conference on persuasive technology (Persuasive 2009). ACM, New York, Article no. 8. doi: 10.1145/1541948.1541960
  36. 36.
    Ashford S, Edmunds J, French DP (2010) What is the best way to change self-efficacy to promote lifestyle and recreational physical activity? A systematic review with meta-analysis. Br J Health Psychol 15:265–288. doi: 10.1348/135910709X461752 CrossRefGoogle Scholar
  37. 37.
    Michie S, Abraham C, Whittington C, McAteer J, Gupta S (2009) Effective techniques in healthy eating and physical activity interventions: a meta-regression. Health Psychol 28:690–701. doi: 10.1037/a0016136 CrossRefGoogle Scholar
  38. 38.
    Deci EL, Ryan RM (1985) Intrinsic motivation and self-determination in human development. Plenum, New YorkCrossRefGoogle Scholar
  39. 39.
    Deci E, Koestner R, Ryan R (2001) Extrinsic rewards and intrinsic motivation in education: reconsidered once again. Rev Educ Res 71:1–27. doi: 10.3102/00346543071001001 CrossRefGoogle Scholar
  40. 40.
    Deterding S (2011) Situated motivational affordances of game elements: a conceptual model. In: Proceedings of CHI ‘11 workshop “Gamification: using game design elements in non-gaming contexts”Google Scholar
  41. 41.
    Nicholson S (2012) A user-centered theoretical framework for meaningful gamification. In: Proceedings of Games + Learning + Society 8.0 (GLS 8.0)Google Scholar
  42. 42.
    Lindqvist J, Cranshaw J, Wiese J, Hong J, Zimmerman J (2011) I’m the mayor of my house: examining why people use foursquare: a social-driven location sharing application. In: Proceedings of the SIGCHI conference on human factors in computing systems (CHI 2011). ACM, New York, pp 2409–2418. doi: 10.1145/1978942.1979295
  43. 43.
    Antin J, Churchill EF (2011) Badges in social media: a social psychological perspective. In: Proceedings of CHI ‘11 workshop “Gamification: using game design elements in non-gaming contexts”Google Scholar
  44. 44.
    Munson SA, Consolvo S (2012) Exploring goal-setting, rewards, self-monitoring, and sharing to motivate physical activity. In: Proceedings of the 6th international conference on pervasive computing technologies for healthcare (PervasiveHealth 2012). IEEE, pp 25–32Google Scholar
  45. 45.
    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: Proceedings of the SIGCHI conference on human factors in computing systems (CHI 2008). ACM, New York, pp 1797–1806. doi: 10.1145/1357054.1357335
  46. 46.
    Consolvo S, Klasnja P, McDonald DW, Avrahami D, Froehlich J, LeGrand L, Libby R, Mosher K, Landay JA (2008) Flowers or a robot army? Encouraging awareness and activity with personal, mobile displays. In: Proceedings of the 10th international conference on ubiquitous computing (UbiComp 2008). ACM, New York, pp 54–63. doi: 10.1145/1409635.1409644
  47. 47.
    Ahtinen A, Huuskonen P, Hakkila J (2010) Let’s all get up and walk to the north pole: design and evaluation of a mobile wellness application. In: Proceeding of the 6th nordic conference on human–computer interaction (NordiCHI 2010). ACM, New York, pp 3-12. doi: 10.1145/1868914.1868920
  48. 48.
    HopeLab (2012) Study shows technology gets kids moving 59% more. Accessed 31 March 2014
  49. 49.
    Festinger L (1954) A theory of social comparison processes. Hum Relat 108:117–140. doi: 10.1177/001872675400700202 CrossRefGoogle Scholar
  50. 50.
    Kruglanski AW, Mayseless O (1990) Classic and current social comparison research: expanding the perspective. Psychol Bull 108:195–208. doi: 10.1037/0033-2909.108.2.195 CrossRefGoogle Scholar
  51. 51.
    de Oliveira R, Oliver N (2008) TripleBeat: enhancing exercise performance with persuasion. In: Proceedings of the 10th international conference on human computer interaction with mobile devices and services (MobileHCI 2008). ACM, New York, pp 255–264. doi: 10.1145/1409240.1409268
  52. 52.
    Lin JJ, Mamykina L, Lindtner S, Delajoux G, Strub HB (2006) Fish’n’Steps: encouraging physical activity with an interactive computer game. In: Proceedings of the 8th international conference on ubiquitous computing (UbiComp 2006). Springer-Verlag Berlin, Heidelberg, pp 261–278. doi: 10.1007/11853565_16
  53. 53.
    Xu Y, Shehan Poole E, Miller AD, Eiriksdottir E, Catrambone R, Mynatt ED (2012) Designing pervasive health games for sustainability, adaptability and sociability. In: Proceedings of the international conference on the foundations of digital games (FDG 2012). ACM, New York, pp 49–56. doi: 10.1145/2282338.2282352
  54. 54.
    Edwards HM, McDonald S, Zhao T (2011) Exploring teenagers’ motivation to exercise through technology probes. Proceedings of the 25th BCS conference on human–computer interaction (BCS-HCI 2011). British Computer Society, Swinton, pp 104–113Google Scholar
  55. 55.
    Brooke J (1996) SUS: a quick and dirty usability scale. In: Jordan PW, Thomas B, Weerdmeester BA, McClelland IL (eds) Usability evaluation in industry. Taylor & Francis, London, pp 189–194Google Scholar
  56. 56.
    Xu Y, Poole ES, Miller AD, Eiriksdottir E, Kestranek D, Catrambone R, Mynatt ED (2012) This is not a one-horse race: understanding player types in multiplayer pervasive health games for youth. In: Proceedings of the ACM 2012 conference on computer supported cooperative work (CSCW 2012). ACM, New York, pp 843–852. doi: 10.1145/2145204.2145330
  57. 57.
    Wiafe I, Nakata K, Gulliver S (2014) Categorizing users in behavior change support systems based on cognitive dissonance. Pers Ubiquit Comput. doi: 10.1007/s00779-014-0782-3
  58. 58.
    Martin H, Bernardos AM, Iglesias J, Casar JR (2013) Activity logging using lightweight classification techniques in mobile devices. Pers Ubiquit Comput 17:675–695. doi: 10.1007/s00779-012-0515-4 CrossRefGoogle Scholar
  59. 59.
    Ivonin L, Chang H-M, Chen W, Rauterberg M (2013) Unconscious emotions: quantifying and logging something we are not aware of. Pers Ubiquit Comput 17:663–673. doi: 10.1007/s00779-012-0514-5 CrossRefGoogle Scholar
  60. 60.
    Baumer EPS, Katz SJ, Freeman JE, Adams P, Gonzales AL, Pollak J, Retelny D, Niederdeppe J, Olson CM, Gay GK (2012) Prescriptive persuasion and open-ended social awareness: expanding the design space of mobile health. In: Proceedings of the ACM 2012 conference on computer supported cooperative work (CSCW 2012). ACM, New York, pp 475–484. doi: 10.1145/2145204.2145279
  61. 61.
    Parker (2014) Reflection-through-performance: personal implications of documenting health behaviors for the collective. Pers Ubiquit Comput. doi: 10.1007/s00779-014-0780-5
  62. 62.
    Liu Y, Alexandrova T, Nakajima T (2011) Gamifying intelligent environments. In: Proceedings of the 2011 international ACM workshop on Ubiquitous Meta User interfaces (UBI-MUI 2011). ACM, New York, pp 7–12. doi: 10.1145/2072652.2072655

Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  1. 1.Media Innovation Lab, Sammy Ofer School of CommunicationsThe Interdisciplinary Center (IDC) HerzliyaHerzliyaIsrael

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