Ontological Review of Persuasion Support Systems (PSS) for Health Behavior Change through Physical Activity


Persuasion Support Systems (PSS) for health behavior change can play an important role in promoting health and well-being through physical activity. It is an emerging application at the crossroad between information systems, persuasion, and healthcare. We propose an ontology to systematically and systemically describe the construct of PSS for health behavior change. The ontology deconstructs the construct into its constituent dimensions and elements, and assembles them into a complete, parsimonious description of the same. We then map the corpus of literature on PSS for health behavior change through physical activity onto the ontology. The resulting ontological map highlights the research topics that are highly- and lightly-emphasized, as well as those with little or no emphasis. It illuminates the landscape of research in the corpus; it highlights biases in emphases that can help and hinder the advancement of the corpus. It can be used to develop a roadmap for future research.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4


  1. 1.

    Klecun-Dabrowska, E., and Cornford, T., Telehealth acquires meanings: information and communication technologies within health policy. Inf. Syst. J. 10(1):41–63, 2000. https://doi.org/10.1046/j.1365-2575.2000.00074.x.

    Article  Google Scholar 

  2. 2.

    Boonstra, A., and Van Offenbeek, M., Towards consistent modes of e-health implementation: structurational analysis of a telecare programme's limited success. Inf. Syst. J. 20(6):537–561, 2010. https://doi.org/10.1111/j.1365-2575.2010.00358.x.

    Article  Google Scholar 

  3. 3.

    Chatterjee, S., and Price, A., Healthy Living with Persuasive Technologies: Framework, Issues, and Challenges. J. Am. Med. Inform. Assoc. 16(2):171–178, 2009. https://doi.org/10.1197/jamia.M2859.

    Article  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Kaptein, M., Markopoulos, P., de Ruyter, B., and Aarts, E., Personalizing persuasive technologies: Explicit and implicit personalization using persuasion profiles. Int J Human-Computer Stud 77:38–51, 2015. https://doi.org/10.1016/j.ijhcs.2015.01.004.

    Article  Google Scholar 

  5. 5.

    Daud, N. A., Sahari@Ashaari, N., and Muda, Z., An Initial Model of Persuasive Design in Web based Learning Environment. Procedia Tech 11:895–902, 2013. https://doi.org/10.1016/j.protcy.2013.12.273.

    Article  Google Scholar 

  6. 6.

    Looije, R., Neerincx, M. A., and Cnossen, F., Persuasive robotic assistant for health self-management of older adults: Design and evaluation of social behaviors. Int J Human-Computer Stud 68(6):386–397, 2010. https://doi.org/10.1016/j.ijhcs.2009.08.007.

    Article  Google Scholar 

  7. 7.

    Matthews, J., Win, K. T., Oinas-Kukkonen, H., and Freeman, M., Persuasive Technology in Mobile Applications Promoting Physical Activity: a Systematic Review. J. Med. Syst. 40(3):72, 2016. https://doi.org/10.1007/s10916-015-0425-x.

    Article  PubMed  Google Scholar 

  8. 8.

    Morrison, L. G., Yardley, L., Powell, J., and Michie, S., What Design Features Are Used in Effective e-Health Interventions? A Review Using Techniques from Critical Interpretive Synthesis. Telemed e-Health 18(2):137–144, 2012. https://doi.org/10.1089/tmj.2011.0062.

    Article  Google Scholar 

  9. 9.

    Doupi, P., and van der Lei, J., Design and implementation considerations for a personalized patient education system in burn care. Int. J. Med. Inform. 74(2–4):151–157, 2005. https://doi.org/10.1016/j.ijmedinf.2004.04.021.

    Article  PubMed  Google Scholar 

  10. 10.

    Clayman, M. L., Boberg, E. W., and Makoul, G., The use of patient and provider perspectives to develop a patient-oriented website for women diagnosed with breast cancer. Patient Educ. Couns. 72(3):429–435, 2008. https://doi.org/10.1016/j.pec.2008.05.032.

    Article  PubMed  Google Scholar 

  11. 11.

    Win, K. T., Hassan, N. M., Oinas-Kukkonen, H., and Probst, Y., Online Patient Education for Chronic Disease Management: Consumer Perspectives. J. Med. Syst. 40(4):88, 2016. https://doi.org/10.1007/s10916-016-0438-0.

    Article  PubMed  Google Scholar 

  12. 12.

    Ferney, S. L., and Marshall, A. L., Website physical activity interventions: preferences of potential users. Health Educ. Res. 21(4):560–566, 2006. https://doi.org/10.1093/her/cyl013.

    Article  PubMed  Google Scholar 

  13. 13.

    DeGuzman, M. A., and Ross, M. W., Assessing the application of HIV and AIDS related education and counselling on the Internet. Patient Educ. Couns. 36(3):209–228, 1999. https://doi.org/10.1016/S0738-3991(98)00096-2.

    CAS  Article  PubMed  Google Scholar 

  14. 14.

    Gosselin, P., and Poitras, P., Use of an internet "viral" marketing software platform in health promotion. J. Med. Internet Res. 10(4):e47, 2008. https://doi.org/10.2196/jmir.1127.

    Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Rezailashkajani, M., Roshandel, D., Ansari, S., and Zali, M. R., A web-based patient education system and self-help group in Persian language for inflammatory bowel disease patients. Int. J. Med. Inform. 77(2):122–128, 2008. https://doi.org/10.1016/j.ijmedinf.2006.12.001.

    Article  PubMed  Google Scholar 

  16. 16.

    Yamout, S. Z., Glick, Z. A., Lind, D. S., Monson, R. A. Z., and Glick, P. L., Using social media to enhance surgeon and patient education and communication. Bull Am College Surgeons 96(7):7–15, 2011.

    Google Scholar 

  17. 17.

    Ramaprasad, A., Syn, T., Strong and Meaningful Use of Healthcare Information Systems (HIS). In: Bienkiewicz M, Verdier C, Plantier G, Schultz T, Fred A, Gamboa H (eds) Proceedings of the International Conference on Health Informatics (BIOSTEC 2014). SciTePress, Angers, pp. 381–386, 2014. 10.5220/0004870303810386

  18. 18.

    Gruber, T. R., Ontology. In: Liu, L., Özsu, M. T. (Eds), Encyclopedia of Database Systems. New York: Springer-Verlag, 2008, 1963–1965.

    Google Scholar 

  19. 19.

    Gruber, T. R., Toward Principles for the Design of Ontologies Used for Knowledge Sharing. Int J Human-Computer Stud 43(5–6):907–928, 1995. https://doi.org/10.1006/ijhc.1995.1081.

    Article  Google Scholar 

  20. 20.

    Cimino, J. J., In defense of the Desiderata. J. Biomed. Inform. 39(3):299–306, 2006. https://doi.org/10.1016/j.jbi.2005.11.008.

    Article  PubMed  Google Scholar 

  21. 21.

    Quine, W. V. O., From a Logical Point of View. Second, revised edn. Boston: Harvard University Press, 1961.

    Google Scholar 

  22. 22.

    Oinas-Kukkonen, H., Harjumaa, M., Towards deeper understanding of persuasion in software and information systems. In: Proceedings of the 1st International Conference on Advances in Computer-Human Interaction. IEEE, pp 200–205, 2008.

  23. 23.

    Fogg, B. J., Persuasive Technology: Using Computers to Change What We Think and Do. Persuasive Technology. San Francisco: Morgan Kaufmann, 2003. 10.1016/B978-1-55860-643-2.X5000-8

  24. 24.

    Prochaska, J. O., Butterworth, S., Redding, C. A., Burden, V., Perrin, N., Leo, M., Flaherty-Robb, M., and Prochaska, J. M., Initial efficacy of MI, TTM tailoring and HRI’s with multiple behaviors for employee health promotion. Prev. Med. 46(3):226–231, 2008. https://doi.org/10.1016/j.ypmed.2007.11.007.

    Article  PubMed  Google Scholar 

  25. 25.

    Malik, N. A., Zhang, J., Lam, O. L. T., Jin, L., and McGrath, C., Effectiveness of computer-aided learning in oral health among patients and caregivers: a systematic review. J. Am. Med. Inform. Assoc. 24(1):209–217, 2017. https://doi.org/10.1093/jamia/ocw045.

    Article  Google Scholar 

  26. 26.

    Ramaprasad, A., Syn, T., Thirumalai, M., An Ontological Map for Meaningful Use of Healthcare Information Systems (MUHIS). In: Bienkiewicz M, Verdier C, Plantier G, Schultz T, Fred A, Gamboa H (eds) Proceedings of the International Conference on Health Informatics (BIOSTEC 2014). Angers: SciTePress, pp. 16–26, 2014. 10.5220/0004734500160026

  27. 27.

    Ramaprasad, A., Syn, T., Thirumalai, M., Ontological Analysis of Meaningful Use of Healthcare Information Systems (MUHIS) Requirements and Practice. In: Plantier G, Schulz T, Fred A, Gamboa H (eds) Biomedical Engineering Systems and Technologies, vol 511. Communications in Computer and Information Science. Cham: Springer International Publishing, pp. 315–330, 2015. 10.1007/978-3-319-26129-4_21

  28. 28.

    Ramaprasad, A., and Syn, T., Ontological Meta-Analysis and Synthesis. Comm Assoc Inform Syst 37(7):138–153, 2015.

    Google Scholar 

  29. 29.

    Brennan, L., Voros, J., and Brady, E., Paradigms at play and implications for validity in social marketing research. J Soc Market 1(2):100–119, 2011. https://doi.org/10.1108/20426761111141869.

    Article  Google Scholar 

  30. 30.

    Horn, B. R., Lee, I.-H., Toward integrated interdisciplinary information and communication sciences: a general systems perspective. In: Proceedings of the 22nd Hawaii International Conference on System Sciences (HICSS 1989), vol 4. Kailua-Kona: IEEE, pp 244–255, 1989. 10.1109/HICSS.1989.48129

  31. 31.

    Tufte, E. R., Envisioining Information. Cheshire: Graphics Press, 1990.

    Google Scholar 

  32. 32.

    Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P., Clarke, M., Devereaux, P., Kleijnen, J., and Moher, D., The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration. PLoS Med. 6(7), 2009. https://doi.org/10.1371/journal.pmed.1000100.

  33. 33.

    Ammann, R., Vandelanotte, C., de Vries, H., and Mummery, W. K., Can a Website-Delivered Computer-Tailored Physical Activity Intervention Be Acceptable, Usable, and Effective for Older People? Health Educ. Behav. 40(2):160–170, 2013. https://doi.org/10.1177/1090198112461791.

    Article  PubMed  Google Scholar 

  34. 34.

    Alley, S., Jennings, C., Plotnikoff, R. C., and Vandelanotte, C., My Activity Coach - Using video-coaching to assist a web-based computer-tailored physical activity intervention: a randomised controlled trial protocol. BMC Public Health 14, 2014. https://doi.org/10.1186/1471-2458-14-738.

  35. 35.

    Spittaels, H., De Bourdeaudhuij, I., Brug, J., and Vandelanotte, C., Effectiveness of an online computer-tailored physical activity intervention in a real-life setting. Health Educ. Res. 22(3):385–396, 2007. https://doi.org/10.1093/her/cyl096.

    Article  PubMed  Google Scholar 

  36. 36.

    Kelders, S. M., van Gemert-Pijnen, J. E., Werkman, A., and Seydel, E. R., Evaluation of a web-based lifestyle coach designed to maintain a healthy bodyweight. J. Telemed. Telecare 16(1):3–7, 2010. https://doi.org/10.1258/jtt.2009.001003.

    Article  PubMed  Google Scholar 

  37. 37.

    King, A. C., Bickmore, T. W., Campero, M. I., Pruitt, L. A., and Yin, J. L., Employing Virtual Advisors in Preventive Care for Underserved Communities: Results From the COMPASS Study. J. Health Commun. 18(12):1449–1464, 2013. https://doi.org/10.1080/10810730.2013.798374.

    Article  PubMed  Google Scholar 

  38. 38.

    Winett, R. A., Anderson, E. S., Wojcik, J. R., Winett, S. G., and Bowden, T., Guide to Health: Nutrition and Physical Activity Outcomes of a Group-Randomized Trial of an Internet-Based Intervention in Churches. Ann. Behav. Med. 33(3):251–261, 2007. https://doi.org/10.1007/BF02879907.

    Article  PubMed  Google Scholar 

  39. 39.

    Antypas, K., and Wangberg, S. C., An Internet- and Mobile-Based Tailored Intervention to Enhance Maintenance of Physical Activity After Cardiac Rehabilitation: Short-Term Results of a Randomized Controlled Trial. J. Med. Internet Res. 16(3):78–95, 2014. https://doi.org/10.2196/jmir.3132.

    Article  Google Scholar 

  40. 40.

    Morgan, P. J., Callister, R., Collins, C. E., Plotnikoff, R. C., Young, M. D., Berry, N., McElduff, P., Burrows, T., Aguiar, E., and Saunders, K. L., The SHED-IT Community Trial: A Randomized Controlled Trial of Internet- and Paper-Based Weight Loss Programs Tailored for Overweight and Obese Men. Ann. Behav. Med. 45(2):139–152, 2013. https://doi.org/10.1007/s12160-012-9424-z.

    Article  PubMed  Google Scholar 

  41. 41.

    Klausen, S. H., Mikkelsen, U. R., Hirth, A., Wetterslev, J., Kjaergaard, H., Sondergaard, L., and Andersen, L. L., Design and rationale for the PREVAIL study: Effect of e-Health individually tailored encouragements to physical exercise on aerobic fitness among adolescents with congenital heart disease—a randomized clinical trial. Am. Heart J. 163(4):549–556, 2012. https://doi.org/10.1016/j.ahj.2012.01.021.

    Article  PubMed  Google Scholar 

  42. 42.

    Hearn, L., Miller, M., and Fletcher, A., Online healthy lifestyle support in the perinatal period: what do women want and do they use it? Aust J Primary Health 19(4):313–318, 2013. https://doi.org/10.1071/py13039.

    Article  Google Scholar 

  43. 43.

    Brindal, E., Freyne, J., Saunders, I., Berkovsky, S., Smith, G., and Noakes, M., Features Predicting Weight Loss in Overweight or Obese Participants in a Web-Based Intervention: Randomized Trial. J. Med. Internet Res. 14(6):114–129, 2012. https://doi.org/10.2196/jmir.2156.

    Article  Google Scholar 

  44. 44.

    Ezendam, N., Noordegraaf, V., Kroeze, W., Brug, J., and Oenema, A., Process evaluation of FATaintPHAT, a computer-tailored intervention to prevent excessive weight gain among Dutch adolescents. Health Promot. Int. 28(1):26–35, 2013. https://doi.org/10.1093/heapro/das021.

    CAS  Article  PubMed  Google Scholar 

  45. 45.

    Mitchell, B. L., Lewis, N. R., Smith, A. E., Rowlands, A. V., Parfitt, G., and Dollman, J., Rural Environments and Community Health (REACH): a randomised controlled trial protocol for an online walking intervention in rural adults. BMC Public Health 14, 2014. https://doi.org/10.1186/1471-2458-14-969.

  46. 46.

    Hurling, R., Catt, M., De Boni, M., Fairley, B. W., Hurst, T., Murray, P., Richardson, A., and Sodhi, J. S., Using Internet and Mobile Phone Technology to Deliver an Automated Physical Activity Program: Randomized Controlled Trial. J. Med. Internet Res. 9(2):1–12, 2007. https://doi.org/10.2196/jmir.9.2.e7.

    Article  Google Scholar 

  47. 47.

    Rothert, K., Strecher, V. J., Doyle, L. A., Caplan, W. M., Joyce, J. S., Jimison, H. B., Karm, L. M., Mims, A. D., and Roth, M. A., Web-based Weight Management Programs in an Integrated Health Care Setting: A Randomized, Controlled Trial. Obes 14(2):266–272, 2006. https://doi.org/10.1038/oby.2006.34.

    Article  Google Scholar 

  48. 48.

    Patrick, K., Marshall, S. J., Davila, E. P., Kolodziejczyk, J. K., Fowler, J. H., Calfas, K. J., Huang, J. S., Rock, C. L., Griswold, W. G., Gupta, A., Merchant, G., Norman, G. J., Raab, F., Donohue, M. C., Fogg, B. J., and Robinson, T. N., Design and implementation of a randomized controlled social and mobile weight loss trial for young adults (project SMART). Contemp Clin Trials 37(1):10–18, 2014. https://doi.org/10.1016/j.cct.2013.11.001.

    CAS  Article  PubMed  Google Scholar 

  49. 49.

    Funk, K. L., Stevens, V. J., Bauck, A., Brantley, P. J., Hornbrook, M., Jerome, G. J., Myers, V. H., and Appel, L., Development and Implementation of a Tailored Self-assessment Tool in an Internet-based Weight Loss Maintenance Program. Clin. Pract. Epidemiol. Ment. Health 7:67–73, 2011. https://doi.org/10.2174/1745017901107010067.

    Article  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Parekh, S., King, D., Boyle, F. M., and Vandelanotte, C., Randomized controlled trial of a computer-tailored multiple health behaviour intervention in general practice: 12-month follow-up results. Int. J. Behav. Nutr. Phys. Act. 11, 2014. https://doi.org/10.1186/1479-5868-11-41.

  51. 51.

    Martinez, J. L., Duncan, L. R., Rivers, S. E., Latimer, A. E., and Salovey, P., Examining the use of message tailoring to promote physical activity among medically underserved adults. J. Health Psychol. 18(4):470–476, 2013. https://doi.org/10.1177/1359105312445798.

    Article  PubMed  Google Scholar 

  52. 52.

    Cheetham, A. H., and Hazel, J. E., Binary (Presence-Absence) Similarity Coefficients. J. Paleontol. 43(5):1130–1136, 1969. https://doi.org/10.2307/1302424.

    Article  Google Scholar 

  53. 53.

    Gower, J. C., A General Coefficient of Similarity and Some of Its Properties. Biometrics 27(4):857–871, 1971. https://doi.org/10.2307/2528823.

    Article  Google Scholar 

  54. 54.

    Oinas-Kukkonen, H., and Harjumaa, M., Persuasive Systems Design: Key Issues, Process Model, and System Features. Comm Assoc Inform Syst 24:485–500, 2009.

    Google Scholar 

  55. 55.

    Fisher, C. M., Adapting the Information–Motivation–Behavioral Skills Model:Predicting HIV-Related Sexual Risk Among Sexual Minority Youth. Health Educ. Behav. 39(3):290–302, 2012. https://doi.org/10.1177/1090198111406537.

    Article  PubMed  Google Scholar 

  56. 56.

    Ajzen, I., and Fishbein, M., Understanding attitudes and predicting social behaviour. Englewood Cliffs: Prentice-Hall, 1980.

    Google Scholar 

  57. 57.

    Win, K. T., Hassan, N., Bonney, A., and Iverson, D., Benefits of Online Health Education: Perception from Consumers and Health Professionals. J. Med. Syst. 39(3):1–8, 2015. https://doi.org/10.1007/s10916-015-0224-4.

    Article  Google Scholar 

Download references

Author information



Corresponding author

Correspondence to Khin Than Win.

Ethics declarations

Conflict of interest

All authors declare that there is no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection on Patient Facing Systems

Appendix 1: Glossary

Appendix 1: Glossary

Information System Support: Support provided by persuasive support systems
  Reduction: Reduce effort users expend when performing target behavior
  Tunneling: Guide users in attitude change by providing means for action that brings them closer to target behavior
  Tailoring: Provide tailored info for user groups
  Personalization: Offer personalized content and services for users
  Self-monitoring: Provide means for users to track their performance or status
  Simulation: Provide means for observing link between cause & effect with regard to users’ behavior
  Rehearsal: Provide means for rehearsing target behavior
  Suggestion: Suggest users carry out behaviors while using the system
  Similarity: Imitate its users in some specific way
  Praise: Use praise via words, images, symbols, sounds to provide user feedback based on behaviors
  Rewards: Provide virtual rewards for users to give credit for performing target behavior
  Liking: Have a look & feel that appeals to users
  Reminders: Remind users of their target behavior while using the system
  Support: Adopt a social role
  Expertise: Provide info showing knowledge, experience & competence
  Verifiability: Provide means to verify accuracy of site content via outside sources
  Surface Credibility: Have competent look & feel
  Real-World Feel: Provide info of the organization/actual people behind it content & services
  Trustworthiness: Provide info that is truthful, fair & unbiased
  Authority: Refer to people in the role of authority
  Endorsements: Provide endorsements from respected sources
  Recognition: Provide public recognition for users who perform their target behavior
  Facilitation: Provide means for discerning others who are performing the behavior
  Cooperation: Provide means for co-operation
  Competition: Provide means for competing with others
  Learning: Provide means to observe others performing their target behaviors to see outcome of their behavior
  Comparison: Provide means for comparing performance with the performance of others
  Influence: Provide means for gathering people who have same goal & make them feel norms
Persuasion: Persuade the user
Action: Persuasive action of the system
  Reinforce: Reinforce the object of persuasion
  Modify: Modify the object of persuasion
  Change: Change the object of persuasion
Focus: Focus of the persuasion
  Knowledge: Knowledge of the user
  Attitude: Attitude of the user
  Behavior: Behavior of the user
Health: Outcomes of healthcare of users
Quality: Quality of healthcare of users
Safety: Safety of healthcare of users
Cost: Cost of healthcare of users
Parity: Parity of healthcare of users

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Win, K.T., Ramaprasad, A. & Syn, T. Ontological Review of Persuasion Support Systems (PSS) for Health Behavior Change through Physical Activity. J Med Syst 43, 49 (2019). https://doi.org/10.1007/s10916-019-1159-y

Download citation


  • Persuasion
  • Health behavior change
  • Ontology
  • Physical activity