Assessing the Usability of a Prediabetes Self-Care Application: a Multi-Method Approach

  • Authors

    • Suthashini Subramaniam
    • Jaspaljeet Singh Dhillon
    2018-11-30
    https://doi.org/10.14419/ijet.v7i4.35.22325
  • Behavioural change theories, Diabetes prevention, Digital health technology, Prediabetes, Self-care, System usability, User experience.

  • Abstract

    Increasing demand for digital technology, worldwide, has unlocked new pathways for diabetes prevention. Health behavioural change theories when integrated in the design of novel health applications can foster effective self-health management and prevention. We developed i-PreventDiabetes, a self-care application for prediabetics, that enables lifestyle monitoring, goal setting and activity planning, which is accessible via both web and mobile. In this study, we evaluated the usability barriers and enablers, and assessed the user experience with the system by using a multi-method approach with 20 participants. This approach includes cognitive walkthrough, think-aloud method, question-asking protocol, System Usability Scale (SUS), User Experience Questionnaire (UEQ), and open-ended questions. The results indicate that the users are satisfied with the concept of preventing diabetes by using a self-care application that includes a variety of functionalities that empowers prediabetics to take charge of their own lifestyle in preventing diabetes.

  • References

    1. [1] Sénéchal, M., Slaght, J., Bharti, N., & Bouchard, D. R. (2014). Independent and combined effect of diet and exercise in adults with prediabetes. Diabetes, metabolic syndrome and obesity: targets and therapy, 7, 521.

      [2] Gulla, J., Neri, P. M., Bates, D. W., & Samal, L. (2017). User requirements for a chronic kidney disease clinical decision support tool to promote timely referral. International journal of medical informatics, 101, 50-57.

      [3] Subramaniam, S., Dhillon, J. S., Ahmad, M. S., Teoh, C., & Leong, J. W. S. (2016). Integrating health behavioural change theories in the design of prediabetes self-care applications: A systematic literature review. Journal of Theoretical and Applied Information Technology, 88(2), 189-201.

      [4] Subramaniam, S., Dhillon, J. S., Ahmad, M. S., WS, L. J., Teoh, C., & Huang, C. S. (2016). Eliciting user requirements to design a prediabetes self-care application: a focus group study with prediabetics and diabetics. Indian Journal of Science and Technology, 9(S1).

      [5] Subramaniam, S., Dhillon, J. S., Ahmad, M. S., Leong, J. W., & Teoh, C. (2017, April). User Requirements for Prediabetes Self-care Application: A Healthcare Professional Perspective. In International Conference of Reliable Information and Communication Technology (pp. 616-626). Springer, Cham.

      [6] Subramaniam, S., Dhillon, J. S., Ahmad, M. S., Teoh, C., & Leong, J. W. (2017, July). A framework for developing prediabetes self-care application. In Research and Innovation in Information Systems (ICRIIS), 2017 International Conference on (pp. 1-7). IEEE.

      [7] Prochaska, J. O., & Velicer, W. F. (1997). The transtheoretical model of health behavior change. American journal of health promotion, 12(1), 38-48.

      [8] Ã…rsand, E., & Demiris, G. (2008). User-centered methods for designing patient-centric self-help tools. Informatics for health and social care, 33(3), 158-169.

      [9] Bozkurt, S., Zayim, N., Gulkesen, K. H., Samur, M. K., KaraaÄŸaoglu, N., & Saka, O. (2011). Usability of a web-based personal nutrition management tool. Informatics for Health and Social Care, 36(4), 190-205.

      [10] Gibson, B. E., King, G., Kushki, A., Mistry, B., Thompson, L., Teachman, G., Batorowicz, B. & McMain-Klein, M. (2014). A multi-method approach to studying activity setting participation: integrating standardized questionnaires, qualitative methods and physiological measures. Disability and rehabilitation, 36(19), 1652-1660.

      [11] Georgsson, M., & Staggers, N. (2016). An evaluation of patients’ experienced usability of a diabetes mHealth system using a multi-method approach. Journal of biomedical informatics, 59, 115-129.

      [12] Faulkner, L. (2003). Beyond the five-user assumption: Benefits of increased sample sizes in usability testing. Behavior Research Methods, Instruments, & Computers, 35(3), 379-383.

      [13] Macefield, R. (2009). How to specify the participant group size for usability studies: a practitioner's guide. Journal of Usability Studies, 5(1), 34-45.

      [14] Rieman, J., Franzke, M., & Redmiles, D. (1995, May). Usability evaluation with the cognitive walkthrough. In Conference companion on Human factors in computing systems (pp. 387-388). ACM.

      [15] Nielsen, J. (1995). 10 Usability Heuristics for User Interface Design. Available from: https://www.nngroup.com/articles/ten-usability-heuristics/ (accessed 19 June 2018)

      [16] Brooke, J. (1996). SUS-A quick and dirty usability scale. Usability evaluation in industry, 189(194), 4-7.

      [17] Laugwitz, B., Held, T., & Schrepp, M. (2008, November). Construction and evaluation of a user experience questionnaire. In Symposium of the Austrian HCI and Usability Engineering Group (pp. 63-76). Springer, Berlin, Heidelberg.

      [18] Bangor, A., Kortum, P., & Miller, J. (2009). Determining what individual SUS scores mean: Adding an adjective rating scale. Journal of usability studies, 4(3), 114-123.

      [19] Brooke, J. (2013). SUS: a retrospective. Journal of usability studies, 8(2), 29-40.

      [20] Schrepp, M., Hinderks, A., & Thomaschewski, J. (2017). Construction of a Benchmark for the User Experience Questionnaire (UEQ). IJIMAI, 4(4), 40-44.

  • Downloads

  • How to Cite

    Subramaniam, S., & Dhillon, J. S. (2018). Assessing the Usability of a Prediabetes Self-Care Application: a Multi-Method Approach. International Journal of Engineering & Technology, 7(4.35), 66-72. https://doi.org/10.14419/ijet.v7i4.35.22325

    Received date: 2018-11-29

    Accepted date: 2018-11-29

    Published date: 2018-11-30