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Usability and Acceptance of a Mobile and Cloud-Based Platform for Supporting Diabetes Self-management

  • Jesús Fontecha
  • Iván González
  • M. Estrella Saucedo
  • M. José Sánchez
  • José Bravo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10586)

Abstract

Millions of people are suffering from Diabetes Mellitus today. This amount is expected to increase over the next few years due to multiple factors, not only genetic ones, but also because of our sedentary lifestyle according to the World Health Organization.

This work presents a cloud-based system which consists of a web platform, a mobile application and a set of services to facilitate a centralised study of the most relevant parameters involved in diabetes self-care. The system was evaluated by a group of diabetic patients in which 75% of them showed their satisfaction using this system for diabetes self-control. Also, the acceptance level between user and system was studied by means of an usability analysis focused on several evaluation techniques.

Keywords

Diabetes mHealth Monitoring System acceptance Usability 

Notes

Acknowledgments

This work has been funded by MAPFRE Foundation and supported by the Plan Propio de Investigación program of Castilla-La Mancha University. Authors gratefully acknowledge the participation and collaboration of the whole group of diabetic users in the evaluation process.

References

  1. 1.
    Shah, V., Garg, S.: Managing diabetes in the digital age. Clin. Diabetes Endocrinol. 1, 16 (2015)CrossRefGoogle Scholar
  2. 2.
    Lanzola, G., Losiouk, E., Favero, S.D., Facchinetti, A., Galderisi, A., Quaglini, S., Magni, L., Cobelli, C.: Remote blood glucose monitoring in mHealth scenarios: a review. Sensors 16(12), 2–16 (2016)CrossRefGoogle Scholar
  3. 3.
    Hood, M., Wilson, R., Corsica, J., Bradley, L., Chirinos, D., Vivo, A.: What do we know about mobile applications for diabetes management? a review of reviews. J. Behav. Med. 39(6), 981–994 (2016)CrossRefGoogle Scholar
  4. 4.
    Georgsson, M., Staggers, N.: Quantifying usability: an evaluation of a diabetes mhealth system on effectiveness, efficiency, and satisfaction metrics with associated user characteristics. J. Am. Med. Inf. Assoc. 23(1), 5–11 (2016)CrossRefGoogle Scholar
  5. 5.
    Hartz, J., Yingling, L., Powel-Wiley, T.: Use of mobile technology in the prevention and management of diabetes mellitus. Curr. Cardiol. Rep. 18(12), 130 (2016)CrossRefGoogle Scholar
  6. 6.
    Castelnuovo, G., Mauri, G., Waki, K.: mHeatlh and eHealth for obesity and types 2 and 1 diabetes. J. Diabetes Res. 2016, 1 (2016)CrossRefGoogle Scholar
  7. 7.
    El-Gayar, O., Timsina, P., Nawar, N., Eid, W.: Mobile applications for diabetes self-management: status and potential. J. Diabetes Sci. Technol. 7(1), 247–262 (2013)CrossRefGoogle Scholar
  8. 8.
    Zapata, B., Fernandez-Aleman, J., Idri, A., Toval, A.: Empirical studies on usability of mHealth apps: a systematic literature review. J. Med. Syst. 39(2), 1 (2015)CrossRefGoogle Scholar
  9. 9.
    Lyles, C., Sarkar, U., Osborn, C.: Getting a technology-based diabetes intervention ready for prime time: a review of usability testing studies. Curr. Diabetes Rep. 14(10), 534 (2014)CrossRefGoogle Scholar
  10. 10.
    Ritchie, J., Spencer, L.: Qualitative data analysis for applied policy research. In: Bryman, A., Burgess, R. (eds.) Analyzing Qualitative Data, pp. 173–194. Routledge, London (1994)CrossRefGoogle Scholar
  11. 11.
    Keenan, S., Hartson, H., Kafura, D., Schulman, R.: The usability problem taxonomy: a framework for classification and analysis. Empir. Soft. Eng. 4(1), 71–104 (1999)CrossRefGoogle Scholar
  12. 12.
    Gale, N., Heath, G., Cameron, E., Rashid, S., Redwood, S.: Using the framework method for the analysis of qualitative data in multi-disciplinary health research. BMC Med. Res. Methodol. 13, 117 (2013)CrossRefGoogle Scholar
  13. 13.
    Carroll, J., Kellog, W., Rosson, M.: The task-artifact cycle. In: Carroll, J. (ed.) Designing Interaction, pp. 74–102. Cambridge University Press, New York (1991)Google Scholar
  14. 14.
    Richardson, L., Ruby, S.: RESTful Web Services. O’Reilly Media, Sebastopol (2008)Google Scholar
  15. 15.
    Ericsson, K., Simon, H.: Protocol Analysis: Verbal Reports as Data (Revised Edition). The MIT Press, Cambridge (1993)Google Scholar
  16. 16.
    Nielsen, J.: Usability inspection methods. In: CHI 1994 Conference Companion on Human Factors in Computing Systems, pp. 413–414 (1994)Google Scholar
  17. 17.
    Virzi, R.: Refining the test phase of usability evaluation: how many subjects is enough? Hum. Factors 34(4), 457–468 (1992)CrossRefGoogle Scholar
  18. 18.
    Nielsen, J., Molich, R.: Heuristic evaluation of user interfaces. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM (1990)Google Scholar
  19. 19.
    Travis, D.: How to prioritise usability problems, October 2009Google Scholar
  20. 20.
    Karsh, B., Weinger, M., Abbott, P., Wears, R.: Health information technology: fallacies and sober realities. J. Am. Med. Inf. Assoc. 17(6), 617–623 (2010)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jesús Fontecha
    • 1
  • Iván González
    • 1
  • M. Estrella Saucedo
    • 2
  • M. José Sánchez
    • 2
  • José Bravo
    • 1
  1. 1.MAmI Research LabUniversity of Castilla-La ManchaCiudad RealSpain
  2. 2.HGUCRCiudad RealSpain

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