A usability study of a mHealth system for diabetes self-management based on framework analysis and usability problem taxonomy methods

Abstract

Self-management of diabetes through the use of mobile and software systems is a reality today. Among other aspects, usability of these systems determines their continued use by patients, closely related to the concepts of engagement, empowerment and treatment adherence. In this work, we present a detailed usability study of a mHealth system for diabetes self-management by means of an evaluation process, which includes the acquisition of usability data through a hybrid approach and a heuristic evaluation. In addition, data analysis was performed by using framework analysis and usability problem taxonomy. As a result, a set of consolidated usability problems categorized by severity index, source, and other factors is presented and studied, also taking into account the impact of these types of issues from the diabetic patients perspective.

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    http://www.mobihealthnews.com/content/six-month-glooko-pilot-shows-increased-engagement-glucose-control-among-t2-diabetes-patients.

References

  1. Brooke J (2013) Sus: a retrospective. J Usability Stud 8(2):29–40

    Google Scholar 

  2. Carroll J, Kellogg W, Rosson M (1991) designing interaction: psychology at the human–computer interface. Cambridge University Press, Cambridge, pp 74–102

    Google Scholar 

  3. Castelnuovo G, Mauri G, Waki K (2016) mhealth and ehealth for obesity and types 2 an 1 diabetes. Journal of Diabetes Research 2016 https://doi.org/10.1155/2016/9627602

  4. Cheng VW (2017) Studying the effectiveness of game-based solutions in a wellbeing app. In: Extended abstracts publication of the annual symposium on computer–human interaction in Play, pp 691–694, https://doi.org/10.1145/3130859.3133231

  5. Cornet V, Holden R (2018) Systematic review of smartphone-based passive sensing for health and wellbeing. J Biomed Inf 77:120–132

    Article  Google Scholar 

  6. Costa A, de Souza F, Moreira A, de Souza D (2018) Webqda 2.0 versus webqda 3.0: a comparative study about usability of qualitative data analysis software. Stud Comput Intell 718:229–240. https://doi.org/10.1007/978-3-319-58965-7_16

    Google Scholar 

  7. Ericsson KA, Simon HA (1993) Protocol analysis: verbal reports as data. The MIT Press, Cambridge

    Google Scholar 

  8. Fontecha J, Gonzalez I, Saucedo ME, Sanchez MJ, Bravo J (2017) Usability and acceptance of a mobile and cloud-based platform for supporting diabetes self-management. In: Ochoa S, Singh P, Bravo J (eds) Ubiquitous computing and ambient intelligence, Springer, Cham, vol 10586, pp 227–239, DOI 0.1007/978-3-319-67585-5\_24, https://link.springer.com/chapter/10.1007/978-3-319-67585-5_24

  9. Fortino G, Gravina R (2015) A cloud-assisted wearable system for physical rehabilitation. In: Fardoun H, Penichet V, Alghazzawi D (eds) ICTs for improving patients rehabilitation research techniques. communications in computer and information science, vol 515. Springer, Berlin, pp 168–182. https://doi.org/10.1007/978-3-662-48645-0_15

    Google Scholar 

  10. Franklin A, Myneni S (2018) Engagement and design barriers of mhealth applications for older adults. ACM International Conference Proceeding Series. https://doi.org/10.1145/3183654.3183695

  11. Gale NK, Heath G, Cameron E, Rashid S, Redwood S (2013) Using the framework method for the analysis of qualitative data in multi-disciplinary health research. BMC Medical Research Methodology 13(117)

  12. Georgsson M, Staggers N (2016a) An evaluation of patients experienced usability of a diabetes mhealth system using a multi-method approach. J Biomed Inf 56:115–129

    Article  Google Scholar 

  13. Georgsson M, Staggers N (2016b) Quantifying usability: an evaluation of a diabetes mhealth system on effectiveness, efficiency, and satisfaction metrics with associated user characteristics. J Am Med Inform Assoc 23(1):5–11

    Article  Google Scholar 

  14. Hamari J, Koivisto J (2015) Why do people use gamification services? Int J Inf Manag 35(4):419–431. https://doi.org/10.1016/j.ijinfomgt.2015.04.006

    Article  Google Scholar 

  15. Hartz J, Yingling L, Powel-Wiley T (2016) Use of mobile technology in the prevention and management of diabetes mellitus. Curr Cardiol Rep 18(12):130. https://doi.org/10.1007/s11886-016-0796-8

    Article  Google Scholar 

  16. Hwang W, Salvendy G (2010) Number of people required for usability evaluation: the 102 rule. Commun ACM 53(5):130–133. https://doi.org/10.1145/1735223.1735255

    Article  Google Scholar 

  17. Iltchev P, Sliwczyiski A, Szynkiewicz P, Marczak M (2016) M-health innovations for patient-centered care, IGI Global, chap Mobile health applications assisting patients with chronic diseases: Examples from asthma care, pp 170–196. https://doi.org/10.4018/978-1-4666-9861-1.ch009

  18. Isakovic M, Sedlar U, Volk M, Bester J (2016) Usability pitfalls of diabetes mhealth apps for the elderly. J Diabetes Res

  19. Istepanian R, Lacal J (2003) Emerging mobile communication technologies for health: some imperative notes on m-health. In: IEEE (ed) A new beginning for human health. In: Proceddings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol 2, pp 1414–1416

  20. Jia G, Yang P, Zhou J, Zhang H, Lin C, Chen J, Yan J, Ning G (2015) A framework design for the mhealth system for self-management promotion. Biomed Mater Eng 26(s1):s1731–s1740. https://doi.org/10.3233/BME-151473

    Google Scholar 

  21. Karsh BT, Weinger MB, Abbott PA, Wears RL (2010) Health information technology: fallacies and sober realities. J Am Med Inform Assoc 17(6):617–623. https://doi.org/10.1136/jamia.2010.005637

    Article  Google Scholar 

  22. Keenan SL, Harstson HR, Kafura DG, Schulman RS (1999) The usability problem taxonomy: a framework for classification and analysis. Empir Softw Eng 4(1):71–104

    Article  Google Scholar 

  23. Klimova B (2017) Mobile devices and mobile applications used in parkinsons disease. In: 14th international conference on mobile web and intelligent information systems, Springer, vol 10486, pp 137–143

  24. Kushniruk A, Patel V (2004) Cognitive and usability engineering methods for the evaluation of clinical information systems. J Biomed Inform 37(1):56–76. https://doi.org/10.1016/j.jbi.2004.01.003

    Article  Google Scholar 

  25. Lamprinos I, Demski H, Mantwill S, Kabak Y, Hildebrand C, Ploessnig M (2016) Modular ict-based patient empowerment framework for self-management of diabetes: design perspectives and validation results. Int J Med Inf 91:31–43

    Article  Google Scholar 

  26. Lanzola G, Losiuk E, Favero S, Facchinetti A, Galderisi A, Quaglini S, Magni L, Cobelli C (2016) Remote blood glucose monitoring in mhealth scenarios: a review. Sensors 16(12):2–16

    Article  Google Scholar 

  27. Lewis J (2018) Measuring perceived usability: the CSUQ, SUS, and UMUX. Int J Hum Comput Inter 34:1–9. https://doi.org/10.1080/10447318.2017.1418805

    Article  Google Scholar 

  28. Logan A (2013) Transforming hypertension management using mobile health technology for telemonitoring and self-care support. Can J Cardiol 29(5):579–585

    Article  Google Scholar 

  29. McKay F, Cheng C, Wright A, Shill J, Stephens H, Uccellini M (2018) Evaluating mobile phone applications for health behaviour change: a systematic review. J Telemed Telecare 24(1):22–30. https://doi.org/10.1177/1357633X16673538

    Article  Google Scholar 

  30. Nielsen J, Landauer T (1993) A mathematical model of the finding of usability problems. In: Proceedings of the INTERACT 93 and CHI 93 Conference on Human Factors in Computing Systems, ACM, pp 206–213

  31. Nielsen J, Molich R (1990) Heuristic evaluation of user interfaces. In: Proceedings of the SIGCHI Conference on Human factors in computing systems, ACM

  32. Ritchie J, Spencer L (1994) Analyzing qualitative data, SAGE, chap qualitative data analysis for applied policy research, pp 173–194

  33. Sardi L, Idri A, Fernandez-Aleman J (2017) A systematic review of gamification in e-health. J Biomed Inf 71:31–48. https://doi.org/10.1016/j.jbi.2017.05.011

    Article  Google Scholar 

  34. Shneidermann B (1998) Designing the user interface: strategies for effective human–computer interaction. Addison-Wesley Longman, Boston

    Google Scholar 

  35. Slater H, Campbell J, Stinson J, Burley M, Briggs A (2017) End user and implementer experiences of mhealth technologies for noncommunicable chronic disease management in young adults: Systematic review. J Med Internet Res 19(12):e406

    Article  Google Scholar 

  36. Tatara N, Arsand E, Skrovseth S, Hartvigsen G (2013) Long-term engagement with a mobile self-management system for people with type 2 diabetes. J Med Internet Res 13(3):e1. https://doi.org/10.2196/mhealth.2432

    Google Scholar 

  37. Travis D (2009) How to prioritise usability problems. Tech. rep., UserFocus, https://www.userfocus.co.uk/articles/prioritise.html, accessed on February 21, 2018

  38. Villarreal V, Fontecha J, Hervs R, Bravo J (2014) Mobile and ubiquitous architecture for the medical control of chronic diseases through the use of intelligent devices: Using the architecture for patients with diabetes. Future Gener Comput Syst 34:161–175. https://doi.org/10.1016/j.future.2013.12.013

    Article  Google Scholar 

  39. Virzi R (1992) Refining the test phase of usability evaluation: how many subjects is enough? Hum Factors 34(4):457–468

    Article  Google Scholar 

  40. Wong-Rieger D, Rieger FP (2013) Health coaching in diabetes: empowering patients to self-manage. Can J Diabetes 37(1):41–44. https://doi.org/10.1016/j.jcjd.2013.01.001

    Article  Google Scholar 

  41. Zapata B, Fernandez-Aleman J, Idri A, Toval A (2015) Empirical studies on usability of mhealth apps: a system literature review. J Med Syst 39(2):1. https://doi.org/10.1007/s10916-014-0182-2

    Article  Google Scholar 

  42. Zapata BC, Fernandez-Aleman J, Toval A, Idri A (2018) Reusable software usability specifications for mHealth applications. J Med Syst 42(3):451. https://doi.org/10.1007/s10916-018-0902-0

    Google Scholar 

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Acknowledgements

This work has been supported by MAPFRE Foundation and the Plan Propio de Investigación program from Castilla-La Mancha University. Authors gratefully acknowledge the participation and collaboration of all diabetic users, and also M. Estrella Saucedo and M. José Sánchez as clinical experts, in the evaluation process.

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Correspondence to Jesús Fontecha.

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Fontecha, J., González, I. & Bravo, J. A usability study of a mHealth system for diabetes self-management based on framework analysis and usability problem taxonomy methods. J Ambient Intell Human Comput (2019). https://doi.org/10.1007/s12652-019-01369-0

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Keywords

  • Diabetes self-management
  • mHealth
  • Usability
  • Framework analysis
  • Usability problem taxonomy