Skip to main content

Advertisement

Log in

Patients’ Perspectives on the Usability of a Mobile App for Self-Management following Spinal Cord Injury

  • Mobile & Wireless Health
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

With decreasing inpatient lengths of stay following spinal cord injury (SCI), newly injured patients may be discharged into the community without the self-management skills needed to prevent secondary conditions. A mobile app was developed to facilitate self-management skills following SCI in the inpatient rehabilitation and early community settings. The objective of this study was to explore patients’ perspectives on the usability of this self-management app. A mixed-methods study design was implemented. The app was trialed at a local rehabilitation centre with 20 inpatient participants who experienced a SCI. They received mobile app training sessions throughout their inpatient rehabilitation. A thematic analysis was performed on qualitative data from post-discharge exit questionnaires and researchers’ field notes. Quantitative data (in the form of participants’ tool usage data and self-reported system usability scale scores) were collected at discharge and 3 months post-discharge. Three main themes emerged from the qualitative analysis: (1) being accessible to users (i.e., being easy to adopt and compatible with assistive technologies), (2) being intuitive to navigate (i.e., incorporating a simple app layout and a system of alert notifications), and (3) offering users flexibility (i.e., providing users with control over their data). The mobile app received above average mean system usability scale scores, both at discharge (78.1/100) and 3 months post-discharge (71.6/100). Given that participants found the app acceptable for use in inpatient rehabilitation and following discharge into the community, further testing is warranted to explore its efficacy in preventing secondary complications.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Adriaansen, J. J., Rujis, L., van Koppenhagen, C., van Asbeck, F., Snoek, G., van Kuppevelet, D. et al., Secondary health conditions and quality of life in persons living with spinal cord injury for at least ten years. J. Rehabil. Med. 48(10):853–860, 2016. https://doi.org/10.2340/16501977-2166.

    Article  PubMed  Google Scholar 

  2. Savic, G., Charlifue, S., Glass, C., Soni, B. M., Gerhart, K. A., and Jamous, M. A., British ageing with SCI study: Changes in physical and psychosocial outcomes over time. Top. Spinal. Cord. Inj. Rehabil. 15(3):41–53, 2010. https://doi.org/10.1310/sci1503-41.

    Article  Google Scholar 

  3. Barlow, J., Wright, C., Sheasby, J., Tuner, A., and Hainsworth, J., Self-management approaches for people with chronic conditions: A review. Patient. Educ. Couns. 48(1):177–187, 2002. https://doi.org/10.1016/S0738-3991(02)00032-0.

    Article  PubMed  Google Scholar 

  4. McColl, M. A., Aiken, A., McColl, A., Sakakibara, B., and Smith, K., Primary care for people with spinal cord injury. Can. Fam. Physcian. 58(11):1207–1216, 2012 Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3498012/pdf/0581207.pdf.

    Google Scholar 

  5. Jerant, A. F., von Frieerichs-Fitzwater, M. M., and Moore, M., Patients’ perceived barriers to active self-management of chronic conditions. Patient. Educ. Couns. 57(3):300–307, 2005. https://doi.org/10.1016/j.pec.2004.08.004.

    Article  PubMed  Google Scholar 

  6. Klonoff, D. C., Twelve modern digital technologies that are transforming decision making for diabetes and all areas of health care. J. Diabetes. Sci. Technol. 7(2):291–295, 2013. https://doi.org/10.1177/193229681300700201.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Gill, P. S., Kamath, A., and Gill, T. S., Distraction: An assessment of smartphone usage in health care work settings. Risk. Manag. Healthc. Policy. 5:105–114, 2012. https://doi.org/10.2147/rhmp.s34813.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Arsand, E., Tatara, N., Ostengen, G., and Hartvigsen, G., Mobile phone-based self-management tools for type 2 diabetes: The few touch applications. J. Diabetes. Sci. Technol. 4(2):328–336, 2010. https://doi.org/10.1177/193229681000400213.

    Article  PubMed  PubMed Central  Google Scholar 

  9. El-Gayar, O., Timsina, P., Nawar, N., and Eid, W., Mobile applications for diabetes self-management: Status and potential. J. Diabetes. Sci. Technol. 7(1):247–262, 2013. https://doi.org/10.1177/193229681300700130.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Hardinge, M., Rutter, H., Velardo, C., Shah, S. A., Williams, V., Tarassenko, L., and Farmer, A., Using a mobile health application to support self-management in chronic obstructive pulmonary disease: A six-month cohort study. BMC. Med. Inform. Decis. Mak. 15:46, 2015. https://doi.org/10.1186/s12911-015-0171-5.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Bevan, N., Usability is quality of use. Adv. Hum. Factor. Ergon. 20:349–354, 1995. https://doi.org/10.1016/S0921-2647(06)90241-8.

    Article  Google Scholar 

  12. Georgsson, M., and Staggers, N., 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, 2016. https://doi.org/10.1093/jamia/ocv099.

    Article  PubMed  Google Scholar 

  13. Creswell, J. W., Clark, V. L. P., Gutmann, M. L., and Hanson, W. E., Advanced mixed methods research designs. In: Tashakkori, A., Teddlie, C. (Eds), Handbook of mixed methods in social & behavioral research. Thousand Oaks: Sage, 2003, 209–240.

    Google Scholar 

  14. O'Cathain, A., Murphy, E., and Nicholl, J., The quality of mixed methods studies in health services research. J. Health. Serv. Res. Policy. 13(2):92–98, 2008. https://doi.org/10.1258/jhsrp.2007.007074.

    Article  PubMed  Google Scholar 

  15. O’Brien, B. C., Harris, I. B., Beckman, T. J., Reed, D. A., and Cook, D. A., Standards for reporting qualitative research: A synthesis of recommendations. Acad. Med. 89(9):1245–1251, 2014. https://doi.org/10.1097/acm.0000000000000388.

    Article  PubMed  Google Scholar 

  16. ISO FDIS 9241–10. Ergonomics of human system interaction – Part 210: human-centered design for interactive systems. 2009; Switzerland: International Organization for Standardization.

  17. Mortenson, W. B., Singh, G., MacGillivray, M., Sadeghi, M., Mills, P., Adams, J., and Sawatzky, B., Development of a self-management app for people with spinal cord injury. J. Med. Syst. 43(6):145, 2019. https://doi.org/10.1007/s10916-019-1273-x.

    Article  PubMed  Google Scholar 

  18. Maynard, Jr., F. M., Bracken, M. B., Creasey, G., Ditunno, J. F., Donovan, W. H., Ducker, T. B., Garber, S. L., Marino, R. J., Stover, S. L., Tator, C. H., Waters, R. L., Wilberger, J. E., and Young, W., International standards for neurological and functional classification of spinal cord injury. Spinal. Cord. 35(5):266–274, 1997. https://doi.org/10.1038/sj.sc.3100432.

    Article  PubMed  Google Scholar 

  19. Kehn, M., and Kroll, T., Staying physically active after spinal cord injury: A qualitative exploration of barriers and facilitators to exercise participation. BMC. Public. Health. 9:168, 2009. https://doi.org/10.1186/1471-2458-9-168.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Munce, S. E. P., Webster, F., Fehlings, M. G., Straus, S. E., Nugaeva, N., Jang, E., Webster, F., and Jaglal, S. B., View of people with traumatic spinal cord injury about the components of self-management programs and program delivery: a Canadian polot study. BMC. Neurology. 14:209, 2014. https://doi.org/10.1186/s12883-014-0209-9.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Stephens, C., Neil, R., and Smith, P., The perceived benefits and barriers of sport in spinal cord injured individuals: A qualitative study. Disabil. Rehabil. 34(24):2061–2070, 2012. https://doi.org/10.3109/09638288.2012.669020.

    Article  PubMed  Google Scholar 

  22. Lewis, J. R., The system usability scale: Past, present, and future. Int. J. Human.-Comput. Interact. 34(7):577–590, 2018. https://doi.org/10.1080/10447318.2018.1455307.

    Article  Google Scholar 

  23. Braun, V., and Clarke, V., Successful qualitative research: a practical guide for beginners. London: Sage, 2013.

    Google Scholar 

  24. Parasuraman, A., Technology readiness index (TRI) a multiple-item scale to measure readiness to embrance new technologies. J. Serv. Res. 2:307–320, 2000. https://doi.org/10.1177/109467050024001.

    Article  Google Scholar 

  25. Horrigan JB. Digital readiness gaps [online]. Pew Research Centre. 2016. Available from: https://www.pewinternet.org/2016/09/20/digital-readiness-gaps/

  26. Gordon, N. P., and Hornbrook, M. C., Older adult’ readiness to engage with eHealth patient education and self-care resources: A cross-sectional survey. BMC. Health. Serv. Res. 18(1):220, 2018. https://doi.org/10.1186/s12913-018-2986-0.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Lin, C. H., Shih, H. Y., and Sher, P. J., Integrating technology readiness into technology acceptance: The TRAM model. Psychol. Market. 24(7):641–657, 2007. https://doi.org/10.1002/mar.20177.

    Article  Google Scholar 

  28. Erdogmus, N., and Esen, M., An investigation of the effects of technology readiness on technology acceptance in e-HRM. Procedia. Soc. Behav. Sci. 24:487–495, 2011. https://doi.org/10.1016/j.sbspro.2011.09.131.

    Article  Google Scholar 

  29. Walczuch, R., Lemmink, J., and Struekens, S., The effect of service employees’ technology readiness on technology acceptance. Inform. Manag. 44:206–2015, 2007.

    Article  Google Scholar 

  30. Godoe, P., and Johansen, T. S., Understanding adoption of new technologies: Technology readiness and technology acceptance as an integrated concept. J. Eur. Psychol. Stud. 3(1):38–52, 2012. https://doi.org/10.5334/jeps.aq.

    Article  Google Scholar 

  31. Larasati, N., and Widyawan, S. P. I., Technology readiness and technology acceptance model in new technology implementation process in low technology SMEs. Int. J. Innovation. Manage. Technol. 8(2):113–117, 2017. https://doi.org/10.18178/ijimt.2017.8.2.713.

    Article  Google Scholar 

  32. Marhefka, S. L., Turner, D., and Lockhart, E., Understanding women’s willingness to use e-health for HIV-related services: A novel application of the technology readiness and acceptance model to a highly stigmatized medical condition. Telemed. J. E. Health., 2018. https://doi.org/10.1089/tmj.2018.0066.

    Article  Google Scholar 

  33. Davis, F. D., Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS. Quarterly. 13(3):319–340, 1989. https://doi.org/10.2307/249008.

    Article  Google Scholar 

  34. Kim, J., and Park, H. A., Development of a health information technology acceptance model using consumers’ health behavior intention. J Med Internet Res 14(5):e133, 2012. https://doi.org/10.2196/jmir.2143.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Mayman, G., Perera, M., Meade, M. A., Jennie, J., and Maslowski, E., Electronic device use by individuals with traumatic spinal cord injury. J. Spinal. Cord. Med. 40(4):449–455, 2017. https://doi.org/10.1080/10790268.2016.1248525.

    Article  PubMed  Google Scholar 

  36. Kim, S., Lee, B. S., and Kim, J. M., Comparison of the using ability between a smartphone and a conventional mobile phone in people with cervical cord injury. Ann Rehabil Med 38(2):183–188, 2014. https://doi.org/10.5535/arm.2014.38.2.183.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Sears, A., Kara, C. M., Oseitutu, K., Karimullah, A., and Feng, J., Productivity, satisfaction, and interaction strategies of individuals with spinal cord injuries and traditional users interacting with speech recognition software. Universal. Access. Inf. Soc. 1(1):4–15, 2001. https://doi.org/10.1007/s102090100001.

    Article  Google Scholar 

  38. Peng, W., Kanthawala, S., Yuan, S., and Hussain, S. A., A qualitative study of user perceptions of mobile health apps. BMC. Public. Health. 16(1):1158, 2016. https://doi.org/10.1186/s12889-016-3808-0.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Reynoldson, C., Stones, C., Allsop, M., Gardner, P., Bennett, M. I., Closs, S. J., Jones, R., and Knapp, P., Assessing the quality and usability of smartphone apps for pain self-management. Pain. Med. 15(6):898–909, 2014. https://doi.org/10.1111/pme.12327.

    Article  PubMed  Google Scholar 

  40. Kayser, L., Kushniruk, A., Osborne, R. H., Norgaard, O., and Turner, P., Enhancing the effectiveness of consumer-focused health information technology systems through eHealth literacy: A framework for understanding users’ needs. JMIR. Hum. Factors. 2(1):e9, 2015. https://doi.org/10.2196/humanfactors.3696.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Alkhaldi, G., Hamilton, F. L., Lau, R., Webster, R., Michie, S., and Murray, E., The effectiveness of prompts to promote engagement with digital interventions: A systematic review. J. Med. Internet. Res. 18(1):e6, 2016. https://doi.org/10.2196/jmir.4790.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Freyne, J., Yin, J., Brindal, E., Hendrie, G. A., Berkovsky, S., and Noakes, M., Push notifications in diet apps: Influencing engagement times and tasks. Int. J. Hum. Comput. Interact. 33(10):833–845, 2017. https://doi.org/10.1080/10447318.2017.1289725.

    Article  Google Scholar 

  43. Morrison, L. G., Hargood, C., Pejovic, V., Geraghty, A. W. A., Lloyd, S., Goodman, N., Michaelides, D. T., Weston, A., Musolesi, M., Weal, M. J., and Yadley, L., The effect of timing and frequency of push notifications on usage of a smartphone-based stress management intervention: An exploratory trial. PLOS. ONE. 13(5):e0198008, 2018. https://doi.org/10.1371/journal.pone.0198008.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Heffernan, K. J., Chang, S., Maclean, S. T., Callegaru, E. T., Garland, S. M., Reavley, N. R., Varigos, G., and Wark, J. D., The potential of eHealth apps to support targeted complex health messages. J. Gen. Pract. 2(5):1–7, 2014. https://doi.org/10.4172/2329-9126.10001182.

    Article  Google Scholar 

  45. Oinas-Kukkonen, H., and Harjumaa, M., Towards deeper understanding of persuasion in software and information systems. Proc. Adv. Comput.-Human .Inter. https://doi.org/10.1109/achi.2008.31.

  46. Bidargaddi, N., Pituch, T., Maaieh, H., Short, C., and Strecher, V., Predicting which type of push notification content motivates users to engage in a self-monitoring app. Prev Med Rep 11:267–273, 2018. https://doi.org/10.1016/j.pmedr.2018.07.004.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Gkatzidou, V., Hone, K., Sutcliffe, L., Gibbs, J., Sadiq, S. T., Szczepura, A., Sonnenberg, P., and Estcourt, C., User interface design for mobile-based sexual health interventions for young people: Design recommendations from a qualitative study on an online chlamydia clinical care pathway. BMC. Med. Inf. Decis. Mak. 15:72, 2015. https://doi.org/10.1186/s12911.015-0197-8.

    Article  Google Scholar 

  48. Neubeck, L., Lowres, N., Benjamin, E. J., Freedman, S. B., Coorey, G., and Redfern, J., The mobile revolution – Using smartphone apps to prevent cardiovascular disease. Nat. Rev. Cardiol. 12(6):350, 2015. https://doi.org/10.1038/nrcardio.2015.34.

    Article  PubMed  Google Scholar 

  49. Jobe, W., Native apps versus mobile web apps. Int. J. Interact. Mobile. Technol. 7(4):27–32, 2013. https://doi.org/10.3991/ijim.v7i4.3226.

    Article  Google Scholar 

  50. Selvarajah, K., Craven, M. P., Massey, A., Crowe, J., Vedhara, K., and Raine-Fenning, N., Native apps versus web apps: Which is best for health care applications? Int Conf Hum Comput Interact:189–196, 2013.

  51. Xiang, J., and Stanley, S. J., From online to offline: Exploring the role of e-health consumption, patient involvement, and patient-centered communication on perceptions of health care quality. Comput. Health. Behav. 70:446–452, 2017. https://doi.org/10.1016/j.chb.2016.12.072.

    Article  Google Scholar 

  52. Lee, K., Kwon, H., Lee, B., Lee, G., Lee, J. H., Park, Y. R., and Shin, S. Y., Effect of self-monitoring on long-term patient engagement with mobile health applications. PLoS. One. 13(7):e0201166, 2018. https://doi.org/10.1371/journal.pone.0201166.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Grindod, K. A., Li, M., and Gates, A., Evaluating user perceptions of mobile medication management applications with older adults: A usability study. JMIR. mHealth. uHealth. 2(1):e11, 2014. https://doi.org/10.2196/mhealth.3048.

    Article  Google Scholar 

  54. Isakovic, M., Sedlar, U., Volk, M., and Bester, J., Usability pitfalls of diabetes mHealth apps for the elderly. J. Diabetes. Res.:1–9, 2016. https://doi.org/10.1155/2016/1604609.

    Article  Google Scholar 

  55. Tatara, N., Arsand, E., Skrovseth, S. O., and Hartvigsen, G., Long-term engagement with a mobile self-management system for people with type 2 diabetes. JMIR. mHealth. uHealth. 1(1):e1, 2013. https://doi.org/10.2196/mhealth.2432.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to W. Ben Mortenson.

Ethics declarations

Declaration of Interest

The authors WBM, GS, MKM, MS, PBM, BJS report no real or perceived conflicts of interest. JA has a conflict of interest as he works as a research and development officer for Self Care Catalysts, a company that may benefit from the mobile app. Conflict of interest was mitigated by Self Catalysts (including JA) having no access to any research data, which remained on the University of British Columbia premises. JA was not involved in the analysis of the data but was involved in reviewing the final draft of the paper. Funding for the research study was provided by the Rick Hansen Institute’s ‘Emerging Interventions & Innovative Technologies’ grant (Grant No. G2015–11). Dr. Mortenson’s work was supported by a New Investigator Award from the Canadian Institutes of Health Research.

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 Mobile & Wireless Health

Appendix

Appendix

Table 1 App Tool Usage and Data Entry
Table 2 Participants enrolled versus screened (in total, 72 participants’ charts were screened)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Singh, G., MacGillivray, M., Mills, P. et al. Patients’ Perspectives on the Usability of a Mobile App for Self-Management following Spinal Cord Injury. J Med Syst 44, 26 (2020). https://doi.org/10.1007/s10916-019-1487-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10916-019-1487-y

Keywords

Navigation