Hostname: page-component-76fb5796d-9pm4c Total loading time: 0 Render date: 2024-04-27T00:41:12.526Z Has data issue: false hasContentIssue false
  • English
  • Français

PERSONAL TECHNOLOGY USE AMONGST STROKE PATIENTS: UNDERSTANDING THE BEST PLATFORMS FOR THE DESIGN OF HEALTH INTERVENTIONS IN TREATMENT AND REHABILITATION

Published online by Cambridge University Press:  27 July 2021

Nicholas William Ciccone ,
Frederik L Dornonville de la Cour ,
Julia Rosemary Thorpe ,
Birgitte Hysse Forchhammer  and
Anja Maier
Nicholas William Ciccone*
Affiliation:
DTU–Technical University of Denmark;
Frederik L Dornonville de la Cour
Affiliation:
DTU–Technical University of Denmark;
Julia Rosemary Thorpe
Affiliation:
Novo Nordisk A/S;
Birgitte Hysse Forchhammer
Affiliation:
The Danish Stroke Association
Anja Maier
Affiliation:
DTU–Technical University of Denmark;
*
Ciccone, Nicholas William, Danish Technical University (DTU), Management Engineering, Denmark, nicic@dtu.dk

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Europe's healthcare systems are under strain with an ageing population contributing to increased risk of strokes. Rapid technology adaption is needed to prevent, rehabilitate and manage symptoms. This paper identifies what technology platforms are most familiar and accessible to stroke patients to guide designers and engineers to develop future interventions. A survey was distributed to 100 inpatients at a stroke unit, identifying patients' accessibility and usage of personal technologies. Results showed that desktop/laptops and smartphones were most used as opposed to tablets and smartwatches. Different technologies were used for different tasks with a notable lack of devices used for personal health. The underlying reasons for this are discussed with recommendations made on what personal technology platforms should be implemented by designers and engineers in technology-based health interventions.

Keywords

TechnologyNew product developmentUser centred designStrokeIntervention
Type
Article
Information
Proceedings of the Design Society , Volume 1: ICED21 , August 2021 , pp. 2419 - 2428
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2021. Published by Cambridge University Press

References

Alexy, E. M. (2000). Computers and caregiving: Reaching out and redesigning interventions for homebound older adults and caregivers. Holistic Nursing Practice, 4(14), 60-66.10.1097/00004650-200007000-00009CrossRefGoogle Scholar
Alvseike, H., & Brønnick, K. (2012). Feasibility of the iPad as a hub for smart house technology in the elderly; Effects of cognition, self-efficacy, and technology experience. J. Multidiscip. Healthcare, 299–306.10.2147/JMDH.S35344CrossRefGoogle ScholarPubMed
Auerbach, A. D., Kripalani, S., & Vasilevskis, E. (2016). Preventability and causes of readmissions in a National Cohort of general medicine patients. JAMA Intern Med, 176, 484–493.10.1001/jamainternmed.2015.7863CrossRefGoogle Scholar
Bain, L., Flynn, D., & Stroud, C. (2018). Harnessing Mobile Devices for Nervous System Disorders. Forum on Neuroscience and Nervous System Disorders. Washington, DC: The National Academic Press.Google Scholar
Broeren, J., Bjorkdahl, A., Claesson, L., Goude, D., Lundgren-Nilsson, A., Samuelsson, H., & Rydmark, M. (2008). Virtual rehabilitation after stroke. Studies in health technology and informatics, 136.Google ScholarPubMed
Caughlin, S., Mehta, S., Corriveau, H., Eng, J. J., Eskes, G., Kairy, D., & Teasell, …, R. (2020). Implementing telerehabilitation after stroke: lessons learned from canadian trials. Telemedicine and e-Health, 26(6), 710-719.CrossRefGoogle ScholarPubMed
Coleman, R., Lebbon, C., Clarkson, J., & Keates, S. (2003). From margins to mainstream. In Inclusive design Springer, London, 1-25.Google Scholar
Czaja, S. J., Charness, N., Fisk, A. D., Hertzog, C., Nair, S. N., & Rogers, W. A. (2006). Factors predicting the use of technology: findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE). Psychol. Aging (21), 333–352.10.1037/0882-7974.21.2.333CrossRefGoogle Scholar
DESI. (2018). DESI Report 2018. European Commission.Google Scholar
Dou, K, Yu, P, Deng, N, Liu, F, Guan, Y, Li, Z, et al. . Patients' acceptance of smartphone health technology for chronic disease management: a theoretical model and empirical test. JMIR Mhealth Uhealth 2017 Dec 6;5(12): e17710.2196/mhealth.7886CrossRefGoogle Scholar
Eurostat. (2017). People in the EU - statistics on an ageing society.Google Scholar
Essén, A., & Östlund, B. (2011). Laggards as innovators? Old users as designers of new services & service systems. International Journal of Design, 5(3).Google Scholar
Free, C., Phillips, G., Watson, L., Galli, L., Felix, L., Edwards, P., & Haines, A. (2013). The effectiveness of mobile-health technologies to improve health care service delivery processes: a systematic review and meta-analysis. PLoS medicine, 10(1).10.1371/journal.pmed.1001363CrossRefGoogle ScholarPubMed
GSMA. (2019). Mobile Economy Europe 2019. 2019: GSM Association. Retrieved from https://www.gsmaintelligence.com/research/?file=b9a6e6202ee1d5f787cfebb95d3639c5&downloadGoogle Scholar
Goodman-Deane, J., Bradley, M., & Clarkson, P. J. (2020). Digital technology competence and experience in the UK population: who can do what. Proceedings of ergonomics and human factors.Google Scholar
Hart, T., Chaparro, B., & Halcomb, C. (2008). Evaluating websites for older adults: Adherence to senior-friendly guidelines and end-user performance. Behaviour & Information Technology, 3(27), 191-199.10.1080/01449290600802031CrossRefGoogle Scholar
Heinz, M., Martin, P., Margrett, J. A., Yearns, M., Franke, W., & Yang, H. (2013). Perceptions of technology among older adults. Gerontol. Nurs(39), 42–51.10.3928/00989134-20121204-04CrossRefGoogle ScholarPubMed
Hood, L. (2013). Systems biology and p4 medicine: past, present, and future. Rambam Maimonides medical journal, 4(2).10.5041/RMMJ.10112CrossRefGoogle ScholarPubMed
Hubert, G. L., Santo, G., Vanhooren, G., Zvan, B., Tur Campos, S., Alasheev, A., & Corea, F. (2019). Recommendations on telestroke in Europe. European stroke journal, 4(2), 101-109.CrossRefGoogle ScholarPubMed
Juznic, P., Blazic, M., Mercun, T., & Plestenjak, B. (2006). Who says that old dogs cannot learn new tricks? New Library World, 8(107), 332-345.10.1108/03074800610677308CrossRefGoogle Scholar
Kulcsar, M., Gilchrist, S., & George, M. G. (2014). Improving stroke outcomes in rural areas through telestroke programs: an examination of barriers, facilitators, and state policies. Telemedicine and e-Health, 3-10.10.1089/tmj.2013.0048CrossRefGoogle ScholarPubMed
Lee, C., & Coughlin, J. F. (2015). Perspective: Older adults' adoption of technology: an integrated approach to identifying determinants and barriers. Journal of Product Innovation Management, 747-759.10.1111/jpim.12176CrossRefGoogle Scholar
Lutze, R., & Waldhör, K. (2015). A smartwatch software architecture for health hazard handling for elderly people. 2015 International Conference on Healthcare Informatics, 356-361.10.1109/ICHI.2015.50CrossRefGoogle Scholar
Macoir, J., Lavoie, M., Routhier, S., & Bier, N. (2019). Key factors for the success of self-administered treatments of poststroke aphasia using technologies. Telemedicine and e-Health, 663-670.10.1089/tmj.2018.0116CrossRefGoogle ScholarPubMed
Matchar, D. B. (2015). International Comparison of Poststroke Resource Use: A Longitudinal Analysis in Europe. Journal of Stroke and Cerebrovascular Diseases, 24(10), 2256- 2262.10.1016/j.jstrokecerebrovasdis.2015.06.020CrossRefGoogle ScholarPubMed
Meskó, B., Drobni, Z., Bényei, É., Gergely, B., & Győrffy, Z. (2017). Digital health is a cultural transformation of traditional healthcare. Mhealth, 3.10.21037/mhealth.2017.08.07CrossRefGoogle Scholar
Micallef, N., Baillie, L., & Uzor, S. (2016). Time to exercise!: an aide-memoire stroke app for post-stroke arm rehabilitation. Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services, 112-123.Google Scholar
Norrving, B., Barrick, J., Davalos, A., Dichgans, M., Cordonnier, C., Guekht, A., & Nabavi, D. (2018). Action plan for stroke in Europe 2018–2030. European Stroke Journal, 3(4), 309-336.CrossRefGoogle ScholarPubMed
O'Hanlon, A., Bond, R., Knapp, B., & Carragher, L. (2010). The Nestling Project: Attitudes toward technology and associations with health, relationships, and quality of life. Gerontechnology, 2(9), 236.Google Scholar
Olivirs, J., Gamito, P., Morais, D., Brito, R., Lopes, P., & Norberto, L. (2014). Cognitive assessment of stroke patients with mobile apps: a controlled study. Studies in health technology and informatics, 103-107.Google Scholar
Osvath, P., Kovacs, A., Boda-Jorg, A., Tenyi, T., & Fekete, S. (2018). The Use of Information and Communication Technology in Elderly and Patients with Dementia. J Gerontol Geriatr Res, 475.10.4172/2167-7182.1000475CrossRefGoogle Scholar
Palacholla, RS, Fischer, N, Coleman, A, Agboola, S, Kirley, K, Felsted, J, Katz, C, Lloyd, S, Jethwani, K. Provider- and patient-related barriers to and facilitators of digital health technology adoption for hypertension management: scoping review. JMIR Cardio 2019; 3(1):e1195110.2196/11951CrossRefGoogle ScholarPubMed
Patel, S., Hughes, R., Hester, T., Stein, J., Akay, M., Dy, J., & Bonato, P. (2010). Tracking motor recovery in stroke survivors undergoing rehabilitation using wearable technology. Annual International Conference of the IEEE Engineering in Medicine and Biology, 6858-6861.Google ScholarPubMed
Patou, F., Ciccone, N., Thorpe, J. R., & Maier, A. (2020). Designing P4-Predictive, Preventive, Personalised and Participative-Healthcare Interventions for Managing Cognitive Decline and Dementia: Where are we at? . Journal of Engineering Design.10.1080/09544828.2020.1763272CrossRefGoogle Scholar
Patou, F., & Maier, A. (2017). Engineering value-effective healthcare solutions: A systems design perspective. ICED17. Design Society.Google Scholar
Pratt, M., Sarmiento, O. L., & Montes, F. (2012). The implications of megatrends in information and communication technology and transportation for changes in global physical activity. Lancet(380), 282-293.CrossRefGoogle ScholarPubMed
Royal College of Physicians. (2016). Mind the Gap! The Third SSNAP Annual Report. London: Royal College of Physicians.Google Scholar
Sagner, M., McNeil, A., Puska, P., Auffray, C., Price, N. D., Hood, L., & McEwen, B. S. (2017). The P4 health spectrum–a predictive, preventive, personalized and participatory continuum for promoting healthspan. Progress in cardiovascular diseases. 59(5), 506-521.10.1016/j.pcad.2016.08.002CrossRefGoogle ScholarPubMed
Scher, D. L. (2015). Will the Apple Watch Revolutionize Healthcare? Medscape Business of Medicine. Retrieved from Medscape: http://www.medscape.com/viewarticle/845762Google Scholar
Song, J., Kim, J., Jones, D. R., Baker, J., & Chin, W. W. (2014). Application discoverability and user satisfaction in mobile application stores: an environmental psychology perspective. Decision Support Systems(59), 37–51.10.1016/j.dss.2013.10.004CrossRefGoogle Scholar
Steinhubl, S. R., Muse, E. D., & Topol, E. J. (2013). Can mobile health technologies transform health care?. Jama, 310(22), 2395-2396.10.1001/jama.2013.281078CrossRefGoogle ScholarPubMed
Stevens, E., Emmett, E., Wang, Y., Mckevitt, C., & Wolfe, C. (2017). The Burdon of Stroke in Europe. Stroke Alliance for Europe.Google Scholar
Stroke Alliance for Europe. (2019). The Burden of Stroke in Europe. Belgium.Google Scholar
Thayer, S. E., & Ray, S. (2006). Online communication preferences across age, gender, and duration of internet use. Cyberpsychology & Behaviour, 4(9), 432-440.10.1089/cpb.2006.9.432CrossRefGoogle Scholar
Thorpe, J., Forchhammer, B. H., & Maier, A. M. (2019). Adapting Mobile and Wearable Technology to Provide Support and Monitoring in Rehabilitation for Dementia: Feasibility Case Series. JMIR Formative Research, 3(4).10.2196/12346CrossRefGoogle ScholarPubMed
Ting, D. S., Carin, L., Dzau, V., & Wong, T. Y. (2020). Digital technology and COVID-19. Nature medicine, 459-461.CrossRefGoogle ScholarPubMed
Nations, United. (2017). World Population Prospects: The 2017 Revision, Key Findings and Advance Tables. Department of Economic and Social Affairs, Population Division.Google Scholar
Vaportzis, E., Giatsi Clausen, M., & Gow, A. J. (2017). Older adults perceptions of technology and barriers to interacting with tablet computers: a focus group study. Frontiers in psychology(8), 1687.10.3389/fpsyg.2017.01687CrossRefGoogle Scholar
Vassli, L. T., & Farshchian, B. A. (2018). Acceptance of health-related ICT among elderly people living in the community: A systematic review of qualitative evidence. International Journal of Human–Computer Interaction, 99-116.CrossRefGoogle Scholar
Vatavu, R. D. (2017). Visual impairments and mobile touchscreen interaction: state-of-the-art, causes of visual impairment, and design guidelines. International Journal of Human–Computer Interaction, 486-509.10.1080/10447318.2017.1279827CrossRefGoogle Scholar
Wagner, N., Hassanein, K., & Head, M. (2010). Computer use by older adults: A multi-disciplinary review. Computers in human behaviour, 5(26), 870-882.10.1016/j.chb.2010.03.029CrossRefGoogle Scholar
Whitelaw, S., Pellegrini, D. M., Mamas, M. A., Cowie, M., & Van Spall, H. G. (2021). Barriers and facilitators of the uptake of digital health technology in cardiovascular care: a systematic scoping review. European Heart Journal-Digital Health.10.1093/ehjdh/ztab005CrossRefGoogle Scholar
Wilson, D. (2017). An overview of the application of wearable technology to nursing practice. Nursing practice, 124-132.Google ScholarPubMed
Organisation, World Health. (2018). Total health expenditure as % of GDP. Retrieved from European Health Information Gateway: https://gateway.euro.who.int/en/indicators/hfa_566-6711-total-health-expenditure-as-of-gdp/visualizations/#id=19661&tab=notesGoogle Scholar
Zhou, J., Rau, P. L., & Salvendy, G. (2012). Use and design of handheld computers for older adults: A review and appraisal. International Journal of Human-Computer Interaction, 799-826.10.1080/10447318.2012.668129CrossRefGoogle Scholar
Zhou, J., Rau, P. L., & Salvendy, G. (2014). Older adults’ text entry on smartphones and tablets: investigating effects of display size and input method on acceptance and performance. International Journal of Human-Computer Interaction, 727-739.10.1080/10447318.2014.924348CrossRefGoogle Scholar