Factors Influencing Continued Wearable Device Use in Older Adult Populations: Quantitative Study.

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dc.contributor.authorMuñoz Esquivel, Karlaen
dc.contributor.authorGillespie, Jamesen
dc.contributor.authorKelly, Danielen
dc.contributor.authorCondell, Joan,en
dc.contributor.authorDavies, Richarden
dc.contributor.authorMcHugh, Catherineen
dc.contributor.authorDuffy, Williamen
dc.contributor.authorNevala, Elinaen
dc.contributor.authorAlamäki, Anttien
dc.contributor.authorJalovaara, Juhaen
dc.contributor.authorTedesco, Salvatoreen
dc.contributor.authorBarton, Johnen
dc.contributor.authorTimmons, Suzanneen
dc.contributor.authorNordström, Annaen
dc.contributor.funderInterreg
dc.date.accessioned2023-04-26T15:26:46Z
dc.date.available2023-04-26T15:53:35Zen
dc.date.available2023-04-26T15:26:46Z
dc.date.issued2023-01-19
dc.date.updated2023-04-26T14:53:36Z
dc.description.abstractThe increased use of wearable sensor technology has highlighted the potential for remote telehealth services such as rehabilitation. Telehealth services incorporating wearable sensors are most likely to appeal to the older adult population in remote and rural areas, who may struggle with long commutes to clinics. However, the usability of such systems often discourages patients from adopting these services. This study aimed to understand the usability factors that most influence whether an older adult will decide to continue using a wearable device. Older adults across 4 different regions (Northern Ireland, Ireland, Sweden, and Finland) wore an activity tracker for 7 days under a free-living environment protocol. In total, 4 surveys were administered, and biometrics were measured by the researchers before the trial began. At the end of the trial period, the researchers administered 2 further surveys to gain insights into the perceived usability of the wearable device. These were the standardized System Usability Scale (SUS) and a custom usability questionnaire designed by the research team. Statistical analyses were performed to identify the key factors that affect participants' intention to continue using the wearable device in the future. Machine learning classifiers were used to provide an early prediction of the intention to continue using the wearable device. The study was conducted with older adult volunteers (N=65; mean age 70.52, SD 5.65 years) wearing a Xiaomi Mi Band 3 activity tracker for 7 days in a free-living environment. The results from the SUS survey showed no notable difference in perceived system usability regardless of region, sex, or age, eliminating the notion that usability perception differs based on geographical location, sex, or deviation in participants' age. There was also no statistically significant difference in SUS score between participants who had previously owned a wearable device and those who wore 1 or 2 devices during the trial. The bespoke usability questionnaire determined that the 2 most important factors that influenced an intention to continue device use in an older adult cohort were device comfort (t=0.34) and whether the device was fit for purpose (t=0.34). A computational model providing an early identifier of intention to continue device use was developed using these 2 features. Random forest classifiers were shown to provide the highest predictive performance (80% accuracy). After including the top 8 ranked questions from the bespoke questionnaire as features of our model, the accuracy increased to 88%. This study concludes that comfort and accuracy are the 2 main influencing factors in sustaining wearable device use. This study suggests that the reported factors influencing usability are transferable to other wearable sensor systems. Future work will aim to test this hypothesis using the same methodology on a cohort using other wearable technologies.en
dc.description.sponsorshipInterreg (Northern Periphery and Arctic Programme 2014-2020 grant 93)
dc.description.statusPeer revieweden
dc.description.versionPublished Version
dc.format.mimetypeapplication/pdfen
dc.identifier.articleide36807
dc.identifier.citationMuñoz Esquivel, K., Gillespie, J., Kelly, D., Condell, J., Davies, R., McHugh, C., Duffy, W., Nevala, E., Alamäki, A., Jalovaara, J., Tedesco, S., Barton, J., Timmons, S. and Nordström, A. (2023) ‘Factors influencing continued wearable device use in older adult populations: quantitative study’, JMIR Aging, 6, p. e36807 (17 pp). https://doi.org/10.2196/36807
dc.identifier.doi10.2196/36807en
dc.identifier.endpage17
dc.identifier.issn2561-7605
dc.identifier.journaltitleJMIR Aging
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/10468/14408
dc.identifier.volume6
dc.language.isoenen
dc.publisherJMIR Publications
dc.rights© Karla Muñoz Esquivel, James Gillespie, Daniel Kelly, Joan Condell, Richard Davies, Catherine McHugh, William Duffy, Elina Nevala, Antti Alamäki, Juha Jalovaara, Salvatore Tedesco, John Barton, Suzanne Timmons, Anna Nordström. Originally published in JMIR Aging (https://aging.jmir.org), 19.01.2023. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Aging, is properly cited. The complete bibliographic information, a link to the original publication on https://aging.jmir.org, as well as this copyright and license information must be included.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectUsability
dc.subjectOlder adults
dc.subjectRemote sensing
dc.subjectSensor systems
dc.titleFactors Influencing Continued Wearable Device Use in Older Adult Populations: Quantitative Study.en
dc.typeArticle (peer-reviewed)en
dc.typeArticleen
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