Smartwatch use among older adults: Findings from two large surveys

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Abstract

Access to modern mobile information and communication technologies (ICT) such as smartphones, tablets, smartwatches, and other wearables in later life remains poorly understood, as does the use of such technologies. Even though modern ICT devices permeate daily life, little is known about the distribution of modern handheld assistances such as smartwatches among older adults. This paper presents data on the distribution of smartwatches among older adults (and the predictors of this usage) by utilizing two representative data sets from Switzerland. Secondary analyses were based on two cross-sectional surveys of 1,824 participants (study 1: n = 811, age ≥ 56 years; study 2: n = 1,013, age ≥ 50 years). Both univariate and multivariate analyses were conducted. The results indicate that 4.4% (study 1) and 6.6% (study 2) of participants owned a smartwatch, and most used the technology daily. Univariate analysis showed that education, age, technological affinity, and the use of mobile ICT devices (smartphones, tablets, and fitness trackers) in particular distinguished smartwatch users from nonusers, whereas gender, income, quality of life, subjective health, participation in education offers and sports, and the use of classical ICT devices (such as radio, TV, and computers) were not significant predictors of group differences between user and non-user of smartwatch. Multivariate analyses confirmed the univariate findings by showing that education, interest in technology, and the use of mobile ICT devices predicted smartwatch usage. While the results must be viewed with caution because of the generally low number of smartwatch users, this initial evaluation of smartwatch use among older adults should nevertheless enrich discussions of the acceptance of wearables among them.

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APA

Seifert, A. (2020). Smartwatch use among older adults: Findings from two large surveys. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12207 LNCS, pp. 372–385). Springer. https://doi.org/10.1007/978-3-030-50252-2_28

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