Open AccessThis study aims to further promote the understanding of the antecedents of the acceptance and use of digital wellness technologies among elderly people through a follow-up to our two prior studies, one which examines the potential longer-term temporal changes in the use intention of digital wellness technologies and its antecedents in the case of the young elderly segment and physical activity logger applications. We base this examination theoretically on UTAUT2 and empirically on survey data …
Author(s) -
Markus Makkonen,
Tuomas Kari,
Lauri Frank
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18690/978-961-286-485-9.39
Subject(s) - expectancy theory , construct (python library) , antecedent (behavioral psychology) , structural equation modeling , psychology , applied psychology , elderly people , technology acceptance model , social psychology , computer science , knowledge management , gerontology , medicine , human–computer interaction , usability , machine learning , programming language
This study aims to further promote the understanding of the antecedents of the acceptance and use of digital wellness technologies among elderly people through a follow-up to our two prior studies, one which examines the potential longer-term temporal changes in the use intention of digital wellness technologies and its antecedents in the case of the young elderly segment and physical activity logger applications. We base this examination theoretically on UTAUT2 and empirically on survey data that is collected from 92 Finnish young elderly users of a physical activity logger application in three subsequent time points and analysed with partial least squares structural equation modelling (PLS-SEM). We find that the initial strong decline in the scores of the antecedent constructs and use intention becomes weaker as the construct scores stabilise over time, whereas especially the effects of performance expectancy and effort expectancy on use intention remain relatively unstable.