A4 Article in conference proceedings
Applying UTAUT2 to Explain the Use of Physical Activity Logger Applications Among Young Elderly (2020)


Makkonen, M., Kari, T., & Frank, L. (2020). Applying UTAUT2 to Explain the Use of Physical Activity Logger Applications Among Young Elderly. In A. Pucihar, M. Kljajic Borstnar, R. Bons, H. Cripps, A. Sheombar, & D. Vidmar (Eds.), 33rd Bled eConference : Enabling technology for a sustainable society (pp. 567-582). University of Maribor. https://doi.org/10.18690/978-961-286-362-3.38


JYU authors or editors


Publication details

All authors or editorsMakkonen, Markus; Kari, Tuomas; Frank, Lauri

Parent publication33rd Bled eConference : Enabling technology for a sustainable society

Parent publication editorsPucihar, Andreja; Kljajic Borstnar, Mirjana; Bons, Roger; Cripps, Helen; Sheombar, Anand; Vidmar, Doroteja

Conference:

  • Bled eConference

Place and date of conferenceBled, Slovenia28.-29.6.2020

eISBN978-961-286-362-3

Publication year2020

Pages range567-582

Number of pages in the book734

PublisherUniversity of Maribor

Place of PublicationMaribor

Publication countrySlovenia

Publication languageEnglish

DOIhttps://doi.org/10.18690/978-961-286-362-3.38

Persistent website addresshttps://press.um.si/index.php/ump/catalog/view/483/586/918-3

Publication open accessOpenly available

Publication channel open accessOpen Access channel

Publication is parallel published (JYX)https://jyx.jyu.fi/handle/123456789/71091


Abstract

Digital wellness technologies have been proposed as a promising way to promote the levels of physical activity and to solve the prevalent problem of physical inactivity among elderly people. In this study, we propose and test a research model for explaining the acceptance and use of these technologies in the case of the young elderly segment (people aged 60–75 years) and physical activity logger applications. The proposed model is theoretically founded on UTAUT2, and it is empirically tested by using the data collected from 115 Finnish young elderly users of a physical activity logger application and analysed with partial least squares based structural equation modelling (PLS-SEM). We find habit to act as the strongest antecedent of use intention, followed by performance expectancy and hedonic motivation with approximately equally strong effects. In contrast, the effects of effort expectancy and social influence on use intention were found as statistically not significant.


Keywordswelfare technologyphysical activityolder peoplephysical trainingmeasuring instruments (devices)measuring methods

Free keywordsphysical activity; logger applications; young elderly; UTAUT2; digital wellness technologies; partial least squares


Contributing organizations


Ministry reportingYes

Reporting Year2020

JUFO rating1


Last updated on 2024-11-03 at 14:27