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When it is part of me, I can do it: Using embodied empowerment to predict adherence to wearable self-care technology.

Authors :
Nelson, Elizabeth C.
Verhagen, Tibert
Vollenbroek-Hutten, Miriam M.R.
Noordzij, Matthijs L.
Source :
Computers in Human Behavior. Sep2024, Vol. 158, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

Despite assumptions that wearable self-care technologies such as smart wristbands and smart watches help users to monitor and self-manage health in daily life, adherence rates are often quite low. In an effort to better understand what determines adherence to wearable self-care technologies, researchers have started to consider the extent to which a technology is perceived as being part of the user (i.e., technology embodiment) and the extent to which users feel they can influence reaching their health goals (i.e., empowerment). Although both concepts are assumed to determine adherence, few studies have empirically validated their influence. Furthermore, the relationships between technology embodiment, empowerment, and adherence to wearable self-care technology have also not been addressed. Drawing upon embodied theory and embodiment cognition theory, this research paper introduces and empirically validates 'embodied empowerment' as a predictor of adherence to wearable self-care technology. Using partial least squares structural equation modeling and multigroup analysis on a dataset of 317 wearable self-care technology users, we find empirical evidence of the validity of embodied empowerment as a determinant of adherence. We also discuss the implications for research and practice. • We introduce embodied empowerment to explain adherence to self-care wearables. • Embodiment and empowerment reinforce each other and function in conjunction. • Embodied and empowerment predict adherence to wearable self-care technology. • The results are consistent for male versus female and younger versus older users. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
07475632
Volume :
158
Database :
Academic Search Index
Journal :
Computers in Human Behavior
Publication Type :
Academic Journal
Accession number :
177750461
Full Text :
https://doi.org/10.1016/j.chb.2024.108314