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Comparison of Older and Younger Adults’ Attitudes Toward the Adoption and Use of Activity Trackers

BACKGROUND: Activity tracking devices have significant potential in assisting older adults’ health care and quality of life, but this population lags behind in the adoption of these devices. While theoretical frameworks have been introduced to explain and increase the adoption of this technology by...

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Detalles Bibliográficos
Autores principales: Kim, Sunyoung, Choudhury, Abhishek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7644379/
https://www.ncbi.nlm.nih.gov/pubmed/33090116
http://dx.doi.org/10.2196/18312
Descripción
Sumario:BACKGROUND: Activity tracking devices have significant potential in assisting older adults’ health care and quality of life, but this population lags behind in the adoption of these devices. While theoretical frameworks have been introduced to explain and increase the adoption of this technology by older adults, little effort has been made to validate the frameworks with people in other age groups. OBJECTIVE: The goal of this study was to validate the theoretical framework of technology acceptance by older adults that we previously proposed through a direct comparison of the attitudes to and experiences of activity trackers in older and younger users. METHODS: Semistructured interviews were conducted with 2 groups of 15 participants to investigate their experiences of using activity trackers. The recruitment criteria included age (between 18 years and 24 years for the younger participant group or 65 years and older for the older participant group) and prior experiences of using mobile devices or apps for activity tracking for 2 months and longer. RESULTS: Our findings showed that the phase of perceived ease of learning as a significant influencer of the acceptance of activity trackers existed only in the older participant group, but this phase never emerged in the younger participant group. In addition, this study confirmed that other phases exist in both age groups, but 2 distinct patterns emerged according to age groups: (1) the social influence construct influenced the older participants positively but the younger participants negatively and (2) older participants’ exploration in the system experiment phase was purpose-driven by particular needs or benefits but for younger participants, it was a phase to explore a new technology. CONCLUSIONS: This study confirms the validity of the proposed theoretical framework to account for the unique aspect of older adults’ technology adoption. This framework can provide theoretical guidelines when designing technology for older adults as well as when generating new investigations and experiments for older adults and technology use.