JOURNAL ARTICLE
The role of biometric identification on the quality of life of older adults.
Published In: International Journal of Technology Management & Sustainable Development, 2023, v. 22, n. 3. P. 275 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Fenuku, Samson Dodzi; Akpaku, Ernest; Brown-Acquaye, William Leslie; Ofoeda, Joshua; Kutiame, Solomon 3 of 3
Abstract
This article investigates the impact of biometric identification technology, specifically Ghana’s national biometric identity system known as the Ghana Card, on the quality of life of older adults in a developing country context. Using a mixed-methods approach grounded in flow theory, the study identifies four key benefits for older adults: improved healthcare access, enhanced information access, social inclusion, and socio-economic development. Quantitative analysis employing partial least squares-structural equation modelling (PLS-SEM) and artificial neural networks (ANN) reveals that improved healthcare access, information access, and socio-economic development significantly enhance older adults’ quality of life, while social inclusion, although positive, does not have a statistically significant effect. These findings provide insights for policymakers and practitioners aiming to leverage biometric systems to support the well-being of older populations, emphasizing the prioritization of healthcare, information, and economic factors over social inclusion in this context.
Additional Information
- Source:International Journal of Technology Management & Sustainable Development. 2023/09, Vol. 22, Issue 3, p275
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2023
- ISSN:1474-2748
- DOI:10.1386/tmsd_00078_1
- Accession Number:174972566
- Copyright Statement:Copyright of International Journal of Technology Management & Sustainable Development is the property of Intellect Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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