Experience first: investigating smart wearable technology acceptance among elderly citizens with Smart Wearables Technology Acceptance Model (SWTAM)
As the population ages, there is a greater demand for health care services and support, especially through smart wearable technology to monitor the elderly’s health, at the same time resolving the psychological, psychosocial, and mobility inadequacies. This study looked at the aspects that may have...
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| Format: | Thesis |
| Language: | en |
| Published: |
2024
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| Subjects: | |
| Online Access: | http://eprints.sunway.edu.my/3218/1/Final%20Hardbound%20Thesis.pdf http://eprints.sunway.edu.my/3218/ |
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| Summary: | As the population ages, there is a greater demand for health care services and support, especially through smart wearable technology to monitor the elderly’s health, at the same time resolving the psychological, psychosocial, and mobility inadequacies. This study looked at the aspects that may have helped older people embrace smart wearable technologies to expedite and promote the use of smart wearable technology. After consulting the earlier related studies, a structural equation modeling-based model of smart wearables acceptance for elderly citizens will be developed. This model will include an extra construct—individual context—by including elements such as anxiety and self-efficacy. This study mainly focused on developing countries, which as Malaysia in this case, as the available studies on the acceptance of smart wearable technology are still lacking in our country. The population of this study is mainly older adults with basic knowledge of Smart Wearable Technology or users of the technology. In the data collection phase, 300 datasets were collected, and 266 examples were used for model validation after data filtering in the data processing phase. The validity and reliability of the constructs in the model were assessed through the method of partial least squares. In the assumption testing, normality and common method variance were applied. For further assessment, convergent validity, discriminant validity, internal consistency reliability, and indicator reliability (outer loadings) were all used to evaluate the measuring model. Difficulties with collinearity, path coefficients, confidence intervals, and effect size (f2) were also evaluated for the structural model’s validation. The findings of this study identified a few factors that significantly impact older people's desire to employ smart wearable technology in both positive and negative ways, where external factors seem to be more having a significant effect on perceived usefulness when compared with perceived ease of use. Furthermore, perceived values are better factors to be explored in influencing the decisions of the elderly. |
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