Social Influence on Health IT Adoption Patterns of the Elderly: An Institutional Theory Based Use Behavior Approach

Bozan, Karoly; Davey, Bill; Parker, Kevin R.

doi:10.1016/j.procs.2015.08.378

Cited by 29 publications

(15 citation statements)

References 41 publications

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“…For H7, the standardized path coefficient between health improvement expectancy and continuous use intention was .337, and statistically significant at the .001 level, also supporting H7. These results are similar to that shown by previous studies, the higher the expected performance for health improvement through the device the higher the intention to use continuously (e.g., Venkatesh et al 2003 ; 2012 ; Bonzan et al 2015 ; Cimperman et al 2016 ). If inpatients had a positive health improvement experience with healthcare wearable devices/apps, they tend to share their experiences and recommend others to use devices/apps.…”

Section: Structural Equation Modeling and Hypothesis Testingsupporting

confidence: 91%

“…Typically, individuals expect effective health management with the support of healthcare applications. Health improvement expectancy refers to the degree to which users believe that the application of a new technology will result in positive health improvement (Venkatesh et al 2003 ; Bozan et al 2015 ). Therefore, health improvement expectancy can be a predictor of continuous use intention (Venkatesh et al 2003 ; Bozan et al 2015 ).…”

Section: Research Model and Hypotheses Developmentmentioning

confidence: 99%

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Healthcare wearable devices: an analysis of key factors for continuous use intention

2020

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This study empirically examined the effects of internal and external factors on actual use behavior, health improvement expectancy, and continuous use intention of healthcare wearable devices. The study proposed a research model with its associated hypotheses that were tested using structural equation modeling. We also performed a comparative analysis of the two sample groups (medical personnel and general public), based on data collected from 288 healthcare wearable devices/apps users. The findings of the study indicated that internal and external factors have positive effects on actual use behavior, and health improvement expectancy and continuous use intention of healthcare wearable devices can be promoted through actual use behavior. The comparative analysis of the two groups showed that medical personnel had higher relationships among the study factors than general public. The study results shed theoretical and practical implications regarding how healthcare wearable devices or apps can be effectively used for disease prevention and health management for the users.

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Section: Structural Equation Modeling and Hypothesis Testingsupporting

confidence: 91%

Section: Research Model and Hypotheses Developmentmentioning

confidence: 99%

Healthcare wearable devices: an analysis of key factors for continuous use intention

2020

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“…They found that some were 'hybrid digital practices' where new practices were merging with established practices. Bozan et al [21] found that older adults adoption and use of digital health technologies was in part influenced by their healthcare providers' advice, but was also greatly influenced by people in their family / social networks that they respected and trusted. Further, mobile devices in the delivery of digital services has the potential to provide personalized services [12].…”

Section: Literature Review: Meaningful Access?mentioning

confidence: 99%

“…Our study thus found that their normal practice would be to seek help from intermediaries such as family and friends. However, seeking help also extends to carers, neighbors, and NGO & government staff to routinely access the internet to find out relevant information [21]. Gabriel, a support worker told us he often searched for information on services and activities for his clients.…”

Section: Extending the Usermentioning

confidence: 99%

Ensembles of Practice: Older Adults, Technology, and Loneliness & Social Isolation in Rural Settings

Hayes

Introna

Smith³

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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This paper considers whether, and if so how, ICT might play a role in addressing loneliness and social isolation for older adults in rural areas. We base our paper on a longitudinal co-creation study that has been undertaken in a rural location in the North of England. We adopt a practice perspective to examine the everyday practices of older adults as they sought out opportunities to address their desire for social connectedness and explore how technology might support them in those practices. Specifically, we argue that we need to identify the linking practices that enable participation in social connectedness through ICT. Based on this, we develop a model to guide future practice based studies and interventions.

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“…There is an increasing interest in a multimedia communication delivery [8][9] for the elderly such as medreminder application reminded people to take medicines, and call relatives or medical personnel in case of emergency through an interactive television [10]. The Senior Channel system allowed older users to interact with TV and multimedia contents, which in turn helped to improve their social inclusion and participation [11].…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of Factors Affecting Multimedia Delivery for Elderly People

Suta¹,

Limdumrongnukoon²,

Chalardkitsirikul³

et al. 2018

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This study aims to apply appropriate information technology services for elderly people in order to fill the communication gap between the elderly, family members and friends by using a multimedia delivery platform. The aim is to improve the quality of life of the elderly people who live alone. It is intended to enhance the lives of elderly people to stay connected with family members, and friends by sending multimedia content including text, audio, image and video. We analyze the factors affecting the elderly person's intention to use the platform by using Unified Theory of Acceptance and Use of Technology (UTAUT) model. The model evaluates the effectiveness of the multimedia delivery platform over the six key UTAUT constructs, namely, Performance Expectancy, Effort Expectancy, Social Influence, Facilitation Conditions, Perceived Security, and Experience and Voluntariness to Behavioral Intention. The analysis is twofold: to determine the factors affecting the intention of the elderly people in using the multimedia delivery platform, and to investigate how to reduce the communication gap between the elderly, family members and friends.

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Social Influence on Health IT Adoption Patterns of the Elderly: An Institutional Theory Based Use Behavior Approach

Cited by 29 publications

References 41 publications

Healthcare wearable devices: an analysis of key factors for continuous use intention

Healthcare wearable devices: an analysis of key factors for continuous use intention

Ensembles of Practice: Older Adults, Technology, and Loneliness & Social Isolation in Rural Settings

Analysis of Factors Affecting Multimedia Delivery for Elderly People

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