Understanding older adults' acceptance of Chatbots in healthcare delivery: an extended UTAUT model
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View abstract on PubMed
Summary
This summary is machine-generated.Older adults’ acceptance of healthcare chatbots is influenced by performance, effort, and social factors. Facilitating conditions, self-actualization, and physical health impact actual use, highlighting key areas for technology design and implementation.
Area Of Science
- Gerontology
- Human-Computer Interaction
- Health Informatics
Background
- Chatbots are increasingly used to support older adults in health and wellness.
- Understanding factors influencing their acceptance in healthcare is crucial.
Purpose Of The Study
- To investigate factors affecting older adults' acceptance and use of chatbots in healthcare.
- To extend the Unified Theory of Acceptance and Use of Technology (UTAUT) model with aging-specific factors.
Main Methods
- An extended UTAUT model was proposed, incorporating perceived physical condition, self-actualization needs, and technology anxiety.
- Partial Least Squares (PLS) analysis was performed on data from 428 Chinese adults aged 60 and above.
Main Results
- Performance expectancy, effort expectancy, and social influence significantly predicted behavioral intention to use chatbots.
- Facilitating conditions, self-actualization needs, and perceived physical condition significantly predicted actual chatbot use.
- Technology anxiety did not significantly affect chatbot use; experience moderated the influence of effort expectancy and social influence.
Conclusions
- Healthcare providers, designers, and policymakers should focus on facilitating conditions, self-actualization, and perceived physical health for effective chatbot adoption by older adults.
- Effort expectancy and social influence have a stronger impact on behavioral intention for less experienced older adults.
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