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Intersecting Minds and Machines: A Review of Behavioral Intentions Towards Health Intelligence Systems
Abstract
The integration of technology in the medical sector, particularly for data acquisition and analysis via the internet of health things (IoHT), offers significant potential for enhancing community health management by monitoring individual lifestyle patterns. A systematic literature review focusing on articles published between 2019 and 2021 explored the behavioral intention toward using IoHT-based healthcare systems. Analyzing 20 selected articles revealed a preference for theories such as the technology acceptance model (TAM), the unified theory of acceptance and use of technology (UTAUT), and the theory of planned behaviour (TPB) to facilitate behavioral change. Key factors influencing behavioral intention toward these systems include performance expectancy, perceived usefulness, effort expectancy, social influence, and resistance to change. The findings highlight the importance of user-centric design in developing IoHT-based healthcare systems to effectively meet community health needs, emphasizing that healthcare solutions should be tailored to individual health behaviors and preferences.
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