e.g. mhealth
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The Technology Acceptance Model (TAM) provides such a framework for understanding the adoption of emerging health-focused technologies. TAM proposes that perceived usefulness (the belief that using a given technology can improve the ability to perform a task) and perceived ease of use (the belief that the technology is easy to use) determine attitudes toward technology adoption [15]. While these 2 beliefs can be measured independently, TAM posits that perceived ease of use influences perceived usefulness.
J Med Internet Res 2025;27:e66550
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We investigated the staff perspective as their perceptions play a key role in the adoption of social robots [16,17]. Our research questions were as follows:
What value does sustained use of social robot Ivy create for people with intellectual disabilities and health care professionals?
What facilitators and barriers influence the continuation versus abandonment of use of social robot Ivy during the execution and continuation phases of implementation?
J Med Internet Res 2025;27:e74168
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Barrier-related themes to physicians’ (n=36) adoption of telemedicine.
Enabler-related themes for physicians’ (n=36) adoption of telemedicine.
Available resources and the environment influence a physician’s inclination to perform [46]. Environmental context and resources have emerged as key barriers to using telemedicine.
J Med Internet Res 2025;27:e73412
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Researching technology adoption on an individual level is a core focus of IS research [14,15]. Adoption primarily concerns the individual user’s acceptance of technology as well as the adoption decision [15,16]. To explain technology adoption, the most well-known IS theories from an individual perspective are the Technology Adoption Model (TAM) [21] and the Unified Theory of Acceptance and Use of Technology (UTAUT) [14].
J Med Internet Res 2025;27:e63668
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Although many studies examine the functionality, accessibility, and usability of PHRs, as well as their barriers and benefits [5,9,10,12], fewer studies focus on PHR adoption by patients and health care professionals [14], which is essential to ensure PHR usage. Rouleau et al [15] mapped the theories, models, and frameworks in a scoping review that addressed the adoption, implementation, and embedment of e Health.
J Med Internet Res 2025;27:e71915
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It is equally crucial to explore the factors associated with the attitudes and perceptions of medical staff toward the adoption of AI in health care. Previous studies have demonstrated that variations in views on AI can be ascribed to a range of factors, including age, sex, educational level, and experience related to AI [15].
J Med Internet Res 2025;27:e75343
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Given their central role in patient care, nurses are key users of digital nursing technologies (DNTs) and play a crucial role in their adoption and effective implementation in nursing care settings [6].
J Med Internet Res 2025;27:e64616
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In the context of e-learning, implementation outcomes include the acceptability, adoption, appropriateness, feasibility, fidelity, and sustainability of e-learning resources in teaching and learning [8]. When e-learning objects are released as open content, reach and discoverability become important.
To date, several models have been used to evaluate the effectiveness and implementation of e-learning resources.
JMIR Med Educ 2025;11:e63882
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