Table 3.

Human-related factors related to acceptance (N=77) of medical AI^a applications (14/32, 43.8%, studies).

Factor category and factors from the rapid review			Umbrella factors used in the survey
AI professionals
	AI company/provider (n=1, 7.1%); brand impact (n=1, 7.1%)	Type of institution/organization of AI professionals (eg, university, technology company, commercial organization)
	Perceived usefulness (n=3, 21.4%); better medical services/ understanding of disease (n=3, 21.4%); improve the quality of people’s lives (n=2, 14.3%); medical costs (n=2, 14.3%); AI role (eg, saving patients’ time; n=1, 7.1%); miniaturization of hardware (n=1, 7.1%)	Purpose to innovate with a specific AI application in medicine (eg, financial vs societal)
Health care professionals
	Knowledge and understanding of AI (n=1, 7.1%)	Knowledge of AI applications in medicine (eg, by means of training and education)
	Behavioral intention to use (n=2, 14.3%); effort expectancy (n=2, 14.3%); perceived ease of use (n=2, 14.3%); perceived usefulness (n=2, 14.3%); intrinsic motivation (n=1, 7.1%); interest in AI (n=1, 7.1%); professional identity (n=1, 7.1%); concerns about benefit to patient care (n=1, 7.1%); general impression of AI (n=1, 7.1%)	Attitude toward AI application usage in medicine (eg, agreeableness, openness, conscientiousness, engagement)
Patients informed about AI application usage in the hospital
	Knowledge/education about AI (n=1, 7.1%); awareness of AI (n=1, 7.1%)	General knowledge of AI applications in medicine
	Behavioral intention to use (n=2, 14.3%); general impression (n=1, 7.1%); Interest in topic (n=1, 7.1%)	Attitude toward AI application usage in medicine (eg, agreeableness, openness, conscientiousness)
	Age (n=1, 7.1%)	Age
All parties
	Expectations of others (n=2, 14.3%)	Transparency between all involved parties (AI professionals, healthcarehealth care professionals, patients)

^aAI: artificial intelligence.