The acceptance of ophthalmic artificial intelligence for eye diseases: a literature review and qualitative analysis

Area of Science:

• Ophthalmology
• Medical Artificial Intelligence
• Health Technology Acceptance

Background:

• Investigating end-user awareness, acceptance, and concerns regarding ophthalmic artificial intelligence (AI) is crucial for its successful integration.
• Existing research often lacks depth in exploring social influences and demographic factors affecting AI adoption in eye care.

Purpose of the Study:

• To review and analyze the literature on the acceptance of ophthalmic AI.
• To evaluate the quality of eligible studies using a psychological model, focusing on key acceptance factors and user demographics.

Main Methods:

• Conducted a literature review to identify studies on ophthalmic AI acceptance.
• Qualitatively analyzed sixteen studies using a psychological model, assessing primary factors (performance expectancy, effort expectancy, social influence, facilitating conditions) and regulating factors (gender, age, experiences, voluntariness).

Main Results:

• Most studies focused on performance and effort expectancies, with limited exploration of social influence, facilitating conditions, and demographic impacts.
• Overall acceptance of ophthalmic AI is high across various groups, including patients, ophthalmologists, and the general public.

Conclusions:

• More robust qualitative studies with larger, diverse, and multidisciplinary stakeholder samples are required.
• Addressing concerns like cost, privacy, safety, trustworthiness, and regulation is vital.
• Evidence-based medicine, high-quality trials, patient education, clinician training, and privacy-preserving technologies are essential for advancing ophthalmic AI acceptance.