ArticlePLOS digital health2026
Awareness, trust, and expectations of AI for glaucoma care among Bulgarian ophthalmologists: Role of demographic factors.
Article in PLOS digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- Artificial intelligence in glaucoma diagnosis and management: Has its time come?Indian journal of ophthalmology · 2026Article
- Accuracy, readability, and bias of GPT-4o mini responses to oculoplastic patient questions.Frontiers in ophthalmology · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) holds promise for enhancing glaucoma screening and management, yet its adoption depends on clinician perceptions, particularly in resource-limited regions like Eastern Europe. This study explores awareness, trust, and expectations of AI in glaucoma care among Bulgarian ophthalmologists, examining the influence of demographic factors such as age, gender, and professional experience. A cross-sectional survey was conducted from March to May 2024 among 156 ophthalmologists and residents recruited via Bulgarian professional societies. The 25-question survey, informed by the Technology Acceptance Model and validated (content validity index = 0.85; Cronbach's α = 0.78), assessed awareness, trust (5- point Likert scale), and expectations. Data were analyzed using non-parametric tests (chi-square, Spearman correlation) and thematic analysis for qualitative responses. The study was approved by the Ethics Committee of Medical University of Varna (No141/14.03.2024), with informed consent obtained and adherence to the Declaration of Helsinki. Participants (73.1% female; median age 35 years, IQR 10) showed varying awareness, with less experienced clinicians (<5 years) more informed (χ2 = 17.89, p < 0.001). Trust was low (7.5% fully trusted AI diagnosis; 5.7% for treatment), with gender differences (males more distrustful in diagnosis, p = 0.009). Younger respondents were more optimistic about AI's impact (ρ = 0.268, p < 0.001). Qualitative themes highlighted diagnostic utility (95% mentions) and concerns like training deficiencies (45%). Bulgarian ophthalmologists exhibit cautious optimism toward AI in glaucoma care, shaped by demographics, underscoring the need for targeted training to build trust. These findings inform regional AI implementation strategies, aligning with ethical priorities for equitable digital health adoption.
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Registered trials
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