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Attitudes and Knowledge Levels of Optometry Students and Educators Towards Artificial Intelligence in Optometric Practice: An Online Cross-Sectional Survey

Fiona Buckmaster, Diane van Staden, Lauren Coetzee

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: Artificial intelligence (AI) is poised to revolutionise all aspects of eye care practice in the coming decades. However, not much is known about optometry students’ and educators’ attitudes or knowledge levels about AI in optometry.
Methods: A cross-sectional online survey was distributed via Qualtrics to optometry students and educators at all optometry universities in the UK through university optometry student societies, word of mouth, social media and the professional networks of the researchers. The survey explored knowledge levels and training experience in AI, competence levels using AI in a clinical scenario, attitudes towards the utilisation of AI in optometry and AI topics to potentially include in an optometry curriculum. Results: A total of 254 responses (213 students and 41 educators) were received from 14 out of 15 optometry universities in the UK. Notably, 96% of students had not received any training in AI, and 76% of students reported little or no knowledge about AI applications in optometry. Educators were more likely to have undergone AI training (34%) and had higher knowledge levels than students, with 59% of educators reporting at least some AI knowledge. Across all respondents, those who had undergone AI training had more positive attitudes towards AI in optometry. Educators felt strongly that teaching about AI should be included in the optometry curriculum. Potential AI topics for inclusion in a curriculum were explored. A broad range of topics were identified as important to include; however, ‘how AI tools are developed, trained and validated’ was seen as the least important to teach to optometry students. Conclusion: Optometry students’ current self-reported knowledge levels about AI applications in optometry are very limited. This research provides an early exploration of the considerations for creating future AI educational initiatives in optometry programmes. However, further research in this area is still required.
Original languageEnglish
Number of pages10
JournalOphthalmic and Physiological Optics
Early online date6 Mar 2026
DOIs
Publication statusE-pub ahead of print - 6 Mar 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 4 - Quality Education
    SDG 4 Quality Education

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