| Title: |
Attitudes of optometrists towards artificial intelligence for the diagnosis of retinal disease: A cross-sectional mail-out survey |
| Authors: |
Ho, S; Doig, GS; Ly, A |
| Source: |
urn:ISSN:0275-5408 ; urn:ISSN:1475-1313 ; Ophthalmic and Physiological Optics, 42, 6, 1170-1179 |
| Publisher Information: |
Springer Nature |
| Publication Year: |
2022 |
| Collection: |
UNSW Sydney (The University of New South Wales): UNSWorks |
| Subject Terms: |
32 Biomedical and Clinical Sciences; 3212 Ophthalmology and Optometry; Bioengineering; Machine Learning and Artificial Intelligence; Clinical Research; Eye Disease and Disorders of Vision; Neurosciences; 3 Good Health and Well Being; Adult; Artificial Intelligence; Cross-Sectional Studies; Female; Humans; Male; Middle Aged; Optometrists; Optometry; Postal Service; Retinal Diseases; clinical decision support; machine learning; survey; anzsrc-for: 32 Biomedical and Clinical Sciences; anzsrc-for: 3212 Ophthalmology and Optometry; anzsrc-for: 1103 Clinical Sciences; anzsrc-for: 1113 Opthalmology and Optometry; anzsrc-for: 1199 Other Medical and Health Sciences |
| Description: |
Purpose: Artificial intelligence (AI)-based systems have demonstrated great potential in improving the diagnostic accuracy of retinal disease but are yet to achieve widespread acceptance in routine clinical practice. Clinician attitudes are known to influence implementation. Therefore, this study aimed to identify optometrists' attitudes towards the use of AI to assist in diagnosing retinal disease. Methods: A paper-based survey was designed to assess general attitudes towards AI in diagnosing retinal disease and motivators/barriers for future use. Two clinical scenarios for using AI were evaluated: (1) at the point of care to obtain a diagnostic recommendation, versus (2) after the consultation to provide a second opinion. Relationships between participant characteristics and attitudes towards AI were explored. The survey was mailed to 252 randomly selected practising optometrists across Australia, with repeat mail-outs to non-respondents. Results: The response rate was 53% (133/252). Respondents' mean (SD) age was 42.7 (13.3) years, and 44.4% (59/133) identified as female, whilst 1.5% (2/133) identified as gender diverse. The mean number of years practising in primary eye care was 18.8 (13.2) years with 64.7% (86/133) working in an independently owned practice. On average, responding optometrists reported positive attitudes (mean score 4.0 out of 5, SD 0.8) towards using AI as a tool to aid the diagnosis of retinal disease, and would be more likely to use AI if it is proven to increase patient access to healthcare (mean score 4.4 out of 5, SD 0.6). Furthermore, optometrists expressed a statistically significant preference for using AI after the consultation to provide a second opinion rather than during the consultation, at the point-of-care (+0.12, p = 0.01). Conclusions: Optometrists have positive attitudes towards the future use of AI as an aid to diagnose retinal disease. Understanding clinician attitudes and preferences for using AI may help maximise its clinical potential and ensure its successful ... |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
unknown |
| Relation: |
https://hdl.handle.net/1959.4/unsworks_83539; https://doi.org/10.1111/opo.13034 |
| DOI: |
10.1111/opo.13034 |
| Availability: |
https://hdl.handle.net/1959.4/unsworks_83539; https://unsworks.unsw.edu.au/bitstreams/5cbfcef3-547c-4b24-9561-5bf1e331ff8f/download; https://doi.org/10.1111/opo.13034 |
| Rights: |
open access ; https://purl.org/coar/access_right/c_abf2 ; CC BY-NC ; https://creativecommons.org/licenses/by-nc/4.0/ ; free_to_read |
| Accession Number: |
edsbas.B077A2BF |
| Database: |
BASE |