Patients' Perception of Robot-Driven Technology in the Management of Retinal Diseases.

Abstract

There is increasing application of robots and other artificial intelligence-driven technologies in the management of retinal disease. These technologies have the potential to meet increasing demands for retinal diseases. However, there is currently a lack of understanding of patients' attitudes towards use of robots in ophthalmology. This study investigates patients' attitudes towards robot-led management of retinal disease. Paper questionnaires were distributed to 177 patients attending intravitreal treatment (IVT) at the Princess Alexandra Eye Pavilion between 1October 2022 and 31January 2023. The questionnaire collected information on age, sex, diagnosis and postcode. In the questionnaire, patients responded to questions about their attitudes towards robot-led diagnosis, treatment decisions and IVT injections. Responses were collected using a 5-category Likert scale which was analysed using ordinal logistic regression with adjustments for age, sex and deprivation status. Those from affluent socioeconomic backgrounds were significantly (p < 0.001) more accepting of robots diagnosing and deciding on treatment, although the total number of patients who were accepting was only 26 (14.7%). Furthermore, there was an increased proportion of patients who would accept robots if the robot made fewer mistakes than doctors, if the robot reduced waiting or appointment time and if the robot was able to communicate well and have empathy; the same association with socioeconomic background remains (p < 0.001). Lastly, 116 patients (65.5%) would not be happy if IVT injections were performed by a robot; this was more likely the case if the patient was female (p = 0.04) or from a more deprived socioeconomic background (p < 0.001). Attitudes towards robot involvement in diagnosis and management of retinal disease are significantly associated with socioeconomic backgrounds and sex. Additional studies are required to further investigate these determinants of robot receptiveness to ensure acceptance and compliance with treatment with these new technologies.