Evidence map›Paper›PMID 37369908›Full record

ArticleOphthalmology and therapy2023

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

Kah Long Aw, Sirindhra Suepiantham, Aryelly Rodriguez, Alison Bruce, Shyamanga Borooah, Peter Cackett

Open access · goldAbstract read
In one paragraph

Article in Ophthalmology and therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 34% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 2 countries.

Kah Long AwPrincess Alexandra Eye Pavilion, Edinburgh, Scotland. awkahlong@gmail.com.ORCID http://orcid.org/0000-0003-4405-576X
Sirindhra SuepianthamUniversity of Edinburgh, Edinburgh, Scotland.
Aryelly RodriguezUniversity of Edinburgh, Edinburgh, Scotland.
Alison BrucePrincess Alexandra Eye Pavilion, Edinburgh, Scotland.
Shyamanga BorooahShiley Eye Institute, San Diego, California, USA.
Peter CackettPrincess Alexandra Eye Pavilion, Edinburgh, Scotland.
Princess Alexandra Eye Pavilion · GBUniversity of Edinburgh · GBSmith-Kettlewell Eye Research Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThere 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.

methodsPaper questionnaires were distributed to 177 patients attending intravitreal treatment (IVT) at the Princess Alexandra Eye Pavilion between 1 October 2022 and 31 January 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.

resultsThose 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).

conclusionAttitudes 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.

Indexed as

Artificial intelligenceIntravitreal injectionRobots in ophthalmology

Identifiers

PMID37369908
PMCPMC10442043
OpenAlexW4382318574

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.