Evidence map›Paper›PMID 37968006›Full record

ArticleBMJ open2023

What are the perceptions and concerns of people living with diabetes and National Health Service staff around the potential implementation of AI-assisted screening for diabetic eye disease? Development and validation of a survey for use in a secondary care screening setting.

Kathryn Willis, Umar A R Chaudhry, Lakshmi Chandrasekaran, Charlotte Wahlich, Abraham Olvera-Barrios, Ryan Chambers, Louis Bolter, John Anderson, S A Barman, Jiri Fajtl and 7 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Cohort Profile: The North East London Diabetes Study (NELDS).International journal of epidemiology · 2026
    Article
  2. Review
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

17 authors at 4 institutions in 1 country.

Kathryn WillisPopulation Health Research Institute, St George's University of London, London, UK.ORCID 0009-0006-2847-3573
Umar A R ChaudhryPopulation Health Research Institute, St George's University of London, London, UK.
Lakshmi ChandrasekaranPopulation Health Research Institute, St George's University of London, London, UK.
Charlotte WahlichPopulation Health Research Institute, St George's University of London, London, UK.
Abraham Olvera-BarriosNIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust, London, UK.
Ryan ChambersDiabetes and Endocrinolgy, Homerton Healthcare NHS Foundation Trust, London, UK.
Louis BolterDiabetes and Endocrinolgy, Homerton Healthcare NHS Foundation Trust, London, UK.
John AndersonDiabetes and Endocrinolgy, Homerton Healthcare NHS Foundation Trust, London, UK.ORCID 0000-0002-2355-9742
S A BarmanSchool of Computer Science and Mathematics, Kingston University London, London, UK.
Jiri FajtlSchool of Computer Science and Mathematics, Kingston University London, London, UK.
Roshan WelikalaSchool of Computer Science and Mathematics, Kingston University London, London, UK.
Catherine EganNIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust, London, UK.
Adnan TufailNIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust, London, UK.
Christopher G OwenPopulation Health Research Institute, St George's University of London, London, UK.
Alicja RudnickaPopulation Health Research Institute, St George's University of London, London, UK arudnick@sgul.ac.uk.
ARIAS Research Group
Study Advisory Group members
St George's, University of London · GBHomerton University Hospital NHS Foundation Trust · GBKingston University · GBMoorfields Eye Hospital NHS Foundation Trust · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

introductionThe English National Health Service (NHS) Diabetic Eye Screening Programme (DESP) performs around 2.3 million eye screening appointments annually, generating approximately 13 million retinal images that are graded by humans for the presence or severity of diabetic retinopathy. Previous research has shown that automated retinal image analysis systems, including artificial intelligence (AI), can identify images with no disease from those with diabetic retinopathy as safely and effectively as human graders, and could significantly reduce the workload for human graders. Some algorithms can also determine the level of severity of the retinopathy with similar performance to humans. There is a need to examine perceptions and concerns surrounding AI-assisted eye-screening among people living with diabetes and NHS staff, if AI was to be introduced into the DESP, to identify factors that may influence acceptance of this technology. METHODS AND ANALYSIS: People living with diabetes and staff from the North East London (NEL) NHS DESP were invited to participate in two respective focus groups to codesign two online surveys exploring their perceptions and concerns around the potential introduction of AI-assisted screening.Focus group participants were representative of the local population in terms of ages and ethnicity. Participants' feedback was taken into consideration to update surveys which were circulated for further feedback. Surveys will be piloted at the NEL DESP and followed by semistructured interviews to assess accessibility, usability and to validate the surveys.Validated surveys will be distributed by other NHS DESP sites, and also via patient groups on social media, relevant charities and the British Association of Retinal Screeners. Post-survey evaluative interviews will be undertaken among those who consent to participate in further research. ETHICS AND DISSEMINATION: Ethical approval has been obtained by the NHS Research Ethics Committee (IRAS ID: 316631). Survey results will be shared and discussed with focus groups to facilitate preparation of findings for publication and to inform codesign of outreach activities to address concerns and perceptions identified.

Indexed as

Diabetes MellitusDiabetic RetinopathyArtificial IntelligenceHumansMass ScreeningSecondary Health CareState MedicineDIABETES & ENDOCRINOLOGYDiabetic retinopathyDiagnostic ImagingPUBLIC HEALTH

Identifiers

PMID37968006
PMCPMC10660949
OpenAlexW4388693697

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.