Evidence map›Paper›PMID 40624704›Full record

ArticleResearch involvement and engagement2025

"How can we involve Patients?" - Students' perspectives on embedding PPIE into a doctoral training centre for AI in medical diagnosis and care.

Aron Syversen, Oliver Umney, Lewis Howell, Jack Breen, Emma Briggs, Zoe Hancox, Sobia Khan, Oliver Mills, Victoria Moglia, Mary Paterson and 1 more

Abstract readLetter
In one paragraph

Article in Research involvement and engagement, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Aron Syversen *School of Computer Science, University of Leeds, Leeds, UK. scabs@leeds.ac.uk.
Oliver Umney *School of Computer Science, University of Leeds, Leeds, UK.
Lewis Howell *School of Computer Science, University of Leeds, Leeds, UK.
Jack BreenSchool of Computer Science, University of Leeds, Leeds, UK.
Emma BriggsSchool of Computer Science, University of Leeds, Leeds, UK.
Zoe HancoxSchool of Computer Science, University of Leeds, Leeds, UK.
Sobia KhanSchool of Computer Science, University of Leeds, Leeds, UK.
Oliver MillsSchool of Computer Science, University of Leeds, Leeds, UK.
Victoria MogliaSchool of Computer Science, University of Leeds, Leeds, UK.
Mary PatersonSchool of Computer Science, University of Leeds, Leeds, UK.
Richard StephensCancer Research Advocates Forum UK, London, UK.

Funding

Engineering and Physical Sciences Research Council EP/S024336/1
6 · The paper itself

Abstract

Artificial intelligence (AI) in healthcare is a rapidly developing research field, but there is limited evidence that patients and public are widely engaged or involved with its progression. Alongside this, there is a growing recognition of the importance of incorporating Patient and Public Involvement and Engagement (PPIE) earlier into researcher training. Doctoral training programmes (centres) may provide the perfect environment to address both issues. This paper describes and evaluates Patient and Public Involvement and Engagement (PPIE) activities within the Centre for Doctoral Training (CDT) in Artificial Intelligence for Medical Diagnosis and Care (“AI-Medical”), at the University of Leeds in the United Kingdom. Authored primarily by PhD candidates from the AI-Medical CDT, it gives an overview of the PPIE activities conducted within the CDT, including accounts of first-hand experiences, supported by quotes and reflections from students. It also shares key learning outcomes and makes actionable recommendations for integrating PPIE into future PhD programmes and individual research projects. These insights highlight both the successes and challenges of embedding PPIE in healthcare-focused AI research projects in a doctoral training centre.

Indexed as

Artificial intelligenceDoctoral training programmesHealthcareJunior researchersPatient and public involvement and engagementPhD students

Identifiers

PMID40624704
PMCPMC12232768

What Socratic 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 Socratic graph.