Evidence map›Paper›PMID 42208661›Full record

ArticleClinical medicine (London, England)2026

A FeAsibility items Checklist for assessing implementation characTeristics of patient-reported Outcome measures in Research, Regulation and Routine clinical care (FACTOR3): Development and evaluation.

Asad Bhatty, Chris Wilkinson, Visvesh Jeyalan, Ali Wahab, Jeremy Dwight, Marcin Ruciński, Edwin de Beurs, Melanie Calvert, Richard P Gale, Mike Horton and 9 more

Abstract read
In one paragraph

Article in Clinical medicine (London, England), 2026. 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. Cardiovascular disease: everybody's business.Clinical medicine (London, England) · 2026
    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

19 authors.

Asad BhattyLeeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK; Leeds Institute for Data Analytics, University of Leeds, Leeds, UK; Department of Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK. Electronic address: A.N.Bhatty@leeds.ac.uk.
Chris WilkinsonHull York Medical School, University of York, York, UK; Academic Cardiovascular Unit, South Tees NHS Foundation Trust, James Cook University Hospital, Middlesbrough, UK.
Visvesh JeyalanAcademic Cardiovascular Unit, South Tees NHS Foundation Trust, James Cook University Hospital, Middlesbrough, UK.
Ali WahabLeeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK; Leeds Institute for Data Analytics, University of Leeds, Leeds, UK; Department of Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Jeremy DwightEuropean Society of Cardiology Patient Forum, UK.
Marcin RucińskiEuropean Society of Cardiology Patient Forum, UK.
Edwin de BeursDepartment of Clinical Psychology, Leiden University, Netherlands and Arkin Mental Health Institute, Amsterdam, the Netherlands.
Melanie CalvertCentre for Patient-Reported Outcome Research (CPROR), Department of Applied Health Sciences, University of Birmingham, Birmingham, UK; National Institute of Health and Care Research (NIHR) Blood and Transplant Research Unit (BTRU) in Precision Cellular Therapeutics at the University of Birmingham, UK; NIHR Applied Research Collaboration (ARC) West Midlands, Birmingham, UK; Birmingham Health Partners Centre for Regulatory Science and Innovation, University of Birmingham, Birmingham, UK.
Richard P GaleHull York Medical School, University of York, York, UK; York and Scarborough Teaching Hospitals NHS Foundation Trust, York, UK.
Mike HortonPsychometric Laboratory for Health Sciences, University of Leeds, Leeds, UK.
Andrea MancaCentre for Health Economics, University of York, Heslington, York, UK.
Tom MelvinSchool of Medicine, Trinity College, University of Dublin, Dublin, Ireland.
Massimo Di MaioDepartment of Oncology, University of Turin, Division of Medical Oncology, Ordine Mauriziano Hospital, Turin, Italy.
Amar RanganAcademic Centre for Surgery, The James Cook University Hospital, Middlesbrough, UK.
Julie SandersFaculty of Nursing, Midwifery & Palliative Care, King's College London, London, UK.
Tonya WindersGlobal Allergy and Airways Patient Platform, Vienna, Austria.
Adam B SmithLeeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK; Leeds Institute for Data Analytics, University of Leeds, Leeds, UK.
Chris P GaleLeeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK; Leeds Institute for Data Analytics, University of Leeds, Leeds, UK; Department of Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
FACTOR3 Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

STUDY

objectivePatient-reported outcome measures (PROMs) provide valuable data to inform regulatory decision making, health technology assessment and routine clinical care. We aimed to develop a feasibility item checklist for PROMs and their selection, beyond their psychometric properties (FACTOR3).

methodsWe followed a five-stage method to select parameters for PROM evaluation. 1) A scoping literature review identified candidate items for consideration; 2) round 1 modified Delphi was used to select items for inclusion or exclusion, conducted by the design group (n = 14); 3) feedback on the checklist was provided by representatives from the European Medicines Agency and National Institute for Health and Care Excellence; 4) round 2 modified Delphi was used to finalise item selection, conducted by the clinical domains group (n = 21) and 5) evaluation of the feasibility item checklist using a selection of PROMS (EQ5D-5L, HeartQOL, the Oxford Hip Score, The EORTC Core Questionnaire QLQ-C30, Re-QOL-10 and NEI-VFQ-25) (Fig. 1).

resultsThe scoping review identified 13 items relating to the intrinsic feasibility of using PROMs which were considered in the modified Delphi. The final FACTOR3 checklist included eight unique candidate items: price; licensing, comprehensibility, duration, coverage, translations, electronic device compatibility; and minimal important difference. Of the six PROMS evaluated, the intraclass correlation coefficient was 0.81, suggesting good reliability.

conclusionsFACTOR3 is a feasibility item checklist to assess the implementation characteristics of PROMs in research, regulation and routine clinical care. It may be used in conjunction with existing psychometric evaluation and user guides for PROMS to facilitate their use in health care.

Indexed as

ChecklistPatient Reported Outcome MeasuresDelphi TechniqueFeasibility StudiesHumansPsychometricsSurveys and QuestionnairesFeasibilityImplementationPatient-reported outcome measuresPROMs

Identifiers

PMID42208661
PMCPMC13315201

What OpenQuestion holds

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LicenceCC BY
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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.