Evidence map›Paper›PMID 39962625›Full record

ArticleBMC rheumatology2025

Preparing to deliver a stepped wedge cluster-randomised trial to test the effectiveness of daily symptom tracking integrated into electronic health records for managing rheumatoid arthritis: a mixed-methods feasibility trial.

Katie L Druce, Yumna Masood, Helen Chadwick, Sarah Skyrme, Deb Griffiths-Jones, Ramiro D Bravo Santisteban, Peter Bower, Jill Firth, Charlotte A Sharp, Christopher J Armitage and 6 more

Abstract read
In one paragraph

Article in BMC rheumatology, 2025. 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
–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

2 citing papers in PubMed.

  1. Article
  2. 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

16 authors.

Katie L Druce *Centre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Yumna Masood *Centre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Helen ChadwickCentre for Health Informatics, Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Vaughan House, Portsmouth Street, Manchester, M13 9GB, UK.
Sarah SkyrmeCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Deb Griffiths-JonesCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Ramiro D Bravo SantistebanCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Peter BowerNIHR ARC Greater Manchester, Centre for Primary Care and Health Services Research, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Jill FirthPennine MSK Partnership, Integrated Care Centre, Oldham, UK.
Charlotte A SharpDivision of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Christopher J ArmitageManchester Centre for Health Psychology, Division of Psychology and Mental Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Dawn DowdingDivision of Nursing, Midwifery and Social Work, School of Health Sciences, Faculty of Biomedicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
John McBethCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Caroline SandersDivision of Population Health, Heath Services Research and Primary Care, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
William G Dixon *Centre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Sabine N van der Veer *Centre for Health Informatics, Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Vaughan House, Portsmouth Street, Manchester, M13 9GB, UK. sabine.vanderveer@manchester.ac.uk.
REMORA team

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe sought to assess the feasibility of a stepped-wedge cluster-randomised trial testing the effectiveness of a complex mHealth intervention called REMORA: a co-designed smartphone app enabling daily, weekly and monthly symptom tracking integrated into electronic health records for people with rheumatoid arthritis (RA).

methodsWe conducted a mixed-methods feasibility trial using a convergent approach with some explanatory sequential elements. Patients were eligible to take part if they were older than ≥18 years of age, had (suspected) RA or undifferentiated inflammatory arthritis, and consented to take part from two outpatient departments. We analysed quantitative app and electronic health record data descriptively. We analysed qualitative data from interviews and clinic observations thematically. We assessed four feasibility domains: recruitment and consent (target: 15 patients per site), intervention uptake (≥70% of recruited participants completed on-boarding, i.e., registered with the app and submitted at least one symptom report), intervention adherence (>50% daily symptom reports provided), and measuring disease activity as the primary outcome (scores available for ≥80% of people with a follow-up clinic visit). Due to time constraints, we only recruited patients to the intervention group, leaving us unable to test the logistics of randomising sites in accordance with the trial's cluster stepped wedge design.

resultsOf 130 people screened, 52 consented. Of those, 32 (62%) completed on-boarding. On-boarded participants provided symptom data on 2384/3771 (63%) of possible days. Among the 48 people who had ≥1 follow-up appointment, at least one disease activity scored was obtained for 46 (96%) of them. Factors related to intervention uptake formed the biggest threat to trial feasibility, including lack of clarity of communication and guidance, access to technology, and personal challenges (e.g., being busy or unwell).

conclusionWe found that delivering a trial to test the effectiveness of integrated symptom tracking in rheumatology outpatient settings was feasible. The future REMORA trial will contribute to the much-needed evidence base for the impact of integrated symptom tracking on care delivery and patient outcomes, including decision-making, patient experience, disease activity, and symptom burden.

trial registrationThis feasibility trial was registered at https://www.isrctn.com/ on 23-Jan-2023 (ISRCTN21226438).

Indexed as

Feasibility studiesmHealthPatient-generated health dataRheumatoid arthritisSmartphone applicationsSymptoms

Identifiers

PMID39962625
PMCPMC11834673

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.