Evidence map›Paper›PMID 35488193›Full record

ReviewBMC medical research methodology2022

Learning from COVID-19 related trial adaptations to inform efficient trial design-a sequential mixed methods study.

Robin Chatters, Cindy L Cooper, Alicia O'Cathain, Caroline Murphy, Athene Lane, Katie Sutherland, Christopher Burton, Angela Cape, Louis Tunnicliffe

Open access · goldAbstract readReview
In one paragraph

Review in BMC medical research methodology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

9 authors at 4 institutions in 1 country.

Robin ChattersSheffield Clinical Trials Research Unit, School of Health and Related Research, The University of Sheffield, Regents Court, Regent Street, Sheffield, S1 4DA, England. r.chatters@sheffield.ac.uk.
Cindy L CooperSheffield Clinical Trials Research Unit, School of Health and Related Research, The University of Sheffield, Regents Court, Regent Street, Sheffield, S1 4DA, England.
Alicia O'CathainMedical Care Research Unit, School of Health and Related Research, The University of Sheffield, Sheffield, UK.
Caroline MurphyKing's Clinical Trials Unit, King's College London, London, UK.
Athene LaneBristol Randomised Trials Collaboration in the Bristol Trials Centre, Bristol Medical School, University of Bristol, Bristol, England.
Katie SutherlandSheffield Clinical Trials Research Unit, School of Health and Related Research, The University of Sheffield, Regents Court, Regent Street, Sheffield, S1 4DA, England.
Christopher BurtonAcademic Unit of Primary Medical Care, The University of Sheffield, Sheffield, UK.
Angela CapeKing's Clinical Trials Unit, King's College London, London, UK.
Louis TunnicliffeLondon School of Hygiene & Tropical Medicine, London, UK.
University of Sheffield · GBKing's College London · GBLondon School of Hygiene & Tropical Medicine · GBUniversity of Bristol · GB

Funding

Department of Health
6 · The paper itself

Abstract

backgroundMany clinical trial procedures were often undertaken in-person prior to the COVID-19 pandemic, which has resulted in adaptations to these procedures to enable trials to continue. The aim of this study was to understand whether the adaptations made to clinical trials by UK Clinical Trials Units (CTUs) during the pandemic have the potential to improve the efficiency of trials post-pandemic.

methodsThis was a mixed methods study, initially involving an online survey administered to all registered UK CTUs to identify studies that had made adaptations due to the pandemic. Representatives from selected studies were qualitatively interviewed to explore the adaptations made and their potential to improve the efficiency of future trials. A literature review was undertaken to locate published evidence concerning the investigated adaptations. The findings from the interviews were reviewed by a group of CTU and patient representatives within a workshop, where discussions focused on the potential of the adaptations to improve the efficiency of future trials.

resultsForty studies were identified by the survey. Fourteen studies were selected and fifteen CTU staff were interviewed about the adaptations. The workshop included 15 CTU and 3 patient representatives. Adaptations were not seen as leading to direct efficiency savings for CTUs. However, three adaptations may have the potential to directly improve efficiencies for trial sites and participants beyond the pandemic: a split remote-first eligibility assessment, recruitment outside the NHS via a charity, and remote consent. There was a lack of published evidence to support the former two adaptations, however, remote consent is widely supported in the literature. Other identified adaptations may benefit by improving flexibility for the participant. Barriers to using these adaptations include the impact on scientific validity, limitations in the role of the CTU, and participant's access to technology.

conclusionsThree adaptations (a split remote-first eligibility assessment, recruitment outside the NHS via a charity, and remote consent) have the potential to improve clinical trials but only one (remote consent) is supported by evidence. These adaptations could be tested in future co-ordinated 'studies within a trial' (SWAT).

Indexed as

Clinical Trials as TopicCOVID-19Research DesignHumansPandemicsSurveys and QuestionnairesClinical trialsConsentCOVID-19Efficient trial designFollow-upIntervention deliveryRecruitmentTrial methodology

Identifiers

PMID35488193
PMCPMC9051017
OpenAlexW4225139620

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.