Evidence map›Paper›PMID 30477551›Full record

ArticleTrials2018

Bias due to MEasurement Reactions In Trials to improve health (MERIT): protocol for research to develop MRC guidance.

Lisa M Miles, Diana Elbourne, Andrew Farmer, Martin Gulliford, Louise Locock, Jim McCambridge, Stephen Sutton, David P French

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

Article in Trials, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
2.3field-weighted citation impact, top 11% 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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 26 citations in OpenAlex.

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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

8 authors at 7 institutions in 1 country.

Lisa M MilesManchester Centre for Health Psychology, University of Manchester, Oxford Road, Manchester, UK.
Diana ElbourneDepartment of Medical Statistics, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.
Andrew FarmerNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Martin GullifordSchool of Population Health and Environmental Sciences, King's College London, London, UK.
Louise LocockHealth Services Research Unit, University of Aberdeen, Aberdeen, UK.
Jim McCambridgeDepartment of Health Sciences, University of York, York, UK.
Stephen SuttonDepartment of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
David P FrenchManchester Centre for Health Psychology, University of Manchester, Oxford Road, Manchester, UK. david.french@manchester.ac.uk.
Manchester Academic Health Science Centre · GBKing's College London · GBUniversity of Aberdeen · GBUniversity of Cambridge · GBUniversity of London · GBUniversity of Oxford · GBUniversity of York · GB

Funding

Chief Scientist Office HSRU1Medical Research Council MC_PC_17229MRC/NIHR MC_PC_17229
6 · The paper itself

Abstract

backgroundThere is now clear systematic review evidence that measurement can affect the people being measured; much of this evidence focusses on how asking people to complete a questionnaire can result in changes in behaviour. Changes in measured behaviour and other outcomes due to this reactivity may introduce bias in otherwise well-conducted randomised controlled trials (RCTs), yielding incorrect estimates of intervention effects. Despite this, measurement reactivity is not currently adequately considered in risk of bias frameworks. The present research aims to produce a set of guidance statements on how best to avoid or minimise bias due to measurement reactivity in studies of interventions to improve health, with a particular focus on bias in RCTs.

methodsThe MERIT study consists of a series of systematic and rapid reviews, a Delphi study and an expert workshop to develop guidance on how to minimise bias in trials due to measurement reactivity. An existing systematic review on question-behaviour effects on health-related behaviours will be updated and three new rapid reviews will be conducted to identify (1) existing guidance on measurement reactivity; (2) systematic reviews of studies that have quantified the effects of measurement on outcomes relating to behaviour and affective outcomes in health and non-health contexts and (3) trials that have investigated the effects of objective measurements of behaviour on concurrent or subsequent behaviour itself. A Delphi procedure will be used to combine the views of experts with a view to reaching agreement on the scope of the guidance statements. Finally, a workshop will be held in autumn 2018, with the aim of producing a set of guidance statements that will form the central part of new MRC guidance on how best to avoid bias due to measurement reactivity in studies of interventions to improve health. DISCUSSION: Our ambition is to produce MRC guidance on measurement reactions in trials which will be used by future trial researchers, leading to the development of trials that are less likely to be at risk of bias.

Indexed as

BiasConsensusConsensus Statements as TopicData AccuracyDelphi TechniqueEndpoint DeterminationHumansRandomized Controlled Trials as TopicReproducibility of ResultsResearch DesignStakeholder ParticipationSystematic Reviews as TopicTreatment OutcomeBiasGuidanceHawthorne effectMeasurementMeasurement reactionsReactivityTrials

Identifiers

PMID30477551
PMCPMC6258480
OpenAlexW2902894498

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.