Cargando…

Reducing bias in trials due to reactions to measurement: experts produced recommendations informed by evidence

OBJECTIVE: This study (MEasurement Reactions In Trials) aimed to produce recommendations on how best to minimize bias from measurement reactivity (MR) in randomized controlled trials of interventions to improve health. STUDY DESIGN AND SETTING: The MERIT study consisted of: (1) an updated systematic...

Descripción completa

Detalles Bibliográficos
Autores principales: French, David P, Miles, Lisa M, Elbourne, Diana, Farmer, Andrew, Gulliford, Martin, Locock, Louise, Sutton, Stephen, McCambridge, Jim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7614249/
https://www.ncbi.nlm.nih.gov/pubmed/34229092
http://dx.doi.org/10.1016/j.jclinepi.2021.06.028
_version_ 1783605584791076864
author French, David P
Miles, Lisa M
Elbourne, Diana
Farmer, Andrew
Gulliford, Martin
Locock, Louise
Sutton, Stephen
McCambridge, Jim
author_facet French, David P
Miles, Lisa M
Elbourne, Diana
Farmer, Andrew
Gulliford, Martin
Locock, Louise
Sutton, Stephen
McCambridge, Jim
author_sort French, David P
collection PubMed
description OBJECTIVE: This study (MEasurement Reactions In Trials) aimed to produce recommendations on how best to minimize bias from measurement reactivity (MR) in randomized controlled trials of interventions to improve health. STUDY DESIGN AND SETTING: The MERIT study consisted of: (1) an updated systematic review that examined whether measuring participants had effects on participants’ health-related behaviors, relative to no-measurement controls, and three rapid reviews to identify:(i) existing guidance on MR; (ii) existing systematic reviews of studies that have quantified the effects of measurement on behavioral or affective outcomes; and (iii) studies that have investigated the effects of objective measurements of behavior on health-related behavior; (2) a Delphi study to identify the scope of the recommendations; and (3) an expert workshop in October 2018 to discuss potential recommendations in groups. RESULTS: Fourteen recommendations were produced by the expert group to: (1) identify whether bias is likely to be a problem for a trial; (2) decide whether to collect data about whether bias is likely to be a problem; (3) design trials to minimize the likelihood of this bias. CONCLUSION: These recommendations raise awareness of how and where taking measurements can produce bias in trials, and are thus helpful for trial design.
format Online
Article
Text
id pubmed-7614249
institution National Center for Biotechnology Information
language English
publishDate 2021
record_format MEDLINE/PubMed
spelling pubmed-76142492023-02-27 Reducing bias in trials due to reactions to measurement: experts produced recommendations informed by evidence French, David P Miles, Lisa M Elbourne, Diana Farmer, Andrew Gulliford, Martin Locock, Louise Sutton, Stephen McCambridge, Jim J Clin Epidemiol Article OBJECTIVE: This study (MEasurement Reactions In Trials) aimed to produce recommendations on how best to minimize bias from measurement reactivity (MR) in randomized controlled trials of interventions to improve health. STUDY DESIGN AND SETTING: The MERIT study consisted of: (1) an updated systematic review that examined whether measuring participants had effects on participants’ health-related behaviors, relative to no-measurement controls, and three rapid reviews to identify:(i) existing guidance on MR; (ii) existing systematic reviews of studies that have quantified the effects of measurement on behavioral or affective outcomes; and (iii) studies that have investigated the effects of objective measurements of behavior on health-related behavior; (2) a Delphi study to identify the scope of the recommendations; and (3) an expert workshop in October 2018 to discuss potential recommendations in groups. RESULTS: Fourteen recommendations were produced by the expert group to: (1) identify whether bias is likely to be a problem for a trial; (2) decide whether to collect data about whether bias is likely to be a problem; (3) design trials to minimize the likelihood of this bias. CONCLUSION: These recommendations raise awareness of how and where taking measurements can produce bias in trials, and are thus helpful for trial design. 2021-11-01 2021-07-03 /pmc/articles/PMC7614249/ /pubmed/34229092 http://dx.doi.org/10.1016/j.jclinepi.2021.06.028 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/) International license.
spellingShingle Article
French, David P
Miles, Lisa M
Elbourne, Diana
Farmer, Andrew
Gulliford, Martin
Locock, Louise
Sutton, Stephen
McCambridge, Jim
Reducing bias in trials due to reactions to measurement: experts produced recommendations informed by evidence
title Reducing bias in trials due to reactions to measurement: experts produced recommendations informed by evidence
title_full Reducing bias in trials due to reactions to measurement: experts produced recommendations informed by evidence
title_fullStr Reducing bias in trials due to reactions to measurement: experts produced recommendations informed by evidence
title_full_unstemmed Reducing bias in trials due to reactions to measurement: experts produced recommendations informed by evidence
title_short Reducing bias in trials due to reactions to measurement: experts produced recommendations informed by evidence
title_sort reducing bias in trials due to reactions to measurement: experts produced recommendations informed by evidence
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7614249/
https://www.ncbi.nlm.nih.gov/pubmed/34229092
http://dx.doi.org/10.1016/j.jclinepi.2021.06.028
work_keys_str_mv AT frenchdavidp reducingbiasintrialsduetoreactionstomeasurementexpertsproducedrecommendationsinformedbyevidence
AT mileslisam reducingbiasintrialsduetoreactionstomeasurementexpertsproducedrecommendationsinformedbyevidence
AT elbournediana reducingbiasintrialsduetoreactionstomeasurementexpertsproducedrecommendationsinformedbyevidence
AT farmerandrew reducingbiasintrialsduetoreactionstomeasurementexpertsproducedrecommendationsinformedbyevidence
AT gullifordmartin reducingbiasintrialsduetoreactionstomeasurementexpertsproducedrecommendationsinformedbyevidence
AT lococklouise reducingbiasintrialsduetoreactionstomeasurementexpertsproducedrecommendationsinformedbyevidence
AT suttonstephen reducingbiasintrialsduetoreactionstomeasurementexpertsproducedrecommendationsinformedbyevidence
AT mccambridgejim reducingbiasintrialsduetoreactionstomeasurementexpertsproducedrecommendationsinformedbyevidence