French David P, Miles Lisa M, Elbourne Diana, Farmer Andrew, Gulliford Martin, Locock Louise, Sutton Stephen, McCambridge Jim
Manchester Centre for Health Psychology, University of Manchester, Oxford Road, Manchester, UK.
Manchester Centre for Health Psychology, University of Manchester, Oxford Road, Manchester, UK.
J Clin Epidemiol. 2021 Nov;139:130-139. doi: 10.1016/j.jclinepi.2021.06.028. Epub 2021 Jul 3.
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.
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.
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.
These recommendations raise awareness of how and where taking measurements can produce bias in trials, and are thus helpful for trial design.
本研究（试验中的测量反应）旨在就如何在改善健康的干预措施的随机对照试验中，最大限度地减少测量反应性（MR）带来的偏倚提出建议。
MERIT研究包括：（1）一项更新的系统评价，该评价考察了与无测量对照相比，测量参与者是否会对参与者的健康相关行为产生影响，以及三项快速评价，以确定：（i）关于测量反应性的现有指南；（ii）对测量对行为或情感结果的影响进行量化的现有研究的系统评价；（iii）研究行为的客观测量对健康相关行为的影响的研究；（2）一项德尔菲研究，以确定建议的范围；（3）2018年10月举办的一次专家研讨会，以分组讨论潜在建议。
专家组提出了14条建议，用于：（1）确定偏倚是否可能成为某项试验的问题；（2）决定是否收集有关偏倚是否可能成为问题的数据；（3）设计试验以尽量减少这种偏倚出现的可能性。
这些建议提高了人们对测量如何以及在何处会在试验中产生偏倚的认识，因此有助于试验设计。
