测量会影响被测量的人;例如,要求人们填写问卷可能会导致行为改变(“问题-行为效应”)。通常的行为和随机对照试验的分析方法隐含地假设测量对研究参与者没有影响。因此,由于测量反应性引起的测量行为和其他结果的变化可能会在其他方面进行良好的随机对照试验中引入偏差。对干预效果的估计不正确,包括低估。
主要目标是(1)提高人们对如何以及在何处进行测量会导致偏倚的认识,以及(2)就如何最好地避免或最大程度地减少因测量反应性而导致的偏倚提供建议。改善健康。
我们进行了(1)一系列系统和快速的综述,(2)德尔菲研究和(3)专家研讨会。发表了一份协议论文[MilesLM,ElbourneD,农夫A,GullifordM,L,McCambridgeJ,etal.在改善健康的试验(MERIT)中测量反应引起的偏差:制定MRC指南的研究方案。2018年试验;19:653]。更新的系统评价检查了相对于无测量对照,测量参与者是否对参与者的健康相关行为产生影响。进行了三项新的快速系统评价,以确定(1)现有的测量反应性指南,(2)现有的系统评价研究量化了测量对与行为和情感结果相关的结果的影响,以及(3)研究了暴露于行为客观测量对健康相关行为的影响的实验研究。40位专家的观点在Delphi程序期间的两次数据收集中定义了建议的范围。讲习班旨在提出一组建议,这些建议是在小组讨论中形成的。
系统评价-我们确定了总共43项研究,这些研究比较了访谈或问卷测量与没有测量的情况,这些研究的总体影响很小(标准化平均差0.06,95%置信区间0.02至0.09;n=104,096,I2=54%)。三项快速系统审查发现,没有关于测量反应性的现有指导,但是我们确实确定了五个系统评价,它们量化了测量对结果的影响(所有都集中在问题-行为效应上,所有标准化的平均差异范围为0.09-0.28),16项研究检查了行为客观测量的反应效应,与反应性小和持续时间短的大多数证据。德尔菲程序——就本建议的范围达成了实质性协议。讲习班——提出了14项建议和三个主要目标。目的是确定偏见是否可能成为审判的问题,决定是否收集进一步的定量或定性数据,以告知有关偏见是否可能成为问题的决策,并确定如何设计试验以最大程度地减少这种偏见的可能性。
主要限制是缺乏关于测量反应性程度的高质量证据,除了一些值得注意的例外,以及可能带来这种情况的情况。
我们希望这些建议将用于开发不太可能存在偏倚风险的新试验。
最大的需要是增加关于测量反应性程度的高质量初级研究的数量。
本研究中的第一个系统综述注册为PROSPEROCRD42018102511。
由英国医学研究委员会和国家健康研究所资助,作为医学研究委员会-国家健康研究方法学研究计划的一部分。
当人们被要求完成调查问卷等测量时,这可能会导致这些人的行为或情绪发生变化。例如,被要求填写饮酒问卷的人被发现饮酒略少,平均而言,而不是那些没有被要求填写问卷的人。当前建立的研究方法通常忽略这些对测量的反应。本研究旨在就如何最好地处理对测量的反应提出建议。这些建议的范围仅限于用于测试治疗是否改善健康的“试验”。要做到这一点,我们确定了相关的研究,这些研究调查了测量是否影响被测量者的各种不同方面。然后,我们就当前建议应考虑的内容以及不在当前建议范围之内的内容咨询了40名专家。然后,我们召集了23位专家,为期2天,提出了一套建议。我们发现了43项研究,研究了是否被要求填写问卷或接受采访会影响被邀请人员的行为。总的来说,完成问卷有一些影响,但在不同的研究中,效果并不十分一致。除了问卷调查(例如血压袖带)之外,很少有研究研究使用行为测量的效果。在检查治疗是否改善健康的研究中,我们找不到关于如何最好地处理测量反应的现有建议。我们为研究人员提出了14条建议,以更好地考虑影响被测量者的测量问题。我们希望这将有助于未来的研究产生更准确的答案。我们还发现,除问卷调查外,还需要对其他措施的影响进行更多研究。
Measurement can affect the people being measured; for example, asking people to complete a questionnaire can result in changes in behaviour (the \'question-behaviour effect\'). The usual methods of conduct and analysis of randomised controlled trials implicitly assume that the taking of measurements has no effect on research participants. Changes in measured behaviour and other outcomes due to measurement reactivity may therefore introduce bias in otherwise well-conducted randomised controlled trials, yielding incorrect estimates of intervention effects, including underestimates.
The main objectives were (1) to promote awareness of how and where taking measurements can lead to bias and (2) to provide recommendations on how best to avoid or minimise bias due to measurement reactivity in randomised controlled trials of interventions to improve health.
We conducted (1) a series of systematic and rapid reviews, (2) a Delphi study and (3) an expert workshop. A protocol paper was published [Miles LM, Elbourne D, Farmer A, Gulliford M, Locock L, McCambridge J, et al. Bias due to MEasurement Reactions In Trials to improve health (MERIT): protocol for research to develop MRC guidance. Trials 2018;19:653]. An updated systematic review examined whether or not measuring participants had an effect on participants\' health-related behaviours relative to no-measurement controls. Three new rapid systematic reviews were conducted to identify (1) existing guidance on measurement reactivity, (2) existing systematic reviews of studies that have quantified the effects of measurement on outcomes relating to behaviour and affective outcomes and (3) experimental studies that have investigated the effects of exposure to objective measurements of behaviour on health-related behaviour. The views of 40 experts defined the scope of the recommendations in two waves of data collection during the Delphi procedure. A workshop aimed to produce a set of recommendations that were formed in discussion in groups.
Systematic reviews - we identified a total of 43 studies that compared interview or questionnaire measurement with no measurement and these had an overall small effect (standardised mean difference 0.06, 95% confidence interval 0.02 to 0.09; n = 104,096, I2 = 54%). The three rapid systematic reviews identified no existing guidance on measurement reactivity, but we did identify five systematic reviews that quantified the effects of measurement on outcomes (all focused on the question-behaviour effect, with all standardised mean differences in the range of 0.09-0.28) and 16 studies that examined reactive effects of objective measurement of behaviour, with most evidence of reactivity of small effect and short duration. Delphi procedure - substantial agreement was reached on the scope of the present recommendations. Workshop - 14 recommendations and three main aims were produced. The aims were to identify whether or not bias is likely to be a problem for a trial, to decide whether or not to collect further quantitative or qualitative data to inform decisions about if bias is likely to be a problem, and to identify how to design trials to minimise the likelihood of this bias.
The main limitation was the shortage of high-quality evidence regarding the extent of measurement reactivity, with some notable exceptions, and the circumstances that are likely to bring it about.
We hope that these recommendations will be used to develop new trials that are less likely to be at risk of bias.
The greatest need is to increase the number of high-quality primary studies regarding the extent of measurement reactivity.
The first systematic review in this study is registered as PROSPERO CRD42018102511.
Funded by the Medical Research Council UK and the National Institute for Health Research as part of the Medical Research Council-National Institute for Health Research Methodology Research Programme.
When people are asked to complete measures such as questionnaires in research studies this can produce changes in the behaviour or emotions of those people. For example, people who are asked to complete questionnaires about drinking alcohol have been found to drink slightly less, on average, than people who are not asked to complete questionnaires. Current established methods of research usually ignore these reactions to measurement. The present research aimed to produce recommendations for how best to deal with reactions to measurement. The scope of these recommendations was limited to ‘trials’ used to test whether or not a treatment improves health. To do this, we identified relevant research studies that have investigated various different aspects of whether or not measurement affects the people being measured. We then consulted 40 experts about what the current recommendations should consider and what was not within the scope of the current recommendations. We then gathered 23 experts together for 2 days to produce a set of recommendations. We found 43 research studies that have looked at whether or not being asked to complete questionnaires or being interviewed affects the behaviour of those people invited. In general, there were some effects of completing questionnaires, but the effects were not very consistent across research studies. There were few studies that have looked at the effects of using measures of behaviour other than questionnaires (e.g. blood pressure cuffs). We could find no existing recommendations for how best to deal with reactions to measurement in research studies that examine whether or not treatments improve health. We have produced 14 recommendations for researchers to better take account of the issue of measuring affecting the people being measured. We hope that this will help future research produce more accurate answers. We also identified that there is a need for more studies of the effects of measures other than questionnaires.