School of Social and Behavioral Health Sciences, Oregon State University, 314 Milam Hall, Corvallis, OR 97331, USA.
Prev Sci. 2012 Jun;13(3):300-13. doi: 10.1007/s11121-011-0265-y.
Person mobility is an inescapable fact of life for most cluster-randomized (e.g., schools, hospitals, clinic, cities, state) cohort prevention trials. Mobility rates are an important substantive consideration in estimating the effects of an intervention. In cluster-randomized trials, mobility rates are often correlated with ethnicity, poverty and other variables associated with disparity. This raises the possibility that estimated intervention effects may generalize to only the least mobile segments of a population and, thus, create a threat to external validity. Such mobility can also create threats to the internal validity of conclusions from randomized trials. Researchers must decide how to deal with persons who leave study clusters during a trial (dropouts), persons and clusters that do not comply with an assigned intervention, and persons who enter clusters during a trial (late entrants), in addition to the persons who remain for the duration of a trial (stayers). Statistical techniques alone cannot solve the key issues of internal and external validity raised by the phenomenon of person mobility. This commentary presents a systematic, Campbellian-type analysis of person mobility in cluster-randomized cohort prevention trials. It describes four approaches for dealing with dropouts, late entrants and stayers with respect to data collection, analysis and generalizability. The questions at issue are: 1) From whom should data be collected at each wave of data collection? 2) Which cases should be included in the analyses of an intervention effect? and 3) To what populations can trial results be generalized? The conclusions lead to recommendations for the design and analysis of future cluster-randomized cohort prevention trials.
人员流动是大多数整群随机（例如，学校、医院、诊所、城市、州）队列预防试验不可避免的事实。流动率是估计干预效果的一个重要实质性考虑因素。在整群随机试验中，流动率通常与种族、贫困和其他与差异相关的变量相关。这就提出了一种可能性，即估计的干预效果可能只适用于人口中流动性最小的部分，从而对外部有效性构成威胁。这种流动也可能对随机试验的结论的内部有效性构成威胁。研究人员必须决定如何处理在试验期间离开研究群（脱落者）、不遵守指定干预措施的人员和群以及在试验期间进入群（后来者）的人员，以及在试验期间一直保持的人员（留滞者）。仅统计技术无法解决人员流动现象引起的内部和外部有效性的关键问题。本评论对整群随机队列预防试验中的人员流动进行了系统的、坎贝尔式的分析。它描述了四种处理脱落者、后来者和留滞者的方法，涉及数据收集、分析和可推广性。有争议的问题是：1）在每次数据收集浪潮中应从谁那里收集数据？2）哪些病例应包括在干预效果分析中？3）可以将试验结果推广到哪些人群？结论导致了对未来整群随机队列预防试验的设计和分析的建议。
