caa a22 4500 60615356X CHVBK 20210128100554.0 cr unu---uuuuu 210128e20150401xx s 000 0 eng 10.1007/s11121-014-0513-z doi (NATIONALLICENCE)springer-10.1007/s11121-014-0513-z Assessing the Generalizability of Randomized Trial Results to Target Populations [Elektronische Daten] [Elizabeth Stuart, Catherine Bradshaw, Philip Leaf] Recent years have seen increasing interest in and attention to evidence-based practices, where the "evidence” generally comes from well-conducted randomized trials. However, while those trials yield accurate estimates of the effect of the intervention for the participants in the trial (known as "internal validity”), they do not always yield relevant information about the effects in a particular target population (known as "external validity”). This may be due to a lack of specification of a target population when designing the trial, difficulties recruiting a sample that is representative of a prespecified target population, or to interest in considering a target population somewhat different from the population directly targeted by the trial. This paper first provides an overview of existing design and analysis methods for assessing and enhancing the ability of a randomized trial to estimate treatment effects in a target population. It then provides a case study using one particular method, which weights the subjects in a randomized trial to match the population on a set of observed characteristics. The case study uses data from a randomized trial of school-wide positive behavioral interventions and supports (PBIS); our interest is in generalizing the results to the state of Maryland. In the case of PBIS, after weighting, estimated effects in the target population were similar to those observed in the randomized trial. The paper illustrates that statistical methods can be used to assess and enhance the external validity of randomized trials, making the results more applicable to policy and clinical questions. However, there are also many open research questions; future research should focus on questions of treatment effect heterogeneity and further developing these methods for enhancing external validity. Researchers should think carefully about the external validity of randomized trials and be cautious about extrapolating results to specific populations unless they are confident of the similarity between the trial sample and that target population. Society for Prevention Research, 2014 Propensity scores nationallicence Horvitz-Thompson weighting nationallicence Positive behavioral interventions and supports (PBIS) nationallicence Stuart Elizabeth Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA aut Bradshaw Catherine University of Virginia, Charlottesville, VA, USA aut Leaf Philip Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA aut Prevention Science Springer US; http://www.springer-ny.com 16/3(2015-04-01), 475-485 1389-4986 16:3<475 2015 16 11121 https://doi.org/10.1007/s11121-014-0513-z text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11121-014-0513-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Stuart Elizabeth Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA aut NATIONALLICENCE 700 1- Bradshaw Catherine University of Virginia, Charlottesville, VA, USA aut NATIONALLICENCE 700 1- Leaf Philip Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA aut NATIONALLICENCE 773 0- Prevention Science Springer US; http://www.springer-ny.com 16/3(2015-04-01), 475-485 1389-4986 16:3<475 2015 16 11121