Linked Life Data

21238868

Source:http://linkedlifedata.com/resource/pubmed/id/21238868

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2011-1-17
pubmed:abstractText
Growing concern about the limited generalizability of trials of preventive interventions has led to several proposals concerning the design, reporting, and interpretation of such trials. This paper presents an epidemiologic framework that highlights three key determinants of population impact of many prevention programs: the proportion of the population at risk who would be candidates for a generic intervention in routine use, the proportion of those candidates who are actually intervened on through a specific program, and the reduction in incidence produced by that program among recipients. It then describes how the design of a prevention trial relates to estimating these quantities. Implications of the framework include the following: (1) reach is an attribute of a program, whereas external validity is an attribute of a trial, and the two should not be conflated; (2) specification of a defined target population at risk is essential in the long run and merits greater emphasis in the planning and interpretation of prevention trials; (3) with due attention to sampling frame and sampling method, the process of subject recruitment for a trial can yield key information about quantities that are important for assessing its potential population impact; and (4) exclusions during subject recruitment can be conceptually separated into intervention-driven, program-driven, and trial-design-driven exclusions, which have quite different implications for trial interpretation and for estimating population impact of the intervention studied.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
1873-2607
pubmed:author
pubmed:copyrightInfo
Copyright © 2011 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
pubmed:issnType
Electronic
pubmed:volume
40
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
191-8
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Estimating the population impact of preventive interventions from randomized trials.
pubmed:affiliation
Harborview Injury Prevention and Research Center, University of Washington, Seattle, WA, USA. koepsell@u.washington.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural