title: Using logic models to capture complexity in systematic reviews.
abstract: Logic models have long been used to understand complex programs to improve social and health outcomes. They illustrate how a program is designed to achieve its intended outcomes. They also can be used to describe connections between determinants of outcomes, for example, low high-school graduation rates or spiraling obesity rates, thus aiding the development of interventions that target causal factors. However, these models have not often been used in systematic reviews. This paper argues that logic models can be valuable in the systematic review process. First, they can aid in the conceptualization of the review focus and illustrate hypothesized causal links, identify effect mediators or moderators, specify intermediate outcomes and potential harms, and justify a priori subgroup analyses when differential effects are anticipated. Second, logic models can be used to direct the review process more specifically. They can help justify narrowing the scope of a review, identify the most relevant inclusion criteria, guide the literature search, and clarify interpretation of results when drawing policy-relevant conclusions about review findings. We present examples that explain how logic models have been used and how they can be applied at different stages in a systematic review. Copyright © 2011 John Wiley & Sons, Ltd.
authors.affiliation: Washington State Institute for Public Policy, Olympia, Washington, USA. LAnderson@wsipp.wa.gov.
authors.forename: Laurie M
authors.initials: LM
authors.lastname: Anderson
authors.affiliation: London School of Hygiene and Tropical Medicine, University of London, London, UK.
authors.forename: Mark
authors.initials: M
authors.lastname: Petticrew
authors.affiliation: Institute for Medical Informatics, Biometry and Epidemiology, University of Munich, Munich, Germany.
authors.forename: Eva
authors.initials: E
authors.lastname: Rehfuess
authors.affiliation: Cochrane Public Health Review Group, University of Melbourne, Melbourne, Australia.
authors.forename: Rebecca
authors.initials: R
authors.lastname: Armstrong
authors.affiliation: Institute of Population Health, University of Ottawa, Ottawa, Ontario, Canada.
authors.forename: Erin
authors.initials: E
authors.lastname: Ueffing
authors.affiliation: Central Regional Services, Queensland Health, Australia and School of Public Health, Queensland University of Technology, Kelvin Grove, Australia.
authors.forename: Phillip
authors.initials: P
authors.lastname: Baker
authors.affiliation: Central Regional Services, Queensland Health, Australia.
authors.forename: Daniel
authors.initials: D
authors.lastname: Francis
authors.affiliation: Institute of Population Health and Department of Medicine, University of Ottawa, and Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
authors.forename: Peter
authors.initials: P
authors.lastname: Tugwell
keywords: logic models; population health; program evaluation; social welfare; systematic reviews