A research and development agenda for systematic reviews that ask complex questions about complex interventions

Jane Noyes, David Gough, Simon Lewin, Alain Mayhew, Susan Michie, Tomas Pantoja, Mark Petticrew, Kevin Pottie, Eva Rehfuess, Ian Shemilt, Sasha Shepperd, Amanda Sowden, Peter Tugwell, Vivian Welch

    Research output: Contribution to journalArticlepeer-review

    Abstract

    OBJECTIVES: This article outlines a research and development agenda for systematic reviews that ask complex questions about interventions varying in degree and type of complexity.

    STUDY DESIGN AND SETTING: Consensus development by key authors of articles on methodological challenges in systematic reviews of complex interventions, based on a 2-day workshop in Montebello, Canada, January 2012.

    RESULTS: There is an urgent need for a more precise and consistently applied lexicon and language to disaggregate several conceptually distinct dimensions of "complexity." Selected current evidence synthesis methods have potential application in reviews where complexity is important. There is a lack of evaluation of methods to better understand the nature of complex interventions and the optimal processes of synthesizing and interpreting evidence from these systematic reviews. Gaps in methods, knowledge, and know-how exist, and there is a need for additional guidance.

    CONCLUSION: Understanding how complexity can impact on findings of systematic reviews is critical. Experience in applying methods that have been developed to facilitate this understanding is limited, and the degree to which these approaches improve the systematic review process or transparency is only partially understood. Future research should concentrate on the impact of complexity on the systematic review process and findings and on further methodological development.

    Original languageEnglish
    Pages (from-to)1262-70
    Number of pages9
    JournalJournal of Clinical Epidemiology
    Volume66
    Issue number11
    DOIs
    Publication statusPublished - Nov 2013

    Keywords

    • Data Interpretation, Statistical
    • Humans
    • Research Design
    • Review Literature as Topic
    • Comment
    • Journal Article
    • Research Support, Non-U.S. Gov't

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