title: Techniques for identifying cross-disciplinary and 'hard-to-detect' evidence for systematic review.
abstract: Driven by necessity in our own complex review, we developed alternative systematic ways of identifying relevant evidence where the key concepts are generally not focal to the primary studies' aims and are found across multiple disciplines-that is, hard-to-detect evidence. Specifically, we sought to identify evidence on community engagement in public health interventions that aim to reduce health inequalities. Our initial search strategy used text mining to identify synonyms for the concept 'community engagement'. We conducted a systematic search for reviews on public health interventions, supplemented by searches of trials databases. We then used information in the reviews' evidence tables to gather more information about the included studies than was evident in the primary studies' own titles or abstracts. We identified 319 primary studies cited in reviews after full-text screening. In this paper, we retrospectively reflect on the challenges and benefits of the approach taken. We estimate that more than a quarter of the studies that were identified would have been missed by typical searching and screening methods. This identification strategy was highly effective and could be useful for reviews of broad research questions, or where the key concepts are unlikely to be the main focus of primary research.
authors.affiliation: EPPI-Centre, Social Science Research Unit, Institute of Education, University of London, 18 Woburn Square, London, UK.
authors.forename: Alison
authors.initials: A
authors.lastname: O'Mara-Eves
authors.affiliation: EPPI-Centre, Social Science Research Unit, Institute of Education, University of London, 18 Woburn Square, London, UK.
authors.forename: Ginny
authors.initials: G
authors.lastname: Brunton
authors.affiliation: PSSRU, LSE Health and Social Care and European Observatory on Health Systems and Policies, London School of Economics and Political Science.
authors.forename: David
authors.initials: D
authors.lastname: McDaid
authors.affiliation: EPPI-Centre, Social Science Research Unit, Institute of Education, University of London, 18 Woburn Square, London, UK.
authors.forename: Josephine
authors.initials: J
authors.lastname: Kavanagh
authors.affiliation: EPPI-Centre, Social Science Research Unit, Institute of Education, University of London, 18 Woburn Square, London, UK.
authors.forename: Sandy
authors.initials: S
authors.lastname: Oliver
authors.affiliation: EPPI-Centre, Social Science Research Unit, Institute of Education, University of London, 18 Woburn Square, London, UK.
authors.forename: James
authors.initials: J
authors.lastname: Thomas
mesh_terms: D057225:Data Mining / Q000379:methods; D019317:Evidence-Based Medicine; D058025:Interdisciplinary Studies; D009323:Natural Language Processing; D010506:Periodicals as Topic; D012107:Research Design; D018875:Vocabulary, Controlled; D000078202:Systematic Reviews as Topic
keywords: information retrieval; review literature as topic; screening; searching; text mining