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Techniques for identifying cross-disciplinary and ‘hard-to-detect’ evidence for systematic review

O'Mara-Eves, A; Brunton, G; McDaid, D; Kavanagh, J; Oliver, S; Thomas, J; (2014) Techniques for identifying cross-disciplinary and ‘hard-to-detect’ evidence for systematic review. Research Synthesis Methods , 5 (1) pp. 50-59. 10.1002/jrsm.1094. Green open access

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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. Copyright

Type: Article
Title: Techniques for identifying cross-disciplinary and ‘hard-to-detect’ evidence for systematic review
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/jrsm.1094
Publisher version: https://doi.org/10.1002/jrsm.1094
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Review literature as topic; information retrieval; searching; text mining; screening
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Education
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Social Research Institute
URI: https://discovery.ucl.ac.uk/id/eprint/10192523
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