Julie Glanville1, Gordon Dooley2, Susi Wisniewski3, Ruth Foxlee4, Anna Noel-Storr4. 1. York Health Economics Consortium, Enterprise House, Innovation Way, University of York, York, UK. 2. Metaxis Ltd, Curbridge, UK. 3. Cochrane Editorial Unit, London, UK. 4. Cochrane Dementia and Cognitive Improvement Group, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
Abstract
BACKGROUND: Evidence synthesis reviews in health care rely on the efficient identification of research evidence, particularly evidence from randomised controlled trials (RCTs). There are no recently validated filters to identify RCTs in the Cumulative Index to Nursing and Allied Health Literature (CINAHL Plus). OBJECTIVES: To develop, test and validate a search filter to identify reports of RCTs from CINAHL Plus. METHODS: Nine sets of relevant and irrelevant records were identified to develop and test search filters iteratively. Two sets were used to validate the sensitivity and precision of the filters. The performance of two previously published filters and the filter built into EBSCOhost was evaluated. RESULTS: We present a validated filter which offers sensitivity of 0.88 (95% CI: 0.77-0.95) and precision of 0.36 (95% CI: 0.31-0.41). This is comparable to the sensitivity of published filters, but has much better precision. CONCLUSIONS: A sensitive and precise filter, developed using records selected based on title and abstract information, is available for identifying reports of RCTs in the CINAHL Plus database via EBSCOhost. Using this filter is likely to reduce the number of results needing to be screened to a quarter of those retrieved by other published filters.
BACKGROUND: Evidence synthesis reviews in health care rely on the efficient identification of research evidence, particularly evidence from randomised controlled trials (RCTs). There are no recently validated filters to identify RCTs in the Cumulative Index to Nursing and Allied Health Literature (CINAHL Plus). OBJECTIVES: To develop, test and validate a search filter to identify reports of RCTs from CINAHL Plus. METHODS: Nine sets of relevant and irrelevant records were identified to develop and test search filters iteratively. Two sets were used to validate the sensitivity and precision of the filters. The performance of two previously published filters and the filter built into EBSCOhost was evaluated. RESULTS: We present a validated filter which offers sensitivity of 0.88 (95% CI: 0.77-0.95) and precision of 0.36 (95% CI: 0.31-0.41). This is comparable to the sensitivity of published filters, but has much better precision. CONCLUSIONS: A sensitive and precise filter, developed using records selected based on title and abstract information, is available for identifying reports of RCTs in the CINAHL Plus database via EBSCOhost. Using this filter is likely to reduce the number of results needing to be screened to a quarter of those retrieved by other published filters.
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