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2 results

  • Translation and validation of a geographic search filter to identify studies about Germany in Embase (Ovid) and MEDLINE(R) ALL (Ovid)

  • Alexander Pachanov, Catharina Muente, Julian Hirt, Dawid Pieper
  • Journal:
    Research Synthesis Methods / Volume 16 / Issue 4 / July 2025
    Published online by Cambridge University Press:
    09 June 2025, pp. 688-700
    • Article
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  • We developed a geographic search filter for retrieving studies about Germany from PubMed. In this study, we aimed to translate and validate it for use in Embase and MEDLINE(R) ALL via Ovid. Adjustments included aligning PubMed field tags with Ovid’s syntax, adding a keyword heading field for both databases, and incorporating a correspondence address field for Embase. To validate the filters, we used systematic reviews (SRs) that included studies about Germany without imposing geographic restrictions on their search strategies. Subsequently, we conducted (i) case studies (CSs), applying the filters to the search strategies of the 17 eligible SRs; and (ii) aggregation studies, combining the SRs’ search strategies with the ‘OR’ operator and applying the filters. In the CSs, the filters demonstrated a median sensitivity of 100% in both databases, with interquartile ranges (IQRs) of 100%–100% in Embase and 93.75%–100% in MEDLINE(R) ALL. Median precision improved from 0.11% (IQR: 0.05%–0.30%) to 1.65% (IQR: 0.78%–3.06%) and from 0.19% (IQR: 0.11%–0.60%) to 5.13% (IQR: 1.77%–6.85%), while the number needed to read (NNR) decreased from 893.40 (IQR: 354.81–2,219.58) to 60.44 (IQR: 33.94–128.97) and from 513.29 (IQR: 167.35–930.99) to 19.50 (IQR: 14.66–59.35) for Embase and MEDLINE(R) ALL, respectively. In the aggregation studies, the overall sensitivities were 98.19% and 97.14%, with NNRs of 83.29 and 33.34 in Embase and MEDLINE(R) ALL, respectively. The new Embase and MEDLINE(R) ALL filters for Ovid reliably retrieve studies about Germany, enhancing search precision. The approach described in our study can support search filter developers in translating filters for various topics and contexts.

  • 3 - Developing a search strategy, locating studies and electronic databases

    • By Tom Pedersen, The Cochrane Anaesthesia Review Group, Centre of Head-Orthopaedics, University of Copenhagen, Rigshospitalet, Copenhagen, Denmark
  • Edited by Ann Møller, KAS Herlev, Copenhagen, Tom Pedersen, Rigshospitalet, Copenhagen
  • Book:
    Evidence-based Anaesthesia and Intensive Care
    Published online:
    05 September 2009
    Print publication:
    09 October 2006, pp 7-18

  • Summary

    This chapter shows how to conduct a comprehensive, objective and reproducible search for studies. It is always necessary to strike a balance between comprehensiveness and precision when developing a search strategy. Developing a search strategy is an iterative process in which the terms that are used are modified, based on what has already been retrieved. An electronic search strategy should generally have three sets of terms: terms to search for the health condition of interest; terms to search for the intervention(s) evaluated and terms to search for the types of study design to be included. Searches of electronic databases are generally the easiest and least time-consuming way to identify an initial set of relevant reports. The chapter discusses how and where the reviewers should look for studies that may be eligible for inclusion such as The Cochrane Library, MEDLINE, EMBASE and other relevant databases that identify appropriate MeSH terms.