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Reporting methodological search filter performance comparisons: a literature review.

Jennifer Harbour1, Cynthia Fraser, Carol Lefebvre

  • 1Healthcare Improvement Scotland, Glasgow, UK.

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This review of methodological search filters found that sensitivity/recall and precision are the most commonly reported performance measures. Innovative presentation of filter performance data could improve selection of appropriate research tools.

Keywords:
bibliographic databasesinformation storage and retrievalmethodological filtersprecisionrecallreview, literature

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Area of Science:

  • Information Science
  • Medical Informatics
  • Health Research Methods

Background:

  • Methodological search filters aid in retrieving studies using specific research methods.
  • Filter selection relies on performance data, necessitating clear presentation.
  • This review analyzes reported measures and presentation formats in filter comparison studies.

Purpose of the Study:

  • To examine the performance measures reported in studies comparing methodological search filters.
  • To evaluate how filter performance data is presented in comparative studies.
  • To identify opportunities for improved presentation of filter performance.

Main Methods:

  • Systematic review of studies comparing methodological search filters.
  • Filters targeted randomized controlled trials, diagnostic accuracy studies, systematic reviews, and economic evaluations.
  • Data extracted included performance measures and presentation formats.

Main Results:

  • Eighteen studies were included, comparing 2 to 38 filters.
  • Sensitivity/recall and precision were the most frequently reported performance measures.
  • Results were primarily presented in tables as percentages; graphical displays were rare.

Conclusions:

  • Sensitivity/recall and precision are the dominant metrics for evaluating search filter performance.
  • Current presentation methods, mainly tables, may not fully optimize filter selection.
  • Novel and innovative graphical or visual presentations could enhance the utility of filter comparison data.