BACKGROUND:Systematic reviews often investigate the effectiveness of interventions for one sex. However, identifying interventions with data presented according to the sex of study participants can be challenging due to suboptimal indexing in bibliographic databases and poor reporting in titles and abstracts. The purposes of this study were to develop a highly sensitive search filter to identify literature relevant to men's health and to assess the performance of a range of sex-specific search terms used individually and in various combinations. METHODS:Comprehensive electronic searches were undertaken across a range of databases to inform a series of systematic reviews investigating obesity management for men. The included studies formed a reference standard set. A set of sex-specific search terms, identified from database-specific controlled vocabularies and from natural language used in the titles and abstracts of relevant papers, was investigated in MEDLINE and Embase. Sensitivity, precision, number needed to read (NNR) and percent reduction in results compared to searching without sex-specific terms were calculated. RESULTS:The reference standard set comprised 57 papers in MEDLINE and 63 in Embase. Seven sex-specific search terms were identified. Searching without sex-specific terms returned 31,897 results in MEDLINE and 37,351 in Embase and identified 84% (MEDLINE) and 83% (Embase) of the reference standard sets. The best performing individual sex-specific term achieved 100%/98% sensitivity (MEDLINE/Embase), NNR 544/609 (MEDLINE/Embase) and reduced the number of results by 18%/17% (MEDLINE/Embase), relative to searching without sex-specific terms. The best performing filter, compromising different combinations of controlled vocabulary terms and natural language, achieved higher sensitivity (MEDLINE and Embase 100%), greater reduction in number of results (MEDLINE/Embase 24%/20%) and greater reduction in NNR (MEDLINE/Embase 506/578) than the best performing individual sex-specific term. CONCLUSIONS:The proposed MEDLINE and Embase filters achieved high sensitivity and a reduction in the number of search results and NNR, indicating that they are useful tools for efficient, comprehensive literature searching but their performance is partially dependent on the appropriate use of database controlled vocabularies and index terms.