PEDAGOGICAL INTERVENTIONS TO ENHANCE MESH TERM SELECTION SKILLS FOR HEALTH RESEARCHERS

Abstract

ABSTRACT
Systematic reviews in the medical field require comprehensive and carefully structured literature searches to ensure the validity and reliability of their findings. These searches are typically developed through collaboration between health researchers and information specialists who combine subject expertise with advanced knowledge of information retrieval methods. Search strategies frequently involve complex Boolean logic that integrates free-text keywords with controlled vocabularies, particularly Medical Subject Headings (MeSH). While the use of MeSH terms can significantly enhance both the accuracy and completeness of search results, selecting the most appropriate terms remains a challenging task due to the complexity of the MeSH system and varying levels of user familiarity. Insufficient expertise may result in inefficient searching or underutilization of MeSH features. This study explores automated approaches for recommending relevant MeSH terms based on initial keyword-only search queries. The primary aim is to assist users in identifying high-value MeSH terms that can strengthen systematic review search strategies. The performance of multiple recommendation methods is assessed through their impact on retrieval effectiveness, ranking quality, and the refinement of iterative search queries.