Literature DB >> 31982541

Title, abstract, and keyword searching resulted in poor recovery of articles in systematic reviews of epidemiologic practice.

Bas B L Penning de Vries1, Maarten van Smeden2, Frits R Rosendaal2, Rolf H H Groenwold3.   

Abstract

OBJECTIVE: Article full texts are often inaccessible via the standard search engines of biomedical literature, such as PubMed and Embase, which are commonly used for systematic reviews. Excluding the full-text bodies from a literature search may result in a small or selective subset of articles being included in the review because of the limited information that is available in only title, abstract, and keywords. This article describes a comparison of search strategies based on a systematic literature review of all articles published in 5 top-ranked epidemiology journals between 2000 and 2017. STUDY DESIGN AND
SETTING: Based on a text-mining approach, we studied how nine different methodological topics were mentioned across text fields (title, abstract, keywords, and text body). The following methodological topics were studied: propensity score methods, inverse probability weighting, marginal structural modeling, multiple imputation, Kaplan-Meier estimation, number needed to treat, measurement error, randomized controlled trial, and latent class analysis.
RESULTS: In total, 31,641 Hypertext Markup Language (HTML) files were downloaded from the journals' websites. For all methodological topics and journals, at most 50% of articles with a mention of a topic in the text body also mentioned the topic in the title, abstract, or keywords. For several topics, a gradual decrease over calendar time was observed of reporting in the title, abstract, or keywords.
CONCLUSION: Literature searches based on title, abstract, and keywords alone may not be sufficiently sensitive for studies of epidemiological research practice. This study also illustrates the potential value of full-text literature searches, provided there is accessibility of full-text bodies for literature searches.
Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Bibliometrics; Epidemiological methods; Statistical methods; Systematic literature review; Text mining

Mesh:

Year:  2020        PMID: 31982541     DOI: 10.1016/j.jclinepi.2020.01.009

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  6 in total

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