Pilot trial comparing COVID-19 publication database to conventional online search methods

Abstract

Background and objectives Literature review using search engines results in a list of manuscripts but does not provide the content contained in the manuscripts. Our goal was to evaluate user performance-based criteria of concept retrieval accuracy and efficiency using a new database system that contained information extracted from 1000 COVID-19 articles. Methods A sample of 17 students from the University of Vermont were randomly assigned to use the COVID-19 publication database or their usual preferred search methods to research eight prompts about COVID-19. The relevance and accuracy of the evidence found for each prompt were graded. A Cox proportional hazards' model with a sandwich estimator and Kaplan-Meier plots were used to analyse these data in a time-to-correct answer context. Results Our findings indicate that students using the new information management system answered significantly more prompts correctly and, in less time, than students using conventional research methods. Bivariate models for demographic factors indicated that previous research experience conferred an advantage in study performance, though it was found to be independent from the assigned research method. Conclusions The results from this pilot randomised trial present a potential tool for more quickly and thoroughly navigating the literature on expansive topics such as COVID-19.