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

Area of Science:

• Information Science
• Medical Informatics
• Bibliometrics

Background:

• Traditional literature searches yield article lists but not content.
• Navigating extensive scientific literature, like that on COVID-19, presents challenges in concept retrieval.
• A new database system was developed using information from 1000 COVID-19 articles.

Purpose of the Study:

• To evaluate a novel information management system for concept retrieval accuracy and efficiency.
• To compare user performance with the new system against conventional research methods.
• To assess the system's utility in managing large volumes of scientific literature.

Main Methods:

• A randomized trial involving 17 university students.
• Participants researched eight COVID-19 prompts using either the new database or their usual search methods.
• Data analyzed using Cox proportional hazards models and Kaplan-Meier plots to assess time-to-correct answer.

Main Results:

• Students using the new system achieved significantly higher accuracy and speed in answering prompts.
• Previous research experience positively impacted performance but was independent of the search method used.
• The new system demonstrated superior efficiency in concept retrieval compared to conventional methods.

Conclusions:

• The developed information management system offers a promising tool for efficient literature navigation.
• This system can help researchers quickly and thoroughly access information on expansive scientific topics.
• Pilot trial results suggest potential for improved research workflows in rapidly evolving fields like COVID-19.