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Crowdsourcing the identification of studies for COVID-19 related Cochrane Rapid Reviews.

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BACKGROUND Utilization of crowdsourcing within evidence synthesis has increased over the last decade. Crowdsourcing platform Cochrane Crowd has engaged a global community of 22,000 people from 170 countries. The COVID-19… Click to show full abstract

BACKGROUND Utilization of crowdsourcing within evidence synthesis has increased over the last decade. Crowdsourcing platform Cochrane Crowd has engaged a global community of 22,000 people from 170 countries. The COVID-19 pandemic presented an opportunity to engage the community and keep up with the exponential output of COVID-19 research. AIMS To test whether a crowd could accurately assess study eligibility for reviews under time constraints. OUTCOME MEASURES time taken to complete each task, time to produce required training modules, crowd sensitivity, specificity and crowd consensus. METHODS We created four crowd tasks, corresponding to four Cochrane COVID-19 Rapid Reviews. The search results of each were uploaded and an interactive training module was developed for each task. Contributors who had participated in another COVID-19 task were invited to participate. Each task was live for 48-hours. The final inclusion and exclusion decisions made by the core author team were used as the reference standard. RESULTS Across all four reviews 14,299 records were screened by 101 crowd contributors. The crowd completed each screening task within 48-hours for three reviews and in 52 hours for one. Sensitivity ranged from 94% to 100%. Four studies, out of a total of 109, were incorrectly rejected by the crowd. However, their absence ultimately would not have altered the conclusions of the reviews. Crowd consensus ranged from 71% to 92% across the four reviews. CONCLUSION Crowdsourcing can play a valuable role in study identification and offers willing contributors the opportunity to help identify COVID-19 research for rapid evidence syntheses. This article is protected by copyright. All rights reserved.

Keywords: crowd; task; cochrane; crowdsourcing identification; rapid reviews

Journal Title: Research synthesis methods
Year Published: 2022

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