Crowdsourcing the identification of studies for <scp>COVID</scp>‐19‐related Cochrane Rapid Reviews

Abstract

BACKGROUND: Utilisation 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-h. 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-h for three reviews and in 52 h 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.

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