@article{TP13235,
author = {Nassr Nama and Klevis Iliriani and Meng Yang Xia and Brian P. Chen and Linghong Linda Zhou and Supichaya Pojsupap and Coralea Kappel and Katie O’Hearn and Margaret Sampson and Kusum Menon and James Dayre McNally},
title = {A pilot validation study of crowdsourcing systematic reviews: update of a searchable database of pediatric clinical trials of high-dose vitamin D},
journal = {Translational Pediatrics},
volume = {6},
number = {1},
year = {2017},
keywords = {},
abstract = {Background: Completing large systematic reviews and maintaining them up to date poses significant challenges. This is mainly due to the toll required of a small group of experts to screen and extract potentially eligible citations. Automated approaches have failed so far in providing an accessible and adaptable tool to the research community. Over the past decade, crowdsourcing has become attractive in the scientific field, and implementing it in citation screening could save the investigative team significant work and decrease the time to publication.
Methods: Citations from the 2015 update of a pediatrics vitamin D systematic review were uploaded to an online platform designed for crowdsourcing the screening process (http://www.CHEORI.org/en/CrowdScreenOverview). Three sets of exclusion criteria were used for screening, with a review of abstracts at level one, and full-text eligibility determined through two screening stages. Two trained reviewers, who participated in the initial systematic review, established citation eligibility. In parallel, each citation received four independent assessments from an untrained crowd with a medical background. Citations were retained or excluded if they received three congruent assessments. Otherwise, they were reviewed by the principal investigator. Measured outcomes included sensitivity of the crowd to retain eligible studies, and potential work saved defined as citations sorted by the crowd (excluded or retained) without involvement of the principal investigator.
Results: A total of 148 citations for screening were identified, of which 20 met eligibility criteria (true positives). The four reviewers from the crowd agreed completely on 63% (95% CI: 57–69%) of assessments, and achieved a sensitivity of 100% (95% CI: 88–100%) and a specificity of 99% (95% CI: 96–100%). Potential work saved to the research team was 84% (95% CI: 77–89%) at the abstract screening stage, and 73% (95% CI: 67–79%) through all three levels. In addition, different thresholds for citation retention and exclusion were assessed. With an algorithm favoring sensitivity (citation excluded only if all four reviewers agree), sensitivity was maintained at 100%, with a decrease of potential work saved to 66% (95% CI: 59–71%). In contrast, increasing the threshold required for retention (exclude all citations not obtaining 3/4 retain assessments) decreased sensitivity to 85% (95% CI: 65–96%), while improving potential workload saved to 92% (95% CI: 88–95%).
Conclusions: This study demonstrates the accuracy of crowdsourcing for systematic review citations screening, with retention of all eligible articles and a significant reduction in the work required from the investigative team. Together, these two findings suggest that crowdsourcing could represent a significant advancement in the area of systematic review. Future directions include further study to assess validity across medical fields and determination of the capacity of a non-medical crowd.},
issn = {2224-4344}, url = {https://tp.amegroups.org/article/view/13235}
}