Abstract
Abstract
Background
Systematic literature screening is a key component in systematic reviews. However, this approach is resource intensive as generally two persons independently of each other (double screening) screen a vast number of search results. To develop approaches for increasing efficiency, we tested the use of text mining to prioritize search results as well as the involvement of only one person (single screening) in the study selection process.
Method
Our study is based on health technology assessments (HTAs) of drug and non-drug interventions. Using a sample size calculation, we consecutively included 11 searches resulting in 33 study selection processes. Of the three screeners for each search, two used screening tools with prioritization (Rayyan, EPPI Reviewer) and one a tool without prioritization. For each prioritization tool, we investigated the proportion of citations classified as relevant at three cut-offs or STOP criteria (after screening 25%, 50% and 75% of the citation set). For each STOP criterion, we measured sensitivity (number of correctly identified relevant studies divided by the total number of relevant studies in the study pool). In addition, we determined the number of relevant studies identified per single screening round and investigated whether missed studies were relevant to the HTA conclusion.
Results
Overall, EPPI Reviewer performed better than Rayyan and identified the vast majority (88%, Rayyan 66%) of relevant citations after screening half of the citation set. As long as additional information sources were screened, it was sufficient to apply a single-screening approach to identify all studies relevant to the HTA conclusion. Although many relevant publications (n = 63) and studies (n = 29) were incorrectly excluded, ultimately only 5 studies could not be identified at all in 2 of the 11 searches (1x 1 study, 1x 4 studies). However, their omission did not change the overall conclusion in any HTA.
Conclusions
EPPI Reviewer helped to identify relevant citations earlier in the screening process than Rayyan. Single screening would have been sufficient to identify all studies relevant to the HTA conclusion. However, this requires screening of further information sources. It also needs to be considered that the credibility of an HTA may be questioned if studies are missing, even if they are not relevant to the HTA conclusion.
Funder
Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen
Publisher
Springer Science and Business Media LLC
Reference32 articles.
1. O’Mara-Eves A, Thomas J, McNaught J, Miwa M, Ananiadou S. Using text mining for study identification in systematic reviews: a systematic review of current approaches. Syst Rev. 2015;4:5.
2. Olofsson H, Brolund A, Hellberg C, Silverstein R, Stenström K, Österberg M, et al. Can abstract screening workload be reduced using text mining? User experiences of the tool Rayyan. Res Syn Meth. 2017;8:275–80.
3. Lefebvre C, Glanville J, Briscoe S, Littlewood A, Marshall C, Metzendorf MI, et al. Chapter 4: searching for and selecting studies. In: Higgins J TJE, editor., et al., Cochrane handbook for systematic reviews of interventions: version 6.1. London: The Cochrane Collaboration; 2020.
4. Rathbone J, Hoffmann T, Glasziou P. Faster title and abstract screening? Evaluating Abstrackr, a semi-automated online screening program for systematic reviewers. Syst Rev. 2015;4:80.
5. Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan: a web and mobile app for systematic reviews. Syst Rev. 2016;5:210.
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献