Write your abstracts carefully—The impact of abstract reporting quality on findability by semi-automated title-abstract screening tools

Systematic reviews summarize scientific evidence from literature to support clinical decision-making. In the conduct of a systematic review, thousands of papers have to be screened for relevance, making the process costly and laborious. To accelerate this process, several tools have been developed that can assist in identifying relevant scientific literature. Such tools screen through the abstracts of scientific papers and predict which papers are likely relevant for the systematic review. However, the performance of these screening tools may depend on whether information is accurately and completely reported in the abstracts. Here, we aimed to evaluate the impact of abstract reporting quality on the performance of screening tools. We used data from a set of scientific papers of which the abstract reporting quality was scored manually (following an existing reporting checklist called TRIPOD), and we applied an existing screening tool as an example. We simulated the procedure of conducting a scientific review and evaluated whether the relevance predictions by the screening tool were associated with abstract reporting quality. We found that relevant scientific papers with abstracts that had poor reporting quality were more difficult to identify as relevant by the screening tool. This finding highlights the importance of adhering to reporting guidelines, not only for transparency of scientific findings but also for optimal usage of screening tools in the conduct of a systematic review.