Effective study selection using text mining or a single-screening approach: a study protocol

Systematic information retrieval generally requires a two-step selection process for studies, which is conducted by two persons independently of one another (double-screening approach). To increase efficiency, two methods seem promising, which will be tested in the planned study: the use of text mining to prioritize search results as well as the involvement of only one person in the study selection process (single-screening approach). The aim of the present study is to examine the following questions related to the process of study selection: Can the use of the Rayyan or EPPI Reviewer tools to prioritize the results of study selection increase efficiency? How accurately does a single-screening approach identify relevant studies? Which advantages or disadvantages (e.g., shortened screening time or increase in the number of full texts ordered) does a single-screening versus a double-screening approach have?

Our study is a prospective analysis of study selection processes based on benefit assessments of drug and non-drug interventions. It consists of two parts: firstly, the evaluation of a single-screening approach based on a sample size calculation (11 study selection processes, including 33 single screenings) and involving different screening tools and, secondly, the evaluation of the conventional double-screening approach based on five conventional study selection processes. In addition, the advantages and disadvantages of the single-screening versus the double-screening approach with regard to the outcomes “number of full texts ordered” and “time required for study selection” are analyzed. The previous work experience of the screeners is considered as a potential effect modifier.

No study comparing the features of prioritization tools is currently available. Our study can thus contribute to filling this evidence gap. This study is also the first to investigate a range of questions surrounding the screening process and to include an a priori sample size calculation, thus enabling statistical conclusions. In addition, the impact of missing studies on the conclusion of a benefit assessment is calculated.

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