Abstract
Systematic reviews are powerful methods used to determine the state-of-the-art in a given field from existing studies and literature. They are critical but time-consuming in research and decision making for various disciplines. When conducting a review, a large volume of data is usually generated from relevant studies. Computer-based tools are often used to manage such data and to support the systematic review process. This paper describes a comprehensive analysis to gather the required features of a systematic review tool, in order to support the complete evidence synthesis process. We propose a framework, elaborated by consulting experts in different knowledge areas, to evaluate significant features and thus reinforce existing tool capabilities. The framework will be used to enhance the currently available functionality of CloudSERA, a cloud-based systematic review tool focused on Computer Science, to implement evidence-based systematic review processes in other disciplines.
Highlights
CondeResearch and development activity and decision making usually require a preliminary study of related literature to understand the up-to-date, state-of-the-art issues, techniques and methods in a given research field
Include computational support to partially automate some of the evidence data synthesis techniques, such as: grounded theory, content analysis, case survey, metaethnography, meta-study, narrative summary, meta-study, qualitative comparative analysis methods, meta-synthesis, and thematic analysis
Undertaking systematic reviews is an essential task before starting any research activity
Summary
CondeResearch and development activity and decision making usually require a preliminary study of related literature to understand the up-to-date, state-of-the-art issues, techniques and methods in a given research field. Health Science researchers need to find out the scientific evidence that supports their clinical decisions. A huge volume of data is published and stored in digital bibliographic repositories, which are often manually reviewed in order to select those related to the field and research purpose. It is important to be acquainted with the quality of the evidence provided in these studies. In this vein, tools such as GRADEpro [5] have emerged, to synthesize and evaluate the quality of evidence found in health science-related studies
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