Symposium Systematic Reviewing 3.0
Systematic Reviews are “top of the bill” in research. The number of systematic reviews published by researchers increases year after year. But performing a sound systematic review is a time-consuming and sometimes boring task. You can make use of tools to work efficiently and of support offered by the library. New developments like text mining, applying R for meta analysis and funding options might improve systematic reviews even more.
The Systematic Reviewing 3.0 symposium is both for novices and experts in systematic reviews. In the morning you can get acquainted with how to perform the ‘perfect’ systematic review, its different phases and the tools available. In the afternoon we will discuss future developments; will machines take over?
Part I: the perfect systematic search
Introduction ‘Death by database: how (not) to perform a systematic review’ – by Rens van de Schoot, associate professor in Methodology and Statistics at the Faculty of Social Sciences, Utrecht University
In a tragic situation that could have been averted, Ellen Roche, a healthy, 24-year-old volunteer in an asthma study, died because the researchers failed to include all relevant literature in their search – they only searched for papers in PubMed and failed to find studies studying serious side effects. (source)
The participants are looking forward to today, some just like penguins… Then we asked them how many abstracts they could screen per hour and how many hours can you screen non-stop?
Lunch with some music by the band Minor Revisions
— Rens van de Schoot (@RensvdSchoot) November 13, 2018
Part II: The future of systematic reviewing
This symposium is part of the project titled Automated Systematic Review, funded by the Innovation Fund for IT in Research Projects and in collaboration with the focus area Utrecht Applied Data Science. ADS builds a community of researchers who are interested in developing the field of data science. By joining forces and working interdisciplinarily, we can accelerate the development of data science techniques within Utrecht University. Join our community at www.uu.nl/ads