Systematic Quantitative Literature Review (SQLR) and Advancing SQLR

Systematic Quantitative Literature Review (SQLR) and Advancing SQLR
Systematic Quantitative Literature Review (SQLR) and Advancing SQLR

Principal speaker

Professor Catherine Pickering

Systematic quantitative literature review is a smart and effective method for undertaking literature reviews, particularly for research students and others exploring new disciplines. It bridges the gap between traditional narrative review methods and meta-analysis. Narrative methods that are common in research theses, rely on the expertise and experience of the author, making them challenging for novices to produce and publish.

In contrast, the method we have developed involves systematically searching the literature using online databases and other sources to find all relevant papers that fit specific criteria (systematically identifying the literature), entering information about each paper into a personal database, then compiling tables that summarise the current status of the literature, including identifying research gaps (quantifying the literature).

The results are reliable, quantifiable and reproducible. Using this method, it is also possible to determine whether there are suitable datasets for meta-analysis. The method works well for specific topics, but also for summarising diverse inter-disciplinary research. There are now over 700 papers published using this method making important contributions to a wide diversity of disciplines.

The morning workshop will outline the method, how it complements other review methods, how to systematically search the literature and how to then quantify it. It will also show examples of papers that have been published using the method highlighting its relevance and applicability to a wide range of disciplines. Additional support material on the method is available at including videos that have now been watched ~150,000 times -

The advanced workshop in the afternoon will focus on key stages in the method where issues may arise, including the selection of literature, how to create and use categories in your personal dataset, and on the different ways that are being used to analyse the resulting datasets. It will also discuss some of the issues raised by reviewers of papers using this method and how you might address them. The workshop will include a chance to ask questions arising from your own reviews.


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