Systematic Review - right from the start

A systematic guide to producing a great review

Ratings: 4.38 / 5.00




Description

Systematic review and meta-analysis are skills that most academics need to possess. However, statistics courses often assume a deep knowledge of mathematics, statistics or programming. Moreover, recent studies have shown that the majority of systematic reviews published in the literature are of poor quality. My course will teach you to undertake high-quality reviews using open source or free software (where possible), which will not only ensure that your review is done well, but that will also give your work a much better chance of being accepted for publication.

I am a highly experienced scientist with publications in major journals. My systematic reviews and meta-analyses on fructose metabolism were published in a high-ranking journal and were reported on in news outlets all over the world.

I don't assume any prior knowledge of statistics, mathematics, programming or use of statistical software packages. You need only bring your subject matter expertise to the course - everything else will be provided. This course also provides short quizzes to help you check your progress.

This course is suitable for all areas of academic endeavour - not just the health sciences. I would love to see academics and researchers take up this powerful methodology in every field of study.

What You Will Learn!

  • Understand the difference between a systematic review and a narrative review
  • Understand the difference between a systematic review and a meta-analysis
  • Choose the right topic and recruit the right team members
  • Design a research question using PICOTS
  • Register a review with PROSPERO
  • Analyse RCTs, cohort studies and case-control studies
  • Design an excellent search strategy
  • Identify and control for bias
  • Undertake citation management
  • Code abstracts using a non-shareable review
  • Code abstracts using a shareable review
  • Design and code full-texts

Who Should Attend!

  • Anyone who wants to learn to do systematic review - in any area of interest