We will introduce methods to perform systematic reviews and meta-analysis of clinical trials. We will cover how to formulate an answerable research question, define inclusion and exclusion criteria, search for the evidence, extract data, assess the risk of bias in clinical trials, and perform a meta-analysis. Upon successfully completing this course, participants will be able to: - Describe the steps in conducting a systematic review - Develop an answerable question using the “Participants Interventions Comparisons Outcomes” (PICO) framework - Describe the process used to collect and extract data from reports of clinical trials - Describe methods to critically assess the risk of bias of clinical trials - Describe and interpret the results of meta-analyses
提供方
教學大綱 - 您將從這門課程中學到什麼
Introduction
To get the ball rolling, we'll take a broad overview of what to expect in this course and then introduce you to the high-level concepts of systematic review and meta-analysis and take a look at who produces and uses systematic reviews.
Framing the Question
In this module, we will discuss how to frame a question, as well as scope, elements, and refining the question.
Searching Principles and Bias Assessment
In this module we will look at finding the evidence, as well as key sources, search strategy, and assessing the risk of bias.
Minimizing Metabias, Qualitative Synthesis, and Interpreting Results
In this module, we will cover minimizing metabias, selection bias, information bias, how to report transparently, qualitative synthesis, and interpreting results.
30%
24%
14%
來自系统评估和元分析入门的熱門評論
Although introductory, I do carry out reviews as a researcher. I Learned a lot to improve my systematic reviews through this course. High quality, though the music could be a little less intense.
Introduction to Systematic Review and Meta-Analysis course is a very good source for beginners which provides an overview on fundamental terminology and steps involved in the systematic review.
講師
Tianjing Li, MD, MHS, PHD
Assistant Professor, Epidemiology
Kay Dickersin, PhD
Professor, Epidemiology關於 约翰霍普金斯大学
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