关键信息
关于内容
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
课程大纲
- Week 1 - 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. - Week 2 - Framing the Question
In this module, we will discuss how to frame a question, as well as scope, elements, and refining the question. - Week 3 - 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. - Week 4 - 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. - Week 5 - Planning the Meta-Analysis and Statistical Methods
This module will cover the planning of your meat-analysis and the statistical methods for meta-analysis. - Week 6 - Wrap Up and Final Peer Review Assignment
In this final module, we'll wrap up with a look back at the key concepts covered over the past few weeks. Afterwards, you will submit your final Peer Review Assignment and evaluate some of your classmates' submissions.
教师
Tianjing Li, MD, MHS, PHD
Assistant Professor, Epidemiology
Bloomberg School of Public Health
Kay Dickersin, PhD
Professor, Epidemiology
Bloomberg School of Public Health
内容设计师
平台
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