Introduction to Systematic Review and Meta-Analysis

Introduction to Systematic Review and Meta-Analysis

Instructors: Tianjing Li, MD, MHS, PHD

Access provided by HKUST

215,596 already enrolled

6 modules

Gain insight into a topic and learn the fundamentals.

3,586 reviews

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

97%

Most learners liked this course

6 modules

Gain insight into a topic and learn the fundamentals.

3,586 reviews

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

97%

Most learners liked this course

Skills you'll gain

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Assessments

7 assignments¹

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Taught in English

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There are 6 modules in this course

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

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.

What's included

5 videos3 readings

5 videosTotal 40 minutes

Welcome to Systematic Reviews and Meta-Analysis 2 minutes
Lecture 1A : Introduction to Systematic Reviews15 minutes
Lecture 1B: Introduction to Meta-Analysis13 minutes
Lecture 1C: Producers and Users of Systematic Reviews8 minutes
Hannah Rothstein, PhD1 minute

3 readingsTotal 30 minutes

Syllabus10 minutes
Pre Course Survey10 minutes
From the Field Videos10 minutes

In this module, we will discuss how to frame a question, as well as scope, elements, and refining the question.

What's included

7 videos1 reading1 assignment1 peer review

7 videosTotal 73 minutes

Lecture 2A: Resources for How to Frame Your Question7 minutes
Lecture 2B: Deciding the Type and Scope of Your Question18 minutes
Lecture 2C: Elements of the Question17 minutes
Lecture 2D: Refining the Question11 minutes
Lecture 2E: Some Examples9 minutes
Lecture 2F: Analytic Frameworks10 minutes
Betsy Becker, PhD2 minutes

1 readingTotal 10 minutes

Welcome to the first Peer Assignment!10 minutes

1 assignmentTotal 30 minutes

Module 230 minutes

1 peer reviewTotal 120 minutes

Peer Assessment 1120 minutes

In this module we will look at finding the evidence, as well as key sources, search strategy, and assessing the risk of bias.

What's included

11 videos2 assignments

11 videosTotal 119 minutes

Searching Principles and Assessing Bias 3 minutes
Lecture 3A: Finding the Evidence: Searching Principles6 minutes
Lecture 3B: Identifying Key Sources and Techniques for Searching18 minutes
Lecture 3C: Building a High-Quality Search Strategy17 minutes
Lecture 3D: Documenting Your Search and Conclusions8 minutes
Lecture 4A: Why Bias in the Individual Study is Important to a Systematic Review and Meta-Analysis7 minutes
Lecture 4B: Selection Bias19 minutes
Lecture 4C: Information Bias8 minutes
Lecture 4D: Bias in the Analysis15 minutes
Lecture 4E: Displaying Study "Quality" in Your Systematic Review16 minutes
Byron Wallace, Phd2 minutes

2 assignmentsTotal 60 minutes

Module 330 minutes
Module 430 minutes

In this module, we will cover minimizing metabias, selection bias, information bias, how to report transparently, qualitative synthesis, and interpreting results.

What's included

9 videos2 assignments

9 videosTotal 88 minutes

Lecture 5A: Standards for Systematic Reviews6 minutes
Lecture 5B: Selection Bias22 minutes
Lecture 5C: Information Bias13 minutes
Lecture 5D: Bias in the Analysis15 minutes
Lecture 5E: Reporting Transparently7 minutes
Lecture 6A: Qualitative Synthesis and Interpreting Results Section A7 minutes
Lecture 6B: What is Qualitative Synthesis10 minutes
Lecture 6C: Some Examples6 minutes
Christopher Schmid, PhD1 minute

2 assignmentsTotal 60 minutes

Module 530 minutes
Module 630 minutes

This module will cover the planning of your meat-analysis and the statistical methods for meta-analysis.

What's included

9 videos2 assignments

9 videosTotal 109 minutes

Planning Meta-Analysis and Statistical Methods 1 minute
Lecture 7A: Planning Your Meta-Analysis Section A8 minutes
Lecture 7B: Introduction to Meta-Analysis15 minutes
Lecture 7C: Why Do a Meta-Analysis?11 minutes
Lecture 7D: Types of Data and Effect Measures20 minutes
Lecture 8A: Fixed Effect Model21 minutes
Lecture 8B: Random Effects Model15 minutes
Lecture 8C: Random Effects Model17 minutes
Michael Borenstein, PhD2 minutes

2 assignmentsTotal 60 minutes

Module 730 minutes
Module 830 minutes

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.

What's included

2 videos1 reading1 peer review

Instructors

Instructor ratings

(937 ratings)

Tianjing Li, MD, MHS, PHD

Johns Hopkins University

1 Course215,596 learners

Kay Dickersin, PhD

Johns Hopkins University

1 Course215,596 learners

Offered by

Johns Hopkins University

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Reviewed on Feb 12, 2017

Incredible course! You learned a lot from these amazing professors. If you take this course you will know how to do a high quality systematic review and even a meta analysis and publish them.

Reviewed on Aug 4, 2020

thank you very much for the opportunity to learn this subject. at least now, i will not be "left out" when my colleagues are discussing these things during critical appraisals of journals.

Reviewed on Apr 16, 2020

It must include some basics for Statistics involved in Meta analysis, other new students joining from world because they did not study this in their Epidemiology classes in their universities.

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