Who is this course for?

This course is designed for clinicians, healthcare professionals, researchers, postgraduate students, and early-career academics who want to learn how to conduct a systematic review and meta-analysis from the beginning.

Many researchers are required to perform systematic reviews during FCPS, MD, MSc, MPhil, or PhD training. However, many struggle with practical questions such as:

• How do I formulate a research question?

• How do I search PubMed effectively?

• Which studies should be included or excluded?

• How do I assess the quality of published studies?

• How do I perform a meta-analysis?

• How do I interpret a forest plot?

• How do I write a publishable systematic review?

This course provides a complete, step-by-step workflow that guides participants from developing a research question to conducting a meta-analysis and preparing a systematic review following international reporting standards.

Participants will gain hands-on experience using internationally recognised tools including Covidence, REDCap, RoB 2, GRADE, and R.

Whether you are preparing a thesis, dissertation, planning your first publication, or pursuing postgraduate training abroad, this course will provide practical research skills that can be applied immediately.

Module 1: Planning a Systematic Review

Week 1: Introduction to Systematic Reviews and Meta-analysis

Evidence-based medicine, types of literature reviews, systematic review versus meta-analysis, importance of systematic reviews in clinical research, developing focused research questions, the PICO and PECO frameworks, and an introduction to the PRISMA guidelines for reporting systematic reviews.

Practical Exercise

Develop a review question using the PICO or PECO framework.

Week 2: Protocol Development and Literature Search

Why systematic review protocols are important, PROSPERO registration, developing inclusion and exclusion criteria, literature searching using PubMed, Embase, Scopus, Web of Science, and the Cochrane Library, constructing search strategies using MeSH terms and Boolean operators, and managing references and duplicate records efficiently.

Practical Exercise

Develop eligibility criteria and create a PubMed search strategy.

Module 2: Conducting the Review

Week 3: Study Screening Using Covidence

• Importing references into Covidence, identifying and removing duplicate records, title and abstract screening, full-text screening, resolving reviewer conflicts, recording reasons for study exclusion, and generating a PRISMA flow diagram to document the study selection process.

• Practical Exercise

• Screen studies using Covidence and generate a PRISMA flow diagram.

Week 4: Data Extraction Using Covidence and REDCap

• Study characteristics, participant characteristics, intervention and comparator details, outcome data extraction, handling missing data, managing multi-arm studies, designing standardized data extraction forms, and using REDCap for efficient and structured data collection.

• Practical Exercise

• Extract data from published studies using Covidence and REDCap.

• Week 5: Risk of Bias Assessment

• Understanding bias in clinical research, distinguishing study quality from Risk of Bias, introduction to the RoB 2 assessment tool, the five domains of RoB 2, making an overall Risk of Bias judgement, and recognising common errors and pitfalls during bias assessment.

• Practical Exercise

• Assess the Risk of Bias of a published randomized controlled trial.

Module 3: Meta-analysis and Evidence Synthesis

Week 6: Introduction to Meta-analysis

• Introduction to effect measures, including Risk Ratio, Odds Ratio, Mean Difference, and Standardised Mean Difference, understanding confidence intervals, fixed-effect and random-effects models, interpreting forest plots, assessing heterogeneity using Q, Tau², and I² statistics, evaluating publication bias with funnel plots, and performing subgroup and sensitivity analyses.

• Practical Exercise

• Interpret published forest plots and understand heterogeneity statistics.

Week 7: Meta-analysis Using R

• Introduction to R and RStudio, preparing datasets for meta-analysis, using the meta and metafor packages, performing meta-analyses for binary and continuous outcomes, generating and interpreting forest plots and funnel plots, conducting subgroup and sensitivity analyses, and exporting publication-quality tables and figures for reports and scientific publications.

• Practical Exercise

• Perform a complete meta-analysis using a prepared dataset in R.

Week 8: GRADE, PRISMA Reporting and Capstone Project

• Introduction to the GRADE framework, assessing the certainty of evidence, preparing Summary of Findings tables, applying the PRISMA 2020 Checklist, writing the Methods, Results, and Discussion sections of a systematic review, selecting an appropriate journal for publication, and understanding common reviewer comments and how to address them effectively.

Capstone Project

Throughout the course, participants will progressively build a complete systematic review and meta-analysis using a research topic of their choice or one provided by the instructors.

Participants will have completed a complete mini systematic review and meta-analysis, including formulating a research question using the PICO/PECO framework, developing a review protocol, designing a comprehensive literature search strategy, defining eligibility criteria, generating a PRISMA flow diagram, screening studies, extracting study data, conducting Risk of Bias assessment, performing a meta-analysis in R, generating forest and funnel plots, preparing a GRADE Summary of Findings table, writing a PRISMA-style report, and presenting an evidence-based conclusion.

During the final session, participants will present their project and receive feedback from the instructor. The capstone project is designed to simulate a real systematic review and can serve as the foundation for a future publication, dissertation, or postgraduate research project.

Learning Outcomes

By the end of this course, participants will be able to:

• Understand the complete systematic review workflow.

• Develop focused research questions using the PICO and PECO frameworks.

• Design systematic review protocols.

• Understand PROSPERO registration.

• Perform comprehensive literature searches.

• Screen studies using Covidence.

• Extract data using Covidence and REDCap.

• Assess Risk of Bias using the RoB 2 tool.

• Perform a basic meta-analysis using R.

• Interpret forest plots, heterogeneity, and publication bias.

• Perform subgroup and sensitivity analyses.

• Evaluate certainty of evidence using the GRADE framework.

• Prepare a PRISMA-compliant systematic review suitable for publication.