Training Course on Systematic Reviews and Meta-Analysis

Module 1: Introduction to Systematic Reviews and Meta-Analysis
Objective: Understand the purpose, scope, and methodology of systematic reviews and meta-analysis.
Subtopics:
Definition and importance of systematic reviews and meta-analysis.
Differences between narrative reviews and systematic reviews.
Overview of the systematic review process and workflow.
Role of evidence synthesis in evidence-based medicine and policy.
Common pitfalls and challenges in conducting systematic reviews.

Module 2: Formulating Research Questions and Protocol Development
Objective: Develop clear, structured research questions and protocols for systematic reviews.
Subtopics:
Using PICO (Population, Intervention, Comparison, Outcome) framework.
Defining inclusion and exclusion criteria.
Developing a detailed review protocol.
Registering protocols in PROSPERO or other registries.
Establishing review objectives and outcomes.

Module 3: Literature Search and Study Selection
Objective: Conduct comprehensive, reproducible literature searches.
Subtopics:
Identifying relevant databases (PubMed, Embase, Cochrane, Scopus, etc.).
Developing effective search strategies and Boolean operators.
Grey literature searching and managing publication bias.
Screening studies: title, abstract, and full-text review.
Using reference management tools (EndNote, Zotero, Mendeley).
Documenting and reporting the search process (PRISMA flow diagram).

Module 4: Data Extraction and Quality Assessment
Objective: Extract relevant data accurately and assess the methodological quality of studies.
Subtopics:
Designing standardized data extraction forms.
Extracting key variables and outcomes from studies.
Assessing study quality using tools (e.g., Cochrane Risk of Bias, Newcastle-Ottawa Scale).
Handling missing or incomplete data.
Ensuring inter-rater reliability and consistency in data extraction.

Module 5: Data Synthesis, Meta-Analysis, and Reporting
Objective: Synthesize evidence and report findings according to best practices.
Subtopics:
Introduction to qualitative (narrative) synthesis.
Quantitative synthesis (meta-analysis) basics.
Fixed-effect vs. random-effects models.
Calculating effect sizes (risk ratios, odds ratios, mean differences).
Assessing heterogeneity (I² statistic, Chi-square test).
Evaluating publication bias (funnel plots, Egger’s test).
Using statistical software for meta-analysis (RevMan, Stata, R).
Reporting findings according to PRISMA guidelines.
Interpreting results for clinical and policy decision-making.
Presenting results in tables, forest plots, and graphs