From research ideas to publishable evidence.

Understand the research process and turn a problem into a research question.

You produceOne research question with rationale and a preliminary literature map.

• Research question development: topic → problem → gap → question
• PICO, PECO and other question frameworks
• Efficient literature searching
• Primary versus secondary research
• Observational versus experimental designs, and choosing the right study design
• Research ethics, plagiarism, authorship and publication ethics
• Introduction to PubMed, Google Scholar, and Scopus and Web of Science concepts
• Reference management: Zotero and Mendeley basics
• Introduction to Excel and R for research

Write and submit a concise scholarly response.

You produceA submission-ready letter based on a published article.

• Finding suitable topics: recent papers, controversies, methodological concerns and important findings
• Types of letter: commentary, critique, clarification and brief scientific response
• Reading a target article critically
• Structure: opening context → key point → evidence → interpretation → closing
• Keeping the argument focused and evidence-based
• References and citation style
• Finding suitable journals: scope, article types, word limits and submission requirements
• Cover letter and submission checklist
• Common reasons letters are rejected

Synthesize literature and write a structured review.

You produceA complete narrative review manuscript outline with selected written sections.

• Topic selection and scope control: broad topic versus focused review question
• Building a literature search strategy
• Organizing evidence into themes
• Introduction and rationale
• Main body: thematic synthesis rather than article-by-article summary
• Critical interpretation and identification of gaps
• Conclusion and future directions
• Citation management and avoiding citation dumping
• Tables, figures and conceptual frameworks
• Choosing a target journal and following author guidelines

Design, collect and analyze primary data.

You produceProtocol, questionnaire, sample-size calculation, analysis plan and manuscript draft.

• Choosing a feasible research question
• Defining the population, exposure and outcome variables
• Inclusion and exclusion criteria
• Questionnaire development: domains, item construction and response options
• Content validity, pilot testing and reliability concepts
• Sampling methods and sampling bias
• Sample-size calculation for prevalence and associations
• Data dictionary and coding plan
• Ethics approval, consent and data-collection workflow
• Data cleaning and missing-data checks
• Descriptive statistics and appropriate inferential tests
• Effect measures and confidence intervals
• Writing the Introduction, Methods, Results and Discussion
• Reporting with the appropriate reporting guideline

Perform descriptive, inferential and regression analyses.

You produceAn analysis report with tables, figures, statistical tests and interpretation.

• Data structure and variable types
• Data cleaning and quality checks
• Descriptive analysis: mean and SD, median and IQR, proportions and distributions
• Normality and graphical exploration
• Choosing inferential tests based on the question and the data
• t-test, Mann–Whitney U, ANOVA and Kruskal–Wallis
• Chi-square and Fisher's exact test
• Correlation
• Effect sizes and confidence intervals
• Confounding, and why association is not causation
• Linear and logistic regression
• Model interpretation, assumptions, diagnostics and common errors
• Reproducible analysis in R

Complete an evidence synthesis from protocol to manuscript.

You produceA complete mini systematic review and meta-analysis, from search strategy to manuscript.

• Topic selection, feasibility and a focused review question
• Protocol development and registration concepts
• Search-string generation: keywords, synonyms, MeSH and other controlled vocabulary, and Boolean operators
• Database searching, deduplication and screening
• Title and abstract screening versus full-text screening; inclusion and exclusion criteria
• PRISMA flow diagram
• Data-extraction sheet design
• Risk-of-bias assessment by study design
• Effect measures: RR, OR, MD, SMD, HR and others
• Fixed-effect versus random-effects models
• Heterogeneity and I²; forest plots
• Subgroup and sensitivity analyses
• Publication bias and funnel plots
• Certainty of evidence and GRADE
• Manuscript writing and PRISMA reporting

Apply meta-regression, prevalence, DTA and TSA methods.

You produceOne advanced analysis project using a real evidence-synthesis dataset.

• Meta-regression: rationale, moderators and interpretation
• Prevalence meta-analysis
• Zero-event studies and sparse data
• Diagnostic test accuracy meta-analysis: sensitivity, specificity and hierarchical models
• Trial Sequential Analysis: information size, monitoring boundaries and interpretation
• Advanced sensitivity analyses
• Clinical and methodological heterogeneity
• Avoiding over-interpretation of advanced analyses

Use CDC and GBD datasets for population-level research.

You produceOne reproducible CDC- or GBD-based research proposal and analysis.

• Introduction to large public-health databases
• CDC data sources and identifying appropriate datasets
• Variable definitions, population and time-period awareness
• Downloading and preparing public-health data
• Descriptive epidemiology using surveillance data; trends over time and stratified analyses
• Global Burden of Disease (GBD) concepts
• Incidence, prevalence, mortality, YLDs, YLLs and DALYs
• Age-standardized rates and their interpretation
• Location, year, sex, age and cause dimensions
• Developing research questions from GBD data
• Visualizing and presenting population-level findings
• Limitations of secondary datasets and ecological analyses

Write, submit and revise manuscripts to publication standard.

You produceA polished manuscript, a journal-selection rationale and a complete submission package.

• Writing a strong title and abstract
• Introduction: background → gap → objective
• Methods: enough detail for reproducibility
• Results: report without over-interpreting
• Discussion: principal findings → comparison → explanation → implications → limitations
• Tables and figures
• References and citation accuracy
• Reporting guidelines and checklists
• Journal selection, and recognizing predatory journals
• Cover letters
• Responding to reviewers, revision and resubmission