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About
The Research Integrity – Professional Standards, Plagiarism and Peer Review Course is designed to provide a comprehensive understanding of ethical research practices, professional standards, and the principles that underpin trust and credibility in scholarly work. It emphasizes the importance of integrity throughout the research lifecycle, from study design and data collection to publication and peer evaluation.
This course covers key areas including responsible conduct of research, research ethics, authorship and contributorship, plagiarism prevention, proper citation and referencing practices, data management, conflicts of interest, publication ethics, and the peer review process. It also highlights strategies for identifying and addressing research misconduct, maintaining transparency, and promoting accountability in academic and professional research environments. Upon completion, learners receive a certification demonstrating competency in research integrity and ethical scholarly practices.
- Researchers and Research Associates
- Graduate and Postgraduate Students
- Academic Faculty and Educators
- Medical, Pharmacy, and Life Science Professionals
- Clinical Research and Regulatory Professionals
- Scientific Writers and Publication Professionals
- Peer Reviewers and Journal Editorial Staff
- Anyone involved in research, publication, or academic activities
What you will learn
Understand the foundations of research integrity, including ethical principles, responsible conduct of research, professional standards, and the importance of transparency and accountability.
Gain knowledge of plagiarism prevention, proper citation and referencing practices, authorship responsibilities, intellectual property considerations, and publication ethics.
Learn the principles of data integrity, research documentation, conflict of interest management, ethical decision-making, and approaches to identifying and preventing research misconduct.
Develop expertise in the peer review process, reviewer responsibilities, manuscript evaluation, ethical publishing practices, and fostering a culture of integrity in research environments.
Course Syllabus
- What is research integrity?
- FFP — defining misconduct
- Questionable research practices
- Data stewardship in practice
- Professional standards
- The integrity ecosystem
- Roles + responsibilities
- Anatomy of a slippery slope
- Reproducibility by design
- Singapore Statement in depth
- Helsinki essentials
- Singapore Statement
- ALLEA code in practice
- National systems compared
- ICMJE + publication rules
- Decision framework for grey areas
- ICMJE criteria, applied
- Authorship abuses
- ICMJE four criteria
- CRediT taxonomy
- Order, roles + disputes
- What is plagiarism?
- Types of plagiarism
- Text recycling rules
- Self-plagiarism
- Citation + paraphrasing
- Attribution beyond text
- AI in research writing
- What LLMs actually do
- Confidentiality + IP risks
- Integrity risks of AI
- Tortured phrases + mills
- Detection reality check
- Why peer review matters
- Reviewer responsibilities
- Anatomy of a good review
- Types of peer review
- Reviewing with AI — rules
- Threats to the record
- The retraction landscape
- Inside paper mills
- Paper mills + predators
- Post-publication scrutiny
Course Benefits
Gain Continuing Professional Development (CPD) Points accredited by The Faculty of Pharmaceutical Medicine of the Royal College of Physicians of the United Kingdom, usable towards the distance-learning element of relevant schemes.
Receive a Whitehall Training certificate on passing the final assessment, evidencing your competence for audits, appraisals and CVs.
Learn through real-world case studies, decision frameworks and checklists you can apply immediately in your own research environment.
Study anytime, anywhere, at your own pace, with bite-sized modules and built-in knowledge checks.
Material aligned to recognised international standards and codes, written and reviewed to a professional, practitioner-grade level.
Reinforce learning with per-module knowledge checks and a final scenario-based assessment.



