Research Integrity, Plagiarism, and the AI Era: A Narrative Review for Nursing Faculty Development in India

Abstract

Background: Research integrity in Indian nursing is under strain like never before. Retractions of papers with Indian affiliations have risen sharply since 2019, predatory publishing has boomed, and the rapid uptake of generative Artificial Intelligence (AI) since November 2022 has unsettled long-standing norms of authorship, originality and honest scholarship. Nursing faculty must educate the next generation of researchers under the University Grants Commission (UGC), Indian Council of Medical Research (ICMR), Indian Nursing Council (INC) and National Medical Commission (NMC) mandates, yet many lack formal training in publication ethics.

Objective: To merge current evidence and policy on research integrity, plagiarism and AI-assisted writing, and to translate this into a Faculty Development Programme (FDP) framework for nursing faculty in India.

Methods: Narrative review of PubMed, Scopus, Google Scholar, ERIC, IndMED and ProQuest (January 2018 to April 2026), supplemented from regulatory bodies and integrity organisations, specifically UGC, ICMR, INC, NMC, COPE, ICMJE, WAME and the World Conferences on Research Integrity Foundation.

Findings: ICMR’s 2017 guidelines converge on four pillars: honesty, accountability, professionalism and stewardship. The UGC Plagiarism Regulations 2018 set graded penalties and require institutional integrity panels. Detection tools vary widely in coverage, cost and regional fit. AI tools cannot be authors under any major journal policy, and AI text detectors are unreliable for Indian and other non-native English writers. Indian retractions are driven by plagiarism, fake peer review and ethical violations.

Conclusion: Building research integrity in Indian nursing requires structured FDPs, hands-on training with detection tools, transparent AI-use disclosure, mentorship, and institutional infrastructure for reporting and adjudication.