Design and Development of an Ethical AI Checklist for Nursing Researchers using 4D Instructional Design: A Concept Paper

Abstract

Introduction: The rapid integration of artificial intelligence (AI) in modern healthcare and academic environments presents notable, yet frequently underestimated, threats to academic integrity for nursing researchers. As AI tools become increasingly prevalent in conducting literature reviews, analysing data, and drafting manuscripts, the likelihood of accidental plagiarism, citation errors, and data mismanagement rises, particularly in the postgraduate fields. Although ethical guidelines for nursing research exist, there is a clear lack of practical, context-specific, and culturally sensitive tools to guide nursing researchers in AI applications. This concept paper outlines the development of an Ethical AI Checklist for nurse researchers. Materials and methods: The methodology uses the 4D Instructional Design model, which includes four sequential phases. The Define phase involved document analysis of international AI ethics frameworks and academic integrity policies, supplemented by focus group discussions (FGDs) with postgraduate students and supervisors to identify ethical challenges in AI use. The Design & Develop phase translated these findings into a structured checklist with four key domains: research planning, writing and authorship, data analysis, and mentorship. The checklist was iteratively refined through pilot testing for usability within postgraduate thesis workshops and institutional ethics seminars to ensure its practicality and cultural relevance. Results: The Ethical AI Checklist was the study output. This final checklist was disseminated into postgraduate supervision workflows and mandatory research ethics curriculum modules. Conclusion: This study presents an essential, evidence-based, and culturally informed approach to support ethical academic practices, protect academic integrity, and encourage the responsible application of AI in nursing studies.

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