Nursing Educators' Perceptions of AI in Research: Risks and Benefits

Area of Science:

• Nursing Research
• Artificial Intelligence
• Health Informatics

Background:

• The integration of Artificial Intelligence (AI) into nursing research is expanding, improving efficiency and objectivity.
• However, this growth is accompanied by significant concerns regarding potential liabilities and maintaining scientific integrity.

Purpose of the Study:

• To investigate the factors influencing nursing educators' perceptions of the risks and benefits associated with utilizing AI in nursing research.
• To identify differences in these perceptions among nursing educators based on demographic and professional characteristics.

Main Methods:

• A cross-sectional survey was conducted with 311 nursing educators from diverse university settings.
• Data analysis involved exploring predictors of AI perception and examining differences based on age, academic rank, and teaching experience.

Main Results:

• Key perceived risks included liability, unregulated standards, and communication barriers, while benefits centered on cost reduction and improved outcomes.
• Marital status, age, education level, academic rank, and teaching experience were significant predictors of AI perception in nursing research.
• Significant differences in AI adoption were observed based on educators' age, academic rank, and teaching experience.

Conclusions:

• Nursing educators acknowledge both the advantages and disadvantages of employing AI in research.
• Implementing tailored training programs and robust institutional support is crucial for the responsible integration of AI.
• Addressing these challenges will enable nursing research to thrive in the evolving digital landscape, equipping educators to critically engage with AI tools.