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

TL;DR

Nursing educators see both benefits and risks in using AI for research, with factors like age and experience influencing their perceptions.

Contribution

The study identifies key predictors of nursing educators' perceptions of AI in research and highlights demographic differences.

Findings

High perceived risks include liability, unregulated standards, and communication barriers.

Perceived benefits include reduced costs and improved outcomes.

Age, academic rank, and teaching experience significantly influence perceptions of AI use.

Abstract

The application of AI in nursing research is increasing, enhancing objectivity and productivity while raising concerns about liability and scientific integrity.

To explore predictors and differences in nursing educators’ perceptions of the risks and benefits of using AI in nursing research.

A cross‐sectional study surveyed 311 nursing educators from various universities.

27% used ChatGPT, and 61.58% were from governmental universities. High perceived risks included liability (M = 3.78, SE = 0.036), unregulated standards (M = 3.76, SE = 0.035), and communication barriers (M = 3.74, SE = 0.036). Perceived benefits included reduced costs (M = 3.88, SE = 0.045) and improved outcomes (M = 3.81, SE = 0.045). Predictors included marital status (B = 7.67, p = 0.001), age (B = −14.65, p = 0.001), level of education (B = 13.80, p = 0.001), academic rank (B = −1.755, p = 0.001), and teaching experience (B = 2.793, p = 0.001). The model was significant (F (df = 7) = 86.82, p = 0.001, R
2 = 0.660) and explained 66.00% of the variance in the mean score of the perceived use of AI in nursing research. There are significant differences in nursing educators’ use of AI in nursing research based on their age (F‐test = 27.63, df = 4, p = 0.001), academic rank (F‐test = 60.79, df = 5, p = 0.001), and teaching experience (F‐test = 17.02, df = 4, p = 0.001).

Educators recognize both risks and benefits of AI in nursing research. Tailored training and institutional support are essential for responsible adoption. Tackling these issues can pave the way for nursing research to flourish in a rapidly changing digital world. Nursing educators need the tools they need to critically interact with AI in research.

The authors of this manuscript have adhered to the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) checklist, which was used to guide the study.

There was no patient or public contribution, as the sample included nursing educators from two governmental universities and one private university.

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