# Postgraduate students’ perceptions of artificial intelligence integration in research: A cross-sectional study

## TL;DR

This study explores how postgraduate nursing and health students in Saudi Arabia perceive the use of AI in research, finding that they are generally optimistic but also concerned about privacy and ethics.

## Contribution

The study provides new insights into AI perceptions among non-Western health-professional students, highlighting unique predictors of AI adoption intention.

## Key findings

- Perceived benefits were the strongest predictor of AI adoption intention (β = 0.588, p < 0.001).
- Female students reported higher adoption intention than males (β = 0.137, p = 0.002).
- Privacy concerns were positively associated with adoption intention (β = 0.230, p < 0.001).

## Abstract

Generative artificial intelligence (AI) tools such as ChatGPT are increasingly used in academic research, yet evidence on postgraduate students’ perceptions remains limited in non-Western and health-professional contexts. Understanding how students perceive AI’s benefits, risks, and ethical implications is essential for informing institutional research policies.

This cross-sectional case study surveyed 267 master’s students enrolled in nursing and health profession programs at Northern Border University in Arar, Saudi Arabia. Data were collected between October 1 and November 15, 2025, using a validated 54-item questionnaire that assessed perceived benefits, perceived risks, privacy concerns, mistrust in AI, performance anxiety, social bias, regulatory matters, liability issues, and intention to adopt AI tools. Multiple linear regression with heteroscedasticity-robust (HC3) standard errors was used to identify predictors of AI adoption intention.

Most participants (85.0%) reported prior use of AI tools, predominantly ChatGPT. Perceived benefits were the strongest predictor of intention to adopt AI for research purposes (β = 0.588, p < 0.001). Privacy concerns were positively associated with adoption intention (β = 0.230, p < 0.001), suggesting informed and critical engagement rather than resistance. Female students reported higher adoption intention than males (β = 0.137, p = 0.002), while prior publication experience was negatively associated with intention (β = −0.089, p = 0.036). Demographic variables such as age, specialty, and marital status were not significant predictors. The adoption-intention model demonstrated moderate explanatory power (adjusted R2 = 0.560).

Among nursing and health profession master’s students at a regional Saudi university, findings indicate pragmatic optimism toward AI integration in academic research, driven primarily by perceived benefits alongside heightened ethical and privacy awareness. Privacy concerns appear to reflect critical literacy rather than barriers to adoption.