Joint latent profile analysis of artificial intelligence literacy and critical thinking among clinical nurses and their association with evidence-based decision-making capacity: A cross-sectional study

In the modern hospital, a nurse's mind is a busy intersection where patient needs, medical guidelines, and complex technology constantly collide. For decades, the gold standard of care has been evidence-based practice: the ability to find the best scientific research, weigh it against a specific patient's unique history, and make a decision that saves lives. Today, a new force has entered this intersection: artificial intelligence. These tools can instantly retrieve medical literature, draft patient records, and flag potential risks, offering a powerful shortcut through the mountains of data nurses face every day. However, this speed comes with a catch. Because these systems are trained on past data, they can sometimes produce answers that are factually wrong, biased, or simply mismatched to a patient's current reality. The critical question for the future of nursing is no longer just whether nurses can use these tools, but how they think while using them. It requires a balance between knowing how to operate the machine and possessing the sharp, independent judgment to know when the machine is wrong.

A recent study involving over 2,300 registered nurses across eight hospitals in China sought to understand exactly how these two skills—technical fluency with artificial intelligence and the ability to think critically—work together in the real world. Rather than treating these as separate checklists, the researchers looked at how they combine within individual nurses. They used a statistical method to group nurses based on their actual scores in both areas, revealing that the workforce is not a single, uniform group. Instead, they found four distinct types of nurses, each with a different mix of strengths and weaknesses that directly impacts their ability to make safe, high-quality decisions for patients.

The study identified four clear profiles. The first group, making up about 22 percent of the nurses, struggled with both skills. These nurses had low confidence and ability in using artificial intelligence tools and also lacked strong critical thinking habits. They represent a high-risk group that may find it difficult to navigate the digital tools of modern nursing or to question the information those tools provide. A second, larger group, comprising roughly 36 percent of the nurses, showed a different pattern: they possessed strong critical thinking skills but had low literacy with artificial intelligence. These nurses could analyze a problem well but lacked the digital tools to find evidence quickly, forcing them to rely on slower, manual methods that consume mental energy.

The third group, representing about 21 percent of the participants, appeared to be the most proficient on the surface. These nurses had high scores in artificial intelligence literacy; they could operate the tools efficiently and retrieve information rapidly. However, their critical thinking skills were only average. The researchers flagged this group as a "hidden risk." Because they are so comfortable with the technology, they might trust the machine's output too readily, failing to spot errors or biases in the generated advice. They are the nurses who might follow a computer's recommendation without asking if it truly fits the patient in front of them. The final group, making up the remaining 21 percent, possessed both high artificial intelligence literacy and high critical thinking skills. These nurses could use the technology to speed up their work while simultaneously using their sharp minds to verify the results, ensuring the final care plan was both efficient and accurate.

When the researchers compared these groups to their actual ability to make evidence-informed decisions, a clear hierarchy emerged. The nurses who were strong in both areas performed the best. Notably, the group with high technical skills but only average critical thinking performed better than the group with low technical skills but high critical thinking. This suggests that while being good at using the tool is important, it is not the only factor; the combination of technical fluency and critical judgment creates a distinct advantage, though the "hidden risk" group still faces challenges in fully optimizing their decision-making compared to the dual-high performers. The study found that the combination of these two skills explained nearly 30 percent of the differences in decision-making quality among the nurses, a significant factor that cannot be ignored.

The findings also pointed to what helps nurses develop these skills. Nurses who received specific training on artificial intelligence were more likely to belong to the high-performing group. Similarly, those who used these tools regularly in their daily work tended to have better skills, but only if they also engaged in critical reflection. The study noted that simply using the tools often was not enough; without training that encouraged questioning and verification, frequent use could actually lead to the dangerous "hidden risk" profile where nurses rely too heavily on the machine. The research suggests that hospitals need to move beyond basic technical training. Instead, they must teach nurses how to use these powerful tools while maintaining a skeptical, analytical eye, ensuring that the human mind remains the final authority in patient care.