Guideline-informed AI chat associated with lower mental effort, task difficulty, and higher confidence among home-visit nurses

Home-visit nurses often make autonomous clinical judgments in patients’ homes, where access to colleagues and evidence-based resources is limited. While guideline-informed artificial intelligence (AI) systems may facilitate access to clinical information, evidence of their effects on nurses’ perceived mental effort remains limited. In an Osaka Metropolitan University-led study, researchers examined whether access to a guideline-informed AI chat system was associated with perceived mental effort, task difficulty, and confidence in answer correctness during a simulated home-visit nursing task.

In a web-based randomized controlled trial, home-visit nurses were randomly allocated 1:1 to AI or non-AI groups, with both groups completing a simulated task involving an older adult with chronic heart failure living alone. The AI group was able to use a NotebookLM system preloaded with publicly available clinical guidelines for the task, whereas the comparison (non-AI) group was instructed not to use external resources.

Of the 140 randomized participants in the trial, 105 completed the task and were included in the complete-case analysis: 53 in the non-AI group and 52 in the AI group. The results of the trial revealed that when compared with the non-AI group, the AI group reported lower perceived mental effort, lower perceived task difficulty, and higher confidence in answer correctness.

As this study neither isolated the independent effect of AI nor evaluated clinical reasoning quality, accuracy, or safety, future research should compare AI-mediated access with conventional access to the same guideline materials and examine the quality of AI-supported reasoning, risks of overconfidence, and implementation of guideline-informed AI systems in real-world home-visit nursing practices.

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