Nurse AI acceptance links to infection control competency

A multicentre cross-sectional study conducted in China has found that nurses’ self-reported infection control competency is more strongly associated with their perceived assistance and acceptance of AI-assisted tools than with the frequency of their actual usage. The research, published in Antimicrobial Resistance & Infection Control, examined the relationship between these variables among registered nurses, highlighting a distinction between how often tools are used and how they are perceived in a clinical context.

The study was motivated by the persistent global threat of hospital-acquired infections, for which nurses bear the majority of frontline prevention and control responsibilities. While AI-assisted tools offer new opportunities for infection control, the systematic relationship between their use and nursing competency had not previously been examined. The researchers aimed to investigate this link by focusing on usage frequency, perceived assistance, acceptance, and adoption patterns across different tasks.

To achieve this, the team conducted a multicentre cross-sectional survey using convenience sampling. The study included registered nurses from 18 hospitals located in 10 cities within Liaoning Province, China. Data collection took place between January and May 2025. Infection-control competency was measured using the ICCS-CN, while AI-assisted tool use and perceptions were assessed through a study-specific questionnaire. It is important to note that all measures in this study were self-reported by the participants.

The results indicated that the mean self-reported infection control competency score was 145.39, with a standard deviation of 22.48. Through statistical modeling, the researchers identified two distinct latent profiles among the nurses. The model-estimated proportions for these groups were 40.1% for moderate competence and 59.9% for high competence.

When analyzing the relationship between AI tool usage and competency, the study found that perceived assistance and acceptance were strongly associated with higher competency levels. In contrast, the frequency of usage showed a limited independent association with competency.

Furthermore, the analysis revealed a positive interaction effect, indicating that the association between perceived assistance/acceptance and competency was stronger at higher levels of usage.

Regarding specific applications, the study found that AI-assisted tools were most often used in outbreak management, case simulations, and emergency planning. Conversely, these tools were used less frequently in preparatory tasks.

The authors conclude that training on AI-assisted tools should emphasize calibrated trust, verification against authoritative guidelines, human oversight, and privacy protection.

Subject of Research: Association between AI tool acceptance and infection control competency among nurses

Article Title: Self-reported AI-assisted tool use, perceived assistance and acceptance, and infection control competency among nurses: a multicentre cross-sectional study

Article References: Fu, T., Zhang, L., & Zhang, X. (2026). Self-reported AI-assisted tool use, perceived assistance and acceptance, and infection control competency among nurses: a multicentre cross-sectional study. Antimicrobial Resistance & Infection Control. https://doi.org/10.1186/s13756-026-01861-1

Image Credits: AI Generated

DOI: 10.1186/s13756-026-01861-1

Keywords: infection control, AI-assisted tools, nursing competency, cross-sectional study, Liaoning Province, perceived assistance, hospital-acquired infections, outbreak management, case simulations, emergency planning, self-reported data, latent profiles, human oversight, privacy protection, calibrated trust, convenience sampling, ICCS-CN, Antimicrobial Resistance, clinical practice, nursing education