ArticleFrontiers in medicine2026
Artificial intelligence readiness and its influencing factors among newly qualified nurses: a cross-sectional study.
Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Exploring factors associated with nursing students' artificial intelligence literacy: insights from a national mixed methods study.BMC nursing · 2026Article
- Artificial intelligence readiness and its relationship with thriving at work among Chinese nurses: a latent profile analysis.Frontiers in public health · 2026Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: This study investigated the artificial intelligence (AI) readiness of newly qualified nurses and identified potential influencing factors. The technology acceptance model was extended by including perceived barriers to provide a comprehensive understanding of AI adoption in clinical practice. Methods: This cross-sectional study was conducted across four tertiary grade A hospitals in Shandong Province in August and September 2022. Using convenience sampling, 329 newly qualified nurses with 1-3 years of clinical experience were surveyed. Data were collected using several instruments: a demographic characteristics questionnaire, the Readiness to Adopt AI in Nursing Practice Scale, the Perceived Usefulness in Nursing Practice Scale, the Perceived Ease of Use in Nursing Practice Scale, and the Perceived Barriers to Accessing AI Technology Scale. Data analysis, including descriptive statistics, correlation analysis, and multiple linear regression, was performed using SPSS 27.0. Results: Newly qualified nurses' AI readiness was moderate (M = 9.85, SD = 1.97). Multiple linear regression identified three significant factors associated with AI readiness: perceived ease of use ( Discussion: The readiness of newly qualified nurses for AI is influenced by multiple factors. Awareness of AI plays a crucial role, in addition to perceived ease of use and prior AI training. Although perceived barriers did not show a significant relationship with readiness, practical challenges, such as knowledge gaps and limited computer skills, require attention. Enhancing AI training, improving system usability, and ensuring adequate time and resource support are essential to strengthen AI application capabilities among newly qualified nurses.
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