Digital competence and AI readiness among nurses: lessons for public health workforce training
Abstract
Background: Digital transformation is changing workforce competencies. Nurses are relevant because digital systems are embedded in care, documentation, patient communication, prevention, and public health functions. This contribution synthesises evidence on nurses’ digital competence and AI readiness for training.
Methods: We conducted cross-sectional online and telephone surveys and related analyses among nurses in Poland. Samples were broad and structured to reflect the nursing workforce, not one institution. Digital competence was assessed with a nursing-specific questionnaire, digital health literacy with a validated scale, and AI readiness through attitude scales and task-specific items. Psychometric, comparative, and regression results were reviewed to identify training-relevant patterns.
Results: Digital competence emerged as a broad professional capability that combines system use, information handling, communication, and safe work with data. Digital health literacy was related to digital competence, suggesting that appraisal and use of digital health information are central to preparedness. Workplace exposure to digital tools also mattered, while broad sociodemographic and institutional categories had limited explanatory value. AI readiness was not reducible to digital familiarity: nurses distinguished among supportive uses, applications with higher autonomy, stronger implications for responsibility, and greater risk. Technological dependence concerns indicated that competence may increase critical awareness rather than simple acceptance.
Conclusions: Training for digital health should combine clinical systems, digital health literacy, data protection, workflow awareness, and patient communication. AI-related training should cover realistic capabilities and limits, human oversight, safety, accountability, and governance. Evidence from nursing helps translate competency frameworks into role-sensitive priorities for the health and public health workforce.
Related
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BibTeX
@article{wojcieszko2026digital,
title = {{Digital competence and AI readiness among nurses: lessons for public health workforce training}},
author = {M Wojcieszko and S Jakubowski and P Smoła and M Duplaga},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.501},
url = {https://doi.org/10.1093/eurpub/ckag169.501},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Digital competence and AI readiness among nurses: lessons for public health workforce training
AU - M Wojcieszko
AU - S Jakubowski
AU - P Smoła
AU - M Duplaga
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.501
UR - https://doi.org/10.1093/eurpub/ckag169.501
AB - Background: Digital transformation is changing workforce competencies. Nurses are relevant because digital systems are embedded in care, documentation, patient communication, prevention, and public health functions. This contribution synthesises evidence on nurses’ digital competence and AI readiness for training. Methods: We conducted cross-sectional online and telephone surveys and related analyses among nurses in Poland. Samples were broad and structured to reflect the nursing workforce, not one institution. Digital competence was assessed with a nursing-specific questionnaire, digital health literacy with a validated scale, and AI readiness through attitude scales and task-specific items. Psychometric, comparative, and regression results were reviewed to identify training-relevant patterns. Results: Digital competence emerged as a broad professional capability that combines system use, information handling, communication, and safe work with data. Digital health literacy was related to digital competence, suggesting that appraisal and use of digital health information are central to preparedness. Workplace exposure to digital tools also mattered, while broad sociodemographic and institutional categories had limited explanatory value. AI readiness was not reducible to digital familiarity: nurses distinguished among supportive uses, applications with higher autonomy, stronger implications for responsibility, and greater risk. Technological dependence concerns indicated that competence may increase critical awareness rather than simple acceptance. Conclusions: Training for digital health should combine clinical systems, digital health literacy, data protection, workflow awareness, and patient communication. AI-related training should cover realistic capabilities and limits, human oversight, safety, accountability, and governance. Evidence from nursing helps translate competency frameworks into role-sensitive priorities for the health and public health workforce.
SN - 1101-1262
SN - 1464-360X
ER -