Comparative Assessment of Artificial Intelligence Readiness, Digital Competency, and Evidence-Based Nursing Practice Among Nurses Working in Public and Private Hospitals of Multan
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Background: Nurses require artificial intelligence readiness, digital competency, and evidence-based practice competency to engage effectively with technology-supported healthcare. Comparative evidence regarding these competencies across Pakistan’s public and private hospital sectors remains limited. Objective: To compare AI readiness, digital competency, and EBP competency among nurses working in public and private hospitals in Multan and to examine relationships among these competencies and perceived barriers. Methods: This comparative cross-sectional study included 340 registered nurses, with 170 participants from each hospital sector. Standardized 0–100 scores were derived from adapted AI-readiness, digital-competency, and EBP-competency instruments. Group differences were evaluated using independent-samples t-tests and chi-square tests, while relationships were examined using Pearson correlations. Results: Private-hospital nurses had higher AI-readiness scores than public-hospital nurses (72.4 ± 11.2 versus 61.8 ± 13.5; mean difference, 10.6; 95% CI, 8.0–13.2; d = 0.85), digital-competency scores (68.7 ± 10.8 versus 56.3 ± 14.1; mean difference, 12.4; 95% CI, 9.7–15.1; d = 0.99), and EBP-competency scores (65.9 ± 12.4 versus 54.7 ± 15.2; mean difference, 11.2; 95% CI, 8.2–14.2; d = 0.81). Digital competency correlated with AI readiness (r = 0.64) and EBP competency (r = 0.68), while AI readiness correlated with EBP competency (r = 0.52; all p < 0.001). Lack of training (85.9%), limited infrastructure (67.9%), and heavy workload (65.6%) were the most frequently reported barriers. Conclusion: Private-hospital nurses reported higher competency scores across all three domains. The observed relationships suggest that AI readiness, digital competency, and EBP competency are interconnected, although causal conclusions cannot be drawn
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1. Cachata D, Costa M, Magalhães T, Lucas P, Gaspar F. Information technology in nursing practice: a scoping review of assessment tools for evaluating nurses’ competencies. J Healthc Leadersh. 2025;17:211–223. doi:10.2147/JHL.S509955.
2. Al Omari O, Alshammari M, Al Jabri W, Al Yahyaei A, Aljohani KA, Sanad HM, et al. Demographic factors, knowledge, attitude and perception and their association with nursing students’ intention to use artificial intelligence: a multicentre survey across 10 Arab countries. BMC Med Educ. 2024;24:1456. doi:10.1186/s12909-024-06452-5.
3. Ye C, Hou D, Pikkarainen M, Chen B, Qin N, Lin S, et al. Exploring the status and influencing factors of nurses’ digital health literacy: a scoping review. BMC Nurs. 2026;25:371. doi:10.1186/s12912-026-04532-z.
4. Golz C, Hahn S, Zwakhalen SMG. Psychometric validation of the Digital Competence Questionnaire for nurses. SAGE Open Nurs. 2024;10:23779608241272641. doi:10.1177/23779608241272641.
5. Akçoban S, Koca G, Berşe S. Development of the Nursing Artificial Intelligence Readiness Scale for nursing students: a validity and reliability study. BMC Nurs. 2026. doi:10.1186/s12912-026-05054-4.
6. El-Bassal NAM, El-Sayed AAI, Elgamal HG. Empowering nurses in the AI era: investigating the interplay between professionalism, AI readiness, and self-efficacy. BMC Nurs. 2025;24:1287. doi:10.1186/s12912-025-03896-y.
7. Ruzafa-Martínez M, López-Iborra L, Moreno-Casbas T, Madrigal-Torres M. Development and validation of the competence in evidence-based practice questionnaire among nursing students. BMC Med Educ. 2013;13:19. doi:10.1186/1472-6920-13-19.
8. Atalla ADG, El-Ashry AM, Mohamed SMS. The relationship between evidence-based practices’ facilitators and barriers among nurses and their competencies: self-efficacy as a mediator. BMC Nurs. 2025;24:458. doi:10.1186/s12912-025-02896-2.
9. Ahmed Z, Kaladi IG, Rehan J, Chandio ZH, Zardari JA, Kumar A. Assessment of readiness and perception toward artificial intelligence integration in nursing education: a quantitative study in Sindh, Pakistan. NURSEARCHER. 2025;5(2):53–57. doi:10.54393/nrs.v5i2.175.
10. Naveed A, Chaudhry FA. Advancing healthcare delivery through artificial intelligence: a cross-sectional study from Pakistan. Turk J Physiother Rehabil. 2025;36(4):104. doi:10.21653/tjpr.2026.OP144.
11. Haq NU, Rahman A, Ahmad Z, Islam S, Rehman N, Gul T. Knowledge, attitudes, and practices of nurses regarding digital health in tertiary care hospitals of Peshawar, Pakistan. Front Med Health Res. 2025;3(5):1–11.
12. Bibi R, Khalid N, Shehzad F. Enhancing nursing competence through simulation-based training, evidence-based practice adoption, and patient safety culture: a study of hospitals in Sargodha, Punjab. Pak J Med Cardiol Rev. 2025;4(4):1610–1624.
13. Asal MGR, Alsenany SA, Elzohairy NW, El-Sayed AAI. The impact of digital competence on pedagogical innovation among nurse educators: the moderating role of artificial intelligence readiness. Nurse Educ Pract. 2025;85:104367. doi:10.1016/j.nepr.2025.104367.
14. Bulut A, Kasap RI, Yılmaz N. Reliability and validity of the Turkish version of the Digital Competence Questionnaire for nurses. BMC Nurs. 2025;24:1225. doi:10.1186/s12912-025-03052-6.