Attitudes and future perspectives of Artificial Intelligence usage among nurses in Family Health Centers
- VernacularTitle:Өрхийн эрүүл мэндийн төвийн сувилагч нарын ai хэрэглээний хандлага ба хэтийн төлөв
- Author:
Dondoosuren Lkhagvajav
1
;
Davaajav Rina
2
;
Tsolmon Tumurtogoo
1
Author Information
1. School of Nursing, International of Ulaanbaatar University, Ulaanbaatar, Mongolia
2. Department of Nursing, Mongolian University of Pharmaceutical Sciences, Ulaanbaatar, Mongolia
- Publication Type:Journal Article
- Keywords:
artificial intelligence;
nursing technology readiness;
digital transformation barriers;
family health center;
work experience;
digital divide
- From:
Mongolian Pharmacy and Pharmacology
2026;29(2):82-87
- CountryMongolia
- Language:Mongolian
-
Abstract:
Introduction:The rapid advancement of Artificial Intelligence (AI) is redefining healthcare delivery, offering
significant potential to optimize nursing workflows and minimize administrative burdens in primary care settings. Family Health Centers (FHC) represent the front line of the healthcare system, yet the integration of AI within these facilities remains complex due to varying levels of professional experience and digital literacy among nursing staff. This study was initiated to comprehensively evaluate the current attitudes, future expectations, and perceived structural barriers toward AI adoption among FHC nurses. Furthermore, the research utilizes Marc Prensky’s generational theory to investigate the “digital divide” between different cohorts of healthcare professionals, aiming to provide a theoretical basis for future digital health strategies in community-based nursing.
Methods:A cross-sectional analytical study design was employed, involving a representative sample of 205
nurses currently practicing in various Family Health Centers. To ensure statistical power and validity, the minimum required sample size was calculated using G*Power 3.1 software. Data collection was facilitated through a meticulously structured questionnaire designed to capture demographic variables, technological readiness, and specific barriers. All quantitative data were processed and analyzed using IBM SPSS version 25.0. The analytical framework included Chi-square tests for categorical variables and Haberman’s adjusted standardized residual (AR) analysis to identify statistically significant patterns in attitudes across different career stages, ensuring a rigorous evaluation of the research hypotheses.
Conclusion:The comprehensive analysis confirms that nurses in Family Health Centers demonstrate a
predominantly positive and proactive attitude toward AI integration, with a strong emphasis on utilizing these technologies for clinical decision support and patient monitoring. A critical finding of the research is the significant correlation between professional experience and perceived obstacles (p=0.011); while younger “Digital Native” nurses identify infrastructural limitations as primary barriers, experienced “Digital (AR=2.8). Despite these challenges, the remarkably low level of technological distrust (3.9%) suggests a high psychological readiness for digital transformation. To facilitate successful adoption, it is concluded that healthcare organizations must implement tailored digital literacy programs that address the specific needs of each generation, alongside strategic investments in digital infrastructure and nursing curricula.
- Full text:2026080202240422570MPPJ-2026-29(2)-82-87.pdf
