Transformative role of artificial intelligence in promoting nurses’ mental resilience and quality of care delivery: from burden to balance

Authors

  • Swati Sharma Department of Mental Health Nursing, M. M. Institute of Nursing and Research, MMU, Ambala, Haryana, India
  • Pritika Department of Mental Health Nursing, ESIC College of Nursing, Indiranagar, Bangalore, Karnataka, India
  • Pradhyumn Kumar Department of Child Health Nursing, Arihant College of Nursing, HNBMU, Haridwar, Uttarakhand, India
  • Phanindrareddy Badduri Department of Child Health Nursing, Dr. Anjireddy College of Nursing, Piduguralla, Andhra Pradesh, India
  • Sivakumar Anusha Department of Mental Health Nursing, Aditya College of Nursing, RGUHS Bangalore, Karnataka, India
  • Prerna Lucas Department of Mental Health Nursing, Adeshwar Nursing Institute, Pandit Deendayal Upadhyay Memorial Health Sciences and Ayush University, Jagdalpur, Raipur, Chhattisgarh, India
  • Vijayaraddi Vandali Department of Medical Surgical Nursing, Shree Gopaldev Jadhav College of Nursing, RGUHS, Kalaburagi, Karnataka, India
  • Surekha Appireddygari Department of Medical Surgical Nursing, SEA College of Nursing, RGUHS, Bangalore, Karnataka, India
  • N. Prabha Department of Medical Surgical Nursing, Karuna College of Nursing, Kerala University of Health Sciences, Palakkad, Kerala, India
  • S. Tongpangkokla Ozukum Department of Child Health Nursing, IMDH College of Nursing, Mokokchung, Nagaland, India
  • Saravanan S. Department of Mental Health Nursing, Sri Gokulam College of Nursing, Dr. M.G.R. Medical University, TN, India
  • Mohammed Umar Department of Mental Health Nursing, Sri Gokulam College of Nursing, Dr. M.G.R. Medical University, TN, India

DOI:

https://doi.org/10.18203/2320-6012.ijrms20254386

Keywords:

Quality of care, Digital transformation, Burnout prevention, Simulation training, Artificial intelligence, Nursing resilience, Affective computing, Predictive analytics

Abstract

The transformative integration of artificial intelligence (AI) in nursing practice has emerged as a crucial innovation to mitigate occupational stress, enhance psychological resilience, and improve the overall quality of care delivery. As healthcare systems face mounting workloads, AI-driven technologies-such as machine learning, affective computing, and predictive analytics-offer meaningful pathways to achieve a balance between technological precision and human compassion. This systematic review critically synthesizes global evidence on AI’s role in promoting nurses’ mental resilience and optimizing patient-centered care outcomes. Following PRISMA 2020 and Joanna Briggs institute (JBI) guidelines, five major electronic databases-PubMed, Scopus, CINAHL, Web of Science, and Cochrane Library-were systematically searched for studies published between 2014 and 2024. A total of 78 studies met the inclusion criteria after rigorous screening, quality appraisal, and ROBINS-I/CASP bias assessment. Thematic and quantitative analyses revealed that AI interventions resulted in an average 28-35% improvement in resilience and a 22-32% enhancement in care quality. Among intervention types, simulation-based AI and affective computing yielded the highest combined benefits, while automation and predictive analytics consistently enhanced operational efficiency. Additionally, governance frameworks contributed indirectly to fostering ethical confidence and long-term trust in AI adoption. Overall, the findings underscore AI’s transformative potential in harmonizing innovation with empathy, empowering nurses toward sustainable well-being and professional excellence. When implemented responsibly, AI redefines modern nursing-from burden to balance-anchored in emotional intelligence, ethical stewardship, and evidence-based precision.

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Published

2025-12-30

How to Cite

Sharma, S., Pritika, Kumar, P., Badduri, P., Anusha, S., Lucas, P., Vandali, V., Appireddygari, S., Prabha, N., Tongpangkokla Ozukum, S., S., S., & Umar, M. (2025). Transformative role of artificial intelligence in promoting nurses’ mental resilience and quality of care delivery: from burden to balance. International Journal of Research in Medical Sciences, 14(1), 226–241. https://doi.org/10.18203/2320-6012.ijrms20254386

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Section

Systematic Reviews