Nelson M Bryant
Midwestern University, USA.
Abstract Title: AI and Digital Metamorphosis in Advanced Practice Nursing Curricula
Biography:
Nelson McNova Bryant, PhD, MSN, MBA, FNP, is an Assistant Professor and Graduate Nursing Program Administrator at Midwestern University with 18 years of academic and clinical leadership experience. A board certified Family Nurse Practitioner, he integrates expertise in health sciences, informatics, business, and human rights to advance nursing education and clinical practice. His background includes clinical director roles, faculty appointments across several institutions, and service as a clinical investigator for the Arizona Department of Economic Security. He has practiced in diverse healthcare settings and is committed to using technology and research to improve education, healthcare delivery, and outcomes for underserved populations.
Research Interest:
The nursing field is rapidly transforming through advances in artificial intelligence and high fidelity simulation, creating pressure for advanced practice nursing (APN) education to evolve amid faculty and clinical site shortages. Although AI offers new educational opportunities, its use in APN programs is still limited and requires stronger evidence to demonstrate true effectiveness rather than relying on enthusiasm. The systematic review and meta-analysis synthesized peer-reviewed evidence regarding the efficacy, challenges, and opportunities of incorporating AI-driven modalities into graduate nursing curricula. The review used a systematic search across major databases (MEDLINE via PubMed, Web of Science, Cochrane Library, EMBASE, EBSCO) from 2017–2025, focusing on RCTs and quasi experimental studies that applied AI in advanced practice nursing education. It followed PRISMA guidelines and evaluated study quality using the Cochrane RoB 2 tool and the Newcastle Ottawa Scale. A database search identified 1,450 studies, with 13 meeting inclusion criteria (n=9 RCTs, n=3 quasi-experimental studies). Across an aggregate sample (N=1,525), AI enhanced simulations significantly improved clinical reasoning scores compared to traditional methods (methods (Standardized Mean Difference = 0.65, 95% CI [0.42, 0.88], p <.001), though results varied widely (I2 = 72%). Qualitative findings noted challenges such as algorithmic bias, high costs, and faculty skepticism. The integration of AI in APN education demonstrates a validated, moderate-to-strong positive effect on cognitive skill acquisition and procedural safety. However, the adoption is slowed by issues such as algorithmic bias and limited faculty preparedness. A balanced model that integrates technological precision with human centered mentorship is essential for future progress.
Keywords: Artificial Intelligence, Virtual Reality, Advanced Practice Nursing, Graduate Nursing Curricula, Digital Metamorphosis