Academic Journal
Advancing Nursing Cognitive Capacity Through Generative AI and Immersive VR as a Structural Intervention for Burnout and Administrative Burden.
| Τίτλος: | Advancing Nursing Cognitive Capacity Through Generative AI and Immersive VR as a Structural Intervention for Burnout and Administrative Burden. |
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| Συγγραφείς: | Nnaka T; The University of North Texas Health Science Center at Fort Worth, College of Nursing, Fort Worth, Texas; and., McMahan T; The University of North Texas, College of Information, Denton, Texas., Teplitskiy N; The University of North Texas Health Science Center at Fort Worth, College of Nursing, Fort Worth, Texas; and., Arcuri S; The University of North Texas Health Science Center at Fort Worth, College of Nursing, Fort Worth, Texas; and., Akpan IN; The University of North Texas Health Science Center at Fort Worth, College of Nursing, Fort Worth, Texas; and., Farih N; The University of North Texas Health Science Center at Fort Worth, College of Nursing, Fort Worth, Texas; and., Brown E; The University of North Texas Health Science Center at Fort Worth, College of Nursing, Fort Worth, Texas; and., Macklin H; The University of North Texas Health Science Center at Fort Worth, College of Nursing, Fort Worth, Texas; and., Ahn C; The University of North Texas Health Science Center at Fort Worth, College of Nursing, Fort Worth, Texas; and., James J; The University of North Texas Health Science Center at Fort Worth, College of Nursing, Fort Worth, Texas; and., Sharma S; The University of North Texas, College of Information, Denton, Texas. |
| Πηγή: | Nursing administration quarterly [Nurs Adm Q] 2026 Oct-Dec 01; Vol. 50 (4), pp. 195-202. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 7703976 Publication Model: Print Cited Medium: Internet ISSN: 1550-5103 (Electronic) Linking ISSN: 03639568 NLM ISO Abbreviation: Nurs Adm Q Subsets: MEDLINE |
| Imprint Name(s): | Publication: 2003- : Hagerstown, MD : Lippincott Williams & Wilkins Original Publication: Germantown, Md., Aspen Systems Corp. |
| Ιατρικοί όροι (MeSH): | Burnout, Professional*/psychology , Burnout, Professional*/prevention & control , Artificial Intelligence*/trends , Brain-Computer Interfaces*/standards , Cognition*, Workload/psychology ; Workload/standards ; Humans ; Generative Artificial Intelligence |
| Περίληψη: | Nurses practice in clinical environments shaped by escalating administrative demands, documentation burdens, and persistent cognitive overload, structural pressures that contribute significantly to burnout and workforce attrition. Generative artificial intelligence (AI) offers a new form of cognitive support that, when implemented responsibly, can reduce the administrative load constraining nursing practice. We examine the early use of an in-house generative AI health assistant designed to predraft documentation and streamline communication. Rather than replacing clinical judgment, we position AI as a structural intervention that expands nurses' cognitive capacity and restores time for direct care and therapeutic engagement. We also explore the integration of electroencephalography data captured through brain-computer interface (BCI) devices such as Galea and EMOTIV headsets. This approach enables real-time insights into clinicians' cognitive workload and emotional states by translating neurophysiological signals into actionable information. By identifying neural indicators associated with stress, anxiety, and fatigue, the system can prompt timely supports as strain emerges. To ensure feasibility within clinical workflows, these wireless BCI systems are deployed during structured documentation periods and simulation-based training sessions. Combining neurotechnology, machine learning, and generative AI, this approach converts neural signals into meaningful insights that support clinician well-being while preserving professional integrity through nursing-led governance and safeguards. (Copyright © 2026 Wolters Kluwer Health, LLC. All rights reserved.) |
| Competing Interests: | The authors declare no conflicts of interest. |
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| Contributed Indexing: | Keywords: artificial intelligence; brain-computer interfaces; nursing clinical practice |
| Entry Date(s): | Date Created: 20260827 Date Completed: 20260827 Latest Revision: 20260827 |
| Update Code: | 20260828 |
| DOI: | 10.1097/NAQ.0000000000000773 |
| PMID: | 42659607 |
| Βάση Δεδομένων: | MEDLINE |
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