The effects of generative AI’s human-like competencies on clinical decision-making DOI Creative Commons
Niko Spatscheck,

Myriam Schaschek,

Axel Winkelmann

et al.

Journal of Decision System, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 39

Published: Dec. 13, 2024

Generative AI (genAI) has revolutionized clinical systems by leveraging human language. Yet, challenges remain in its integration into settings, particularly regarding the risk of physicians relying on hallucinated advice. We conducted an experimental study with 368 novice who diagnosed patient cases while being augmented genAI systems. A theoretical model was empirically tested to examine how anthropomorphism and advice elaboration affect trust cognitive load as mediators for appropriate reliance. Findings show that augmenting decisions can improve physicians' diagnostic accuracy but also frequently results inappropriate reliance due miscalibrated trust. Moreover, we emphasize uncanny familiarity evoked anthropomorphizing systems, which diminishes reducing load. Our findings highlight benefits ethical decision support, underscoring need balance advantages safeguarding integrity agency.

Language: Английский

Artificial intelligence in critical care nursing: A scoping review DOI
Yujin Park, Sun Ju Chang, Eunhye Kim

et al.

Australian Critical Care, Journal Year: 2025, Volume and Issue: 38(4), P. 101225 - 101225

Published: April 6, 2025

Language: Английский

Citations

1
Neonatal nurses’ experiences with generative AI in clinical decision-making: a qualitative exploration in high-risk nicus DOI Creative Commons
Abeer Nuwayfi Alruwaili, Afrah Madyan Alshammari,

Ali Alhaiti

et al.

BMC Nursing, Journal Year: 2025, Volume and Issue: 24(1)

Published: April 7, 2025

Neonatal nurses in high-risk Intensive Care Units (NICUs) navigate complex, time-sensitive clinical decisions where accuracy and judgment are critical. Generative artificial intelligence (AI) has emerged as a supportive tool, yet its integration raises concerns about impact on nurses' decision-making, professional autonomy, organizational workflows. This study explored how neonatal experience integrate generative AI examining influence nursing practice, dynamics, cultural adaptation Saudi Arabian NICUs. An interpretive phenomenological approach, guided by Complexity Science, Normalization Process Theory, Tanner's Clinical Judgment Model, was employed. A purposive sample of 33 participated semi-structured interviews focus groups. Thematic analysis used to code interpret data, supported an inter-rater reliability 0.88. Simple frequency counts were included illustrate the prevalence themes but not quantitative measures. Trustworthiness ensured through reflexive journaling, peer debriefing, member checking. Five emerged: (1) Decision-Making, 93.9% reported that AI-enhanced required human validation; (2) Professional Practice Transformation, with 84.8% noting evolving role boundaries workflow changes; (3) Organizational Factors, 97.0% emphasized necessity infrastructure, training, policy integration; (4) Cultural Influences, 87.9% highlighting AI's alignment family-centered care; (5) Implementation Challenges, 90.9% identified technical barriers strategies. can support effectiveness depends structured reliable culturally sensitive implementation. These findings provide evidence-based insights for policymakers healthcare leaders ensure enhances expertise while maintaining safe, patient-centered care.

Language: Английский

Citations

0
Artificial Intelligence in Nursing: Technological Benefits to Nurse’s Mental Health and Patient Care Quality DOI Open Access
Hamad Ghaleb Dailah,

Mahdi Dafer Koriri,

Alhussean Sabei

et al.

Healthcare, Journal Year: 2024, Volume and Issue: 12(24), P. 2555 - 2555

Published: Dec. 18, 2024

Nurses are frontline caregivers who handle heavy workloads and high-stakes activities. They face several mental health issues, including stress, burnout, anxiety, depression. The welfare of nurses the standard patient treatment depends on resolving this problem. Artificial intelligence is revolutionising healthcare, its integration provides many possibilities in addressing these concerns. This review examines literature published over past 40 years, concentrating AI nursing for support, improved care, ethical issues. Using databases such as PubMed Google Scholar, a thorough search was conducted with Boolean operators, narrowing results relevance. Critically examined were publications artificial applications care ethics, health, health. examination revealed that, by automating repetitive chores improving workload management, (AI) can relieve challenges faced improve care. Practical implications highlight requirement using rigorous implementation strategies that address data privacy, human-centred decision-making. All changes must direct to guarantee sustained significant influence healthcare.

Language: Английский

Citations

4
Application of artificial intelligence in nursing practice: a qualitative study of Jordanian nurses’ perspectives DOI Creative Commons
Wesam T. Almagharbeh,

Hazem AbdulKareem Alfanash,

Khaldoon Aied Alnawafleh

et al.

BMC Nursing, Journal Year: 2025, Volume and Issue: 24(1)

Published: Jan. 25, 2025

Language: Английский

Citations

0
Artificial Intelligence role in changing the role of nurses in patient care: Systematic Review (Preprint) DOI Creative Commons
Inas Al Khatib, Malick Ndiaye

JMIR Nursing, Journal Year: 2024, Volume and Issue: 8, P. e63335 - e63335

Published: Sept. 9, 2024

Background This review investigates the relationship between artificial intelligence (AI) use and role of nurses in patient care. AI exists health care for clinical decision support, disease management, engagement, operational improvement will continue to grow popularity, especially nursing field. Objective We aim examine whether integration into practice may have led a change Methods To compile pertinent data on their relationship, we conducted thorough systematic literature analysis using secondary sources, including academic from Scopus database, industry reports, government publications. A total 401 resources were reviewed, 53 sources ultimately included paper, comprising 50 peer-reviewed journal articles, 1 conference proceeding, 2 reports. categorize find patterns data, used thematic findings 3 primary themes 9 themes. demonstrate existed or was forecasted exist, case studies applications examples also relied on. Results The research shows that all practitioners be impacted by revolutionary technology known as AI. Nurses should at forefront this empowered throughout implementation process any its tools accelerate innovation, improve decision-making, automate speed up processes, save overall costs practice. Conclusions study adds existing body knowledge about consequences changing further investigate connection care, future can quantitative techniques based recruiting who been involved tool deployment—whether design aspect use—and gathering empirical purpose.

Language: Английский

Citations

1
The effects of generative AI’s human-like competencies on clinical decision-making DOI Creative Commons
Niko Spatscheck,

Myriam Schaschek,

Axel Winkelmann

et al.

Journal of Decision System, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 39

Published: Dec. 13, 2024

Generative AI (genAI) has revolutionized clinical systems by leveraging human language. Yet, challenges remain in its integration into settings, particularly regarding the risk of physicians relying on hallucinated advice. We conducted an experimental study with 368 novice who diagnosed patient cases while being augmented genAI systems. A theoretical model was empirically tested to examine how anthropomorphism and advice elaboration affect trust cognitive load as mediators for appropriate reliance. Findings show that augmenting decisions can improve physicians' diagnostic accuracy but also frequently results inappropriate reliance due miscalibrated trust. Moreover, we emphasize uncanny familiarity evoked anthropomorphizing systems, which diminishes reducing load. Our findings highlight benefits ethical decision support, underscoring need balance advantages safeguarding integrity agency.

Language: Английский

Citations

0