Artificial Intelligence in Mental Health Nursing: Balancing Clinical Efficiency and the Human Touch-A Quest for a New Synthesis.

Erman Y��ld��z
Author Information
  1. Erman Y��ld��z: Department of Psychiatric Nursing, Faculty of Nursing, Inonu University, Malatya, T��rkiye. ORCID

Abstract

BACKGROUND: Artificial intelligence (AI) applications are increasingly being integrated into mental health nursing, presenting opportunities alongside challenges.
AIM: This article aims to examine the complex balance between leveraging AI for clinical efficiency and preserving indispensable human elements such as empathy and the therapeutic relationship in mental health nursing.
METHOD: Utilizing a review of literature, theoretical approaches, and insights from field observations, this debate essay explores the integration of AI, focusing on potential benefits, risks, and ethical considerations.
RESULTS: Findings indicate that while AI offers undeniable contributions to diagnostic processes and care coordination, its role should be complementary, not substitutive. Excessive reliance on algorithms risks damaging the patient-nurse relationship, potentially reducing individuals to data points. Significant ethical issues, including data privacy and algorithmic bias, require careful consideration.
CONCLUSION: AI should be implemented to enhance, not replace, human interaction in mental health nursing. A new synthesis is proposed where AI systems support efficiency, thereby allowing nurses more time to address patients' complex emotional needs. Key recommendations include restructuring nursing education, creating robust feedback channels, and establishing comprehensive ethical principles to preserve the essential human dimension of care.

Keywords

References

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Word Cloud

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