ReviewJournal of psychiatric and mental health nursing2025
Artificial Intelligence in Mental Health Nursing: Balancing Clinical Efficiency and the Human Touch-A Quest for a New Synthesis.
Review in Journal of psychiatric and mental health nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Effects of digital health interventions on self-care and quality of life in patients with an ostomy: A systematic review and meta-analysis.Asia-Pacific journal of oncology nursing · 2026Review
- When Care Becomes Digital: Shared Experiences in Psychiatric Nursing-A Phenomenological Study.Journal of psychiatric and mental health nursing · 2026Article
- Improving Nursing Team Collaboration Through Nurses' Digital Literacy: A Variable-Centered and Person-Centered Perspective.Journal of nursing management · 2025Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial intelligence (AI) applications are increasingly being integrated into mental health nursing, presenting opportunities alongside challenges.
aimThis 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.
methodUtilizing 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.
resultsFindings 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.
conclusionAI 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.