Trends in artificial intelligence in nursing: Impacts on nursing management

Artificial intelligence in future nursing care: Exploring perspectives of nursing professionals - A descriptive qualitative study

Background

The healthcare landscape is rapidly evolving, with artificial intelligence (AI) emerging as a transformative force. In this context, understanding the viewpoints of nursing professionals regarding the integration of AI in future nursing care is crucial.

Aims

This study aimed to provide insights into the perceptions of nursing professionals regarding the role of AI in shaping the future of healthcare.

Methods

A cohort of 23 nursing professionals was recruited between April 7, 2023, and May 4, 2023, for this study. Employing a thematic analysis approach, qualitative data from interviews with nursing professionals were analyzed. Verbatim transcripts underwent rigorous coding, and these codes were organized into themes through constant comparative analysis. The themes were refined and developed through the grouping of related codes, ensuring an authentic representation of participants' viewpoints.

Results

After careful data analysis, ten key themes emerged including: (I) Perceptions of AI readiness; (II) Benefits and concerns; (III) Enhanced patient outcomes; (IV) Collaboration and workflow; (V) Human-tech balance: (VI) Training and skill development; (VII) Ethical and legal considerations; (VIII) AI implementation barriers; (IX) Patient-nurse relationships; (X) Future vision and adaptation.

Conclusion

This study provides valuable insights into nursing professionals' perspectives on the integration of AI in future nursing care. It highlights their enthusiasm for AI's potential benefits while emphasizing the importance of ethical and compassionate nursing practice. The findings underscore the need for comprehensive training programs to equip nursing professionals with the skills necessary for successful AI integration. Ultimately, this research contributes to the ongoing discourse on the role of AI in nursing, paving the way for a future where innovative technologies complement and enhance the delivery of patient-centered care.

Research landscape and trends of cerebral amyloid angiopathy: a 25-year scientometric analysis

Background

Cerebral amyloid angiopathy (CAA), a cerebral small vessel disease affecting leptomeningeal and cortical small blood vessels, is a common cause of spontaneous lobar intracerebral hemorrhage and cognitive impairment, particularly in elderly patients. This study aims to investigate the field of CAA research from a scientometric perspective.

Methods

Publications related to CAA from January 1st, 1999 to September 29th, 2023 were retrieved from the Web of Science Core Collection database. The scientometric software VOSviewer and CiteSpace were used to analyze and visualize the publication trends, countries/regions, institutions, authors, journals, cited references, and keywords of CAA.

Results

A total of 2,798 publications related to CAA from 73 countries/regions, led by the United States, were included. The number of publications showed an increasing trend over time. Massachusetts General Hospital was the most productive institution, and authors Greenberg and Charidimou published the most papers and were most frequently co-cited. Journal of Alzheimer's Disease was the most prolific journal in this field, and Neurology was the most co-cited journal. Apart from "cerebral amyloid angiopathy", the most frequently used keywords were "Alzheimer's disease", "amyloid beta", "intracerebral hemorrhage", and "dementia". The burst keywords in recent years included "cortical superficial siderosis" and "dysfunction".

Conclusions

This scientometric analysis provides a comprehensive overview of CAA research over the past 25 years, and offers important insights for future research directions and scientific decision-making in this field.

Advancing nursing practice with artificial intelligence: Enhancing preparedness for the future

AIM

This article aimed to explore the role of AI in advancing nursing practice, focusing on its impact on readiness for the future.

DESIGN AND METHODS

A position paper, the methodology comprises three key steps. First, a comprehensive literature search using specific keywords in reputable databases was conducted to gather current information on AI in nursing. Second, data extraction and synthesis from selected articles were performed. Finally, a thematic analysis identifies recurring themes to provide insights into AI's impact on future nursing practice.

RESULTS

The findings highlight the transformative role of AI in advancing nursing practice and preparing nurses for the future, including enhancing nursing practice with AI, preparing nurses for the future (AI education and training) and associated, ethical considerations and challenges. AI-enabled robotics and telehealth solutions expand the reach of nursing care, improving accessibility of healthcare services and remote monitoring capabilities of patients' health conditions.

The Basics of Artificial Intelligence in Nursing: Fundamentals and Recommendations for Educators

BACKGROUND

Artificial intelligence (AI) offers exciting possibilities; however, AI is a double-edged sword. The adoption of this technology offers many benefits but also presents risks to academic integrity and appropriately prepared graduates. Many of today's nurse educators are from generations that are unlikely to possess an understanding of AI. This article provides fundamental knowledge needed to understand the current state of AI in nursing and offers recommendations to nurse educators on ways to responsibly incorporate AI technologies into nursing curricula.

METHOD

AI literature from PubMed, CINAHL, and Google Scholar was reviewed and synthesized.

RESULTS

Definitions, explanations, and applications to nursing education are outlined. Recommendations are made for AI implementation, along with ideas to avoid potential AI-enabled plagiarism and academic dishonesty.

CONCLUSION

As professionals, nurse educators should understand the basics of AI and be able to judge the appropriateness of integration and also recognize opportunities to embrace future application. [J Nurs Educ. 2023;62(12):716-720.].

Harnessing Artificial Intelligence: Strategies for Mental Health Nurses in Optimizing Psychiatric Patient Care

This narrative review explores the transformative impact of Artificial Intelligence (AI) on mental health nursing, particularly in enhancing psychiatric patient care. AI technologies present new strategies for early detection, risk assessment, and improving treatment adherence in mental health. They also facilitate remote patient monitoring, bridge geographical gaps, and support clinical decision-making. The evolution of virtual mental health assistants and AI-enhanced therapeutic interventions are also discussed. These technological advancements reshape the nurse-patient interactions while ensuring personalized, efficient, and high-quality care. The review also addresses AI's ethical and responsible use in mental health nursing, emphasizing patient privacy, data security, and the balance between human interaction and AI tools. As AI applications in mental health care continue to evolve, this review encourages continued innovation while advocating for responsible implementation, thereby optimally leveraging the potential of AI in mental health nursing.