Nursing in a posthuman era: Towards a technology-integrated ecosystem of care

Ethical boundaries and data-sharing practices in AI-enhanced nursing: An Arab perspective

AIM

This study explored the ethical boundaries and data-sharing practices in artificial intelligence (AI)-enhanced nursing from the perspective of Arab nurses.

BACKGROUND

Although AI offers advancements in clinical decision-making and operational efficiency, it also presents challenges such as ethical dilemmas, data privacy concerns, and technical issues. These challenges are being addressed through continuous education, the development of robust ethical guidelines, and the implementation of transparent data-sharing practices METHODS: A qualitative approach was employed, adhering to the Standards for Reporting Qualitative Research (SRQR) guidelines. Fourteen registered nurses from healthcare facilities in Abha City, Saudi Arabia, were selected through purposive sampling. Data were collected through semistructured interviews, observational data and document analysis. Thematic analysis was used to analyze the data.

RESULTS

Nurses reported that AI technologies enhance clinical decision-making and efficiency by automating routine tasks. However, they also highlighted ethical challenges, including conflicts between AI recommendations and patient preferences, the need for continuous training, and resource constraints. The importance of maintaining human interaction and empathy in nursing practice was emphasized.

DISCUSSION

The findings align with existing literature on the benefits and challenges of AI in nursing. Ethical dilemmas, particularly related to data privacy and informed consent, require careful management. Continuous education and adequate resources are essential for successful AI integration.

CONCLUSION

AI in nursing not only offers significant benefits but also presents ethical and practical challenges. Clear ethical guidelines, continuous education, and adequate resources are crucial for optimizing AI integration.

IMPLICATIONS FOR NURSING

AI can enhance clinical decision-making and efficiency, allowing nurses to focus on patient interaction and critical thinking.

IMPLICATIONS FOR HEALTH POLICY

Develop robust ethical frameworks and data protection regulations. Implement continuous professional development programs and ensure adequate resources for AI integration in healthcare.

The Future of Artificial Intelligence in Mental Health Nursing Practice: An Integrative Review

Artificial intelligence (AI) has been increasingly used in delivering mental healthcare worldwide. Within this context, the traditional role of mental health nurses has been changed and challenged by AI-powered cutting-edge technologies emerging in clinical practice. The aim of this integrative review is to identify and synthesise the evidence of AI-based applications with relevance for, and potential to enhance, mental health nursing practice. Five electronic databases (CINAHL, PubMed, PsycINFO, Web of Science and Scopus) were systematically searched. Seventy-eight studies were identified, critically appraised and synthesised following a comprehensive integrative approach. We found that AI applications with potential use in mental health nursing vary widely from machine learning algorithms to natural language processing, digital phenotyping, computer vision and conversational agents for assessing, diagnosing and treating mental health challenges. Five overarching themes were identified: assessment, identification, prediction, optimisation and perception reflecting the multiple levels of embedding AI-driven technologies in mental health nursing practice, and how patients and staff perceive the use of AI in clinical settings. We concluded that AI-driven technologies hold great potential for enhancing mental health nursing practice. However, humanistic approaches to mental healthcare may pose some challenges to effectively incorporating AI into mental health nursing. Meaningful conversations between mental health nurses, service users and AI developers should take place to shaping the co-creation of AI technologies to enhance care in a way that promotes person-centredness, empowerment and active participation.

Critical posthumanism: A double-edged sword for advancing nursing knowledge in planetary health

In this article, we aimed to evaluate the utility of critical posthumanism for nurses interested in planetary health-a growing area of study that requires a decentering of the human, and environmental justice considerations. We used Chinn and colleagues' method to describe and critically reflect on critical posthumanism, extending the theory analysis method to include a wide range of academic and video sources. We found that critical posthumanism is like a double-edged sword: It provides a lens through which to transcend human-centric approaches to healthcare but is marred by its lack of clarity and inaccessibility. We argue critical posthumanism can be adapted to enhance its potential at the intersection of nursing and planetary health. An analysis of critical posthumanism is followed by a discussion framed by five ways of knowing in nursing, highlighting real-world examples of how critical posthumanism can aid nurses in dealing with planetary health concerns. By exploring the intersections of critical posthumanism with nursing knowledge, we demonstrate how critical posthumanism can enable nurses to comprehend and tackle environmental issues intricately linked to human health.