Robots and Robotics in Nursing

Industrial Robotics and the Future of Work

Starting in the 1970s with robots that were physically isolated from contact with their human co-workers, robots now collaborate with human workers towards a common task goal in a shared workspace. This type of robotic device represents a new era of workplace automation. Industrial robotics is rapidly evolving due to advances in sensor technology, artificial intelligence (AI), wireless communications, mechanical engineering, and materials science. While these new robotic devices are used mainly in manufacturing and warehousing, human-robot collaboration is now seen across multiple goods-producing and service-delivery industry sectors. Assessing and controlling the risks of human-robot collaboration is a critical challenge for occupational safety and health research and practice as industrial robotics becomes a pervasive feature of the future of work. Understanding the physical, psychosocial, work organization, and cybersecurity risks associated with the increasing use of robotic technologies is critical to ensuring the safe development and implementation of industrial robotics. This commentary provides a brief review of the uses of robotic technologies across selected industry sectors; the risks of current and future industrial robotic applications for worker and employer alike; strategies for integrating human-robot collaboration into a health and safety management system; and the role of robotic safety standards in the future of work.

HEalthcare Robotics' ONtology (HERON): An Upper Ontology for Communication, Collaboration and Safety in Healthcare Robotics

Background: Healthcare robotics needs context-aware policy-compliant reasoning to achieve safe human-agent collaboration. The current ontologies fail to provide healthcare-relevant information and flexible semantic enforcement systems. Methods: HERON represents a modular upper ontology which enables healthcare robotic systems to communicate and collaborate while ensuring safety during operations. The system enables domain-specific instantiations through SPARQL queries and SHACL-based constraint validation to perform context-driven logic. The system models robotic task interactions through simulated eldercare and diagnostic and surgical support scenarios which follow ethical and regulatory standards. Results: The validation tests demonstrated HERON's capacity to enable safe and explainable autonomous operations in changing environments. The semantic constraints enforced proper eligibility for roles and privacy conditions and policy override functionality during agent task execution. The HERON system demonstrated compatibility with healthcare IT systems and demonstrated adaptability to the GDPR and other policy frameworks. Conclusions: The semantically rich framework of HERON establishes an interoperable foundation for healthcare robotics. The system architecture maintains an open design which enables HL7/FHIR standard integration and robotic middleware compatibility. HERON demonstrates superior healthcare-specific capabilities through its evaluation against SUMO HL7 and MIMO. The future research will focus on optimizing HERON for low-resource clinical environments while extending its applications to remote care emergency triage and adaptive human-robot collaboration.

Artificial Intelligence in Nursing: Technological Benefits to Nurse's Mental Health and Patient Care Quality

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

Compassionate Care with Autonomous AI Humanoid Robots in Future Healthcare Delivery: A Multisensory Simulation of Next-Generation Models

The integration of AI and robotics in healthcare raises concerns, and additional issues regarding autonomous systems are anticipated. Effective communication is crucial for robots to be seen as "caring", necessitating advanced mechatronic design and natural language processing (NLP). This paper examines the potential of humanoid robots to autonomously replicate compassionate care. The study employs computational simulations using mathematical and agent-based modeling to analyze human-robot interactions (HRIs) surpassing Tetsuya Tanioka's TRETON. It incorporates stochastic elements (through neuromorphic computing) and quantum-inspired concepts (through the lens of Martha Rogers' theory), running simulations over 100 iterations to analyze complex behaviors. Multisensory simulations (visual and audio) demonstrate the significance of "dynamic communication", (relational) "entanglement", and (healthcare system and robot's function) "superpositioning" in HRIs. Quantum and neuromorphic computing may enable humanoid robots to empathetically respond to human emotions, based on Jean Watson's ten caritas processes for creating transpersonal states. Autonomous AI humanoid robots will redefine the norms of "caring". Establishing "pluralistic agreements" through open discussions among stakeholders worldwide is necessary to align innovations with the values of compassionate care within a "posthumanist" framework, where the compassionate care provided by Level 4 robots meets human expectations. Achieving compassionate care with autonomous AI humanoid robots involves translating nursing, communication, computer science, and engineering concepts into robotic care representations while considering ethical discourses through collaborative efforts. Nurses should lead the design and implementation of AI and robots guided by "technological knowing" in Rozzano Locsin's TCCN theory.

Christian Worldview and Caring in Nursing: The Legacy of Sister Simone Roach

ABSTRACT

Sister Simone Roach, a noted philosopher of caring in nursing, left behind a significant body of theoretical and practical work highlighting the areas of nursing ethics, care/caring, and compassion. This article explores the integration of the moral foundation of agape love in Pauline theology and Roach's human caring in nursing (1992) as the action of agape love. A narrative literature review explores the relationship between the scriptural ethics of St. Paul (Pauline ethics) and Roach's caring in nursing.

Artificial intelligence in head and neck surgery: Potential applications and future perspectives

Artificial intelligence (AI) has the potential to improve the surgical treatment of patients with head and neck cancer. AI algorithms can analyse a wide range of data, including images, voice, molecular expression and raw clinical data. In the field of oncology, there are numerous AI practical applications, including diagnostics and treatment. AI can also develop predictive models to assess prognosis, overall survival, the likelihood of occult metastases, risk of complications and hospital length of stay.

Harnessing the power of artificial intelligence and robotics impact on attaining competitive advantage for sustainable development in hospitals with conclusions for future research approaches

Artificial intelligence (AI) and robotics have emerged as game-changing technologies with the potential to revolutionize the healthcare industry. In the context of hospitals, their integration holds the promise of not only improving patient care but also driving competitive advantage and fostering sustainable development. This review paper aims to explore and evaluate the impact of AI and robotics applications on attaining competitive advantage and promoting sustainable development in hospitals, examines the current landscape of AI and robotics adoption in healthcare settings and delve into their specific applications within hospitals, including AI-assisted diagnosis, robotic surgery, patient monitoring, and data analytics. A key finding is the insufficient use of KI to date in terms of promoting sustainable development in hospitals. Furthermore, attempts to analyze the potential benefits and challenges associated with these technologies in terms of enhancing patient outcomes, operational efficiency, cost savings, and differentiation from competitors. Drawing upon a comprehensive review of the existing literature and case studies, this paper provides valuable insights into the transformative potential of AI and robotics in hospitals.

A spark of change: developing an innovative gerontological nursing intervention mapping initiative for training and education (IGNITE)

BACKGROUND

With an aging global population and advancements in medical technology, there is an urgent need for innovative gerontological nursing education programs. This study aimed to develop and evaluate the Innovative Gerontological Nursing Intervention Mapping Initiative for Training and Education (IGNITE) program. This program is a digital platform-based postgraduate nursing curriculum that employs the Intervention Mapping Approach (IMA) and Transformative Learning Theory to address the evolving needs of gerontological nursing.

METHODS

The IGNITE program's development process encompassed a comprehensive approach, including needs assessment, mapping of course objectives, integration of theory-based methods and strategies, course design, implementation, and rigorous evaluation. The pilot evaluation study involved pre- and post-tests focused on ageism, attitudes towards elder care, knowledge about older adults, transformative behavior change, and program satisfaction. The findings revealed significant improvements across all these dimensions, affirming the effectiveness of the program.

RESULTS

The program leveraged experiential learning, critical reflection, and rational discourse to facilitate transformative educational experiences. Notably, pre- and post-test comparisons showed marked improvements in attitudes towards older adult care and dementia care knowledge. Participants expressed high satisfaction with the program, with significant reported changes in transformative behaviors. The study also illuminated the initial negative attitudes of clinical nurses towards older adults and underscored the importance of transformative learning experiences in fostering empathy and understanding.

CONCLUSIONS

The IGNITE program lays a foundational framework for developing educational materials that promote transformative learning and self-reflection among healthcare professionals. This approach can lead to innovative nursing practices and personal growth. The application of the IMA and Transformative Learning Theory in gerontological nursing education shows significant promise. Future research should focus on exploring the long-term impacts of such programs and their applicability in diverse healthcare settings.

A Comprehensive Review of Prone Ventilation in the Intensive Care Unit: Challenges and Solutions

This comprehensive review explores the intricate landscape of prone ventilation in the intensive care unit (ICU), spanning physiological rationale, challenges in implementation, psychosocial impacts, technological innovations, economic considerations, barriers to adoption, and implications for clinical practice. The physiological benefits of prone positioning, including improved oxygenation and lung compliance, are discussed alongside the challenges of patient selection and technical complexities. The psychosocial impact on patients and caregivers, as well as the economic implications for healthcare systems, adds a crucial dimension to the analysis. The review also delves into innovative technologies, such as advanced monitoring and automation, shaping the landscape of prone ventilation. Moreover, it addresses the barriers to widespread adoption and outlines strategies to overcome resistance, emphasizing the need for a comprehensive and collaborative approach. The implications for clinical practice underscore the importance of evidence-based guidelines, ongoing education, and a holistic patient-centered care approach. The conclusion highlights the call to action for further research to refine protocols and technology, ultimately optimizing the application of prone ventilation in critical care settings.

Robotics in Nursing: Protocol for a Scoping Review

BACKGROUND

Globally, health care systems are challenged with the shortage of health care professionals, particularly nurses. The decline in the nursing workforce is primarily attributed to an aging population, increased demand for health care services, and a shortage of qualified nurses. Stressful working conditions have also increased the physical and emotional demands and perceptions of burnout, leading to attrition among nurses. Robotics has the potential to alleviate some of the workforce challenges by augmenting and supporting nurses in their roles; however, the impact of robotics on nurses is an understudied topic, and limited literature exists.

OBJECTIVE

We aim to understand the extent and type of evidence in relation to robotics integration in nursing practice.

METHODS

The Joanna Briggs Institute methodology and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist will guide the scoping review. The MEDLINE (Ovid), Embase (Ovid), CINAHL Plus with Full Text (EBSCOhost), Scopus, Cochrane Library, and IEEE Xplore electronic bibliographic databases will be searched to retrieve papers. In addition, gray literature sources, including Google Scholar, dissertations, theses, registries, blogs, and relevant organizational websites will be searched. Furthermore, the reference lists of included studies retrieved from the databases and the gray literature will be hand-searched to ensure relevant papers are not missed. In total, 2 reviewers will independently screen retrieve papers at each stage of the screening process and independently extract data from the included studies. A third reviewer will be consulted to help decision-making if conflicts arise. Data analysis will be completed using both descriptive statistics and content analysis. The results will be presented using tabular and narrative formats.

RESULTS

The review is expected to describe the current evidence on the integration and impact of robots and robotics into nursing clinical practice, provide insights into the current state and knowledge gaps, identify a direction for future research, and inform policy and practice. The authors expect to begin the data searches in late January 2024.

CONCLUSIONS

The robotics industry is evolving rapidly, providing different solutions that promise to revamp health care delivery with possible improvements to nursing practice. This review protocol outlines the steps proposed to systematically investigate this topic and provides an opportunity for more insights from scholars and researchers working in the field.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/50626.

Human-Robot Collaboration for Healthcare: A Narrative Review

Robotic applications have often quickly transitioned from industrial to social. Because of this, robots can now engage with people in a natural way and blend in with their surroundings. Due to the lack of medical professionals, growing healthcare costs, and the exponential rise in the population of vulnerable groups like the ill, elderly, and children with developmental disabilities, the use of social robots in the healthcare system is expanding. As a result, social robots are employed in the medical field to entertain and educate hospitalized patients about health issues, as well as to assist the elderly and sick. They are also employed in the dispensing of medications, rehabilitation, and emotional and geriatric care. Thus, social robots raise the standard and effectiveness of medical care. This article explains how patients and healthcare professionals collaborate with robots in the healthcare industry. The objectives of this collaboration are to resolve moral and legal concerns, improve patient outcomes, and improve healthcare delivery. It has a broad range of uses, including telemedicine, rehabilitation, and robotic surgical support. Human-robot interaction is the term used to describe interactions between social robots and people. Many obstacles stand in the way of human-robot interaction in healthcare, including safety concerns, acceptability issues, appropriateness, usefulness, and the worry that robots may replace human carers. In the end, these difficulties result in a poor adoption rate for robotic technology. As a result, the applications and difficulties of human-robot interaction in healthcare are thoroughly evaluated in this research. This study also reviews future safety prospects from human-robot interaction in healthcare, as well as ethical and usability issues including privacy, trust, and safety, and our aims to provide a comprehensive overview of the use of robots in healthcare, including their applications, benefits, challenges, and prospects, to facilitate a deeper understanding of this evolving field.

Facilitators and barriers to using AI-enabled robots with older adults in long-term care from staff perspective: a scoping review protocol

INTRODUCTION

Assistive and service robots have been increasingly designed and deployed in long-term care (LTC) but little evidence guides their use. This scoping review synthesises existing studies on facilitators and barriers to using artificial intelligence (AI)-enabled robots with older adults in LTC settings.

METHODS AND ANALYSIS

We will follow the Joanna Briggs Institute's scoping review methodology for the study, to be conducted from November 2023 to April 2024. We will focus on literature exploring the use of AI-enabled robots with older adults in an LTC setting from healthcare providers' perspectives. Three steps will be taken: (a) keywords and index terms will be identified from MEDLINE and CINAHL databases; (b) comprehensive searches will be conducted in MEDLINE, CINAHL, Embase, Web of Science, Scopus, AgeLine, PsycINFO, ProQuest and Google, using keywords and index terms identified in step (a); and (c) examining reference lists of the included studies and selecting items in the reference lists which meet the inclusion criteria. Searches for grey literature will also be conducted via Google. The results will be presented in a charting table and a narrative summary will be presented in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist.

ETHICS AND DISSEMINATION

Ethics approval and participation consent are not required because the data are publicly available. The results will be presented via a journal article and conference presentations.

Contributions to Nursing Knowledge: A Dialogue With Dr. Rozzano Locsin

There are many nursing scholars who have contributed to nursing knowledge. Dr. Rozzano Locsin is one of those scholars. His many contributions to nursing knowledge include his middle-range theory technological competency as caring in nursing. In this scholarly dialogue Dr. Locsin talks about nursing and his contributions to its knowledge development.