1
|
Watson AL. Ethical considerations for artificial intelligence use in nursing informatics. Nurs Ethics 2024:9697330241230515. [PMID: 38318798 DOI: 10.1177/09697330241230515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
Artificial intelligence revolutionizes nursing informatics and healthcare by enhancing patient outcomes and healthcare access while streamlining nursing workflow. These advancements, while promising, have sparked debates on traditional nursing ethics like patient data handling and implicit bias. The key to unlocking the next frontier in holistic nursing care lies in nurses navigating the delicate balance between artificial intelligence and the core values of empathy and compassion. Mindful utilization of artificial intelligence coupled with an unwavering ethical commitment by nurses may transform the very essence of nursing.
Collapse
|
2
|
Johnson EA, Dudding KM, Carrington JM. When to err is inhuman: An examination of the influence of artificial intelligence-driven nursing care on patient safety. Nurs Inq 2024; 31:e12583. [PMID: 37459179 DOI: 10.1111/nin.12583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 07/05/2023] [Accepted: 07/09/2023] [Indexed: 01/18/2024]
Abstract
Artificial intelligence, as a nonhuman entity, is increasingly used to inform, direct, or supplant nursing care and clinical decision-making. The boundaries between human- and nonhuman-driven nursing care are blurred with the advent of sensors, wearables, camera devices, and humanoid robots at such an accelerated pace that the critical evaluation of its influence on patient safety has not been fully assessed. Since the pivotal release of To Err is Human, patient safety is being challenged by the dynamic healthcare environment like never before, with nursing at a critical juncture to steer the course of artificial intelligence integration in clinical decision-making. This paper presents an overview of artificial intelligence and its application in healthcare and highlights the implications which affect nursing as a profession, including perspectives on nursing education and training recommendations. The legal and policy challenges which emerge when artificial intelligence influences the risk of clinical errors and safety issues are discussed.
Collapse
Affiliation(s)
- Elizabeth A Johnson
- Mark & Robyn Jones College of Nursing, Montana State University, Bozeman, Montana, USA
| | - Katherine M Dudding
- Department of Family, Community, and Health Systems, UAB School of Nursing, The University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Jane M Carrington
- Department of Family, Community and Health System Science, University of Florida College of Nursing, Gainesville, Florida, USA
| |
Collapse
|
3
|
Rony MKK, Parvin MR, Ferdousi S. Advancing nursing practice with artificial intelligence: Enhancing preparedness for the future. Nurs Open 2024; 11:10.1002/nop2.2070. [PMID: 38268252 PMCID: PMC10733565 DOI: 10.1002/nop2.2070] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Revised: 11/15/2023] [Accepted: 12/02/2023] [Indexed: 01/26/2024] Open
Abstract
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.
Collapse
Affiliation(s)
| | - Mst. Rina Parvin
- Major of Bangladesh ArmyCombined Military HospitalDhakaBangladesh
| | - Silvia Ferdousi
- International University of Business Agriculture and TechnologyDhakaBangladesh
| |
Collapse
|
4
|
He X, Zheng X, Ding H. Existing Barriers Faced by and Future Design Recommendations for Direct-to-Consumer Health Care Artificial Intelligence Apps: Scoping Review. J Med Internet Res 2023; 25:e50342. [PMID: 38109173 PMCID: PMC10758939 DOI: 10.2196/50342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 09/20/2023] [Accepted: 11/28/2023] [Indexed: 12/19/2023] Open
Abstract
BACKGROUND Direct-to-consumer (DTC) health care artificial intelligence (AI) apps hold the potential to bridge the spatial and temporal disparities in health care resources, but they also come with individual and societal risks due to AI errors. Furthermore, the manner in which consumers interact directly with health care AI is reshaping traditional physician-patient relationships. However, the academic community lacks a systematic comprehension of the research overview for such apps. OBJECTIVE This paper systematically delineated and analyzed the characteristics of included studies, identified existing barriers and design recommendations for DTC health care AI apps mentioned in the literature and also provided a reference for future design and development. METHODS This scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines and was conducted according to Arksey and O'Malley's 5-stage framework. Peer-reviewed papers on DTC health care AI apps published until March 27, 2023, in Web of Science, Scopus, the ACM Digital Library, IEEE Xplore, PubMed, and Google Scholar were included. The papers were analyzed using Braun and Clarke's reflective thematic analysis approach. RESULTS Of the 2898 papers retrieved, 32 (1.1%) covering this emerging field were included. The included papers were recently published (2018-2023), and most (23/32, 72%) were from developed countries. The medical field was mostly general practice (8/32, 25%). In terms of users and functionalities, some apps were designed solely for single-consumer groups (24/32, 75%), offering disease diagnosis (14/32, 44%), health self-management (8/32, 25%), and health care information inquiry (4/32, 13%). Other apps connected to physicians (5/32, 16%), family members (1/32, 3%), nursing staff (1/32, 3%), and health care departments (2/32, 6%), generally to alert these groups to abnormal conditions of consumer users. In addition, 8 barriers and 6 design recommendations related to DTC health care AI apps were identified. Some more subtle obstacles that are particularly worth noting and corresponding design recommendations in consumer-facing health care AI systems, including enhancing human-centered explainability, establishing calibrated trust and addressing overtrust, demonstrating empathy in AI, improving the specialization of consumer-grade products, and expanding the diversity of the test population, were further discussed. CONCLUSIONS The booming DTC health care AI apps present both risks and opportunities, which highlights the need to explore their current status. This paper systematically summarized and sorted the characteristics of the included studies, identified existing barriers faced by, and made future design recommendations for such apps. To the best of our knowledge, this is the first study to systematically summarize and categorize academic research on these apps. Future studies conducting the design and development of such systems could refer to the results of this study, which is crucial to improve the health care services provided by DTC health care AI apps.
Collapse
Affiliation(s)
- Xin He
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China
| | - Xi Zheng
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China
| | - Huiyuan Ding
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China
| |
Collapse
|
5
|
González Aguña A, Gonzalo de Diego B, Páez Ramos S, Fernández Batalla M, Jiménez Rodríguez ML, Santamaría García JM. Care Robotics: An Assessment of Professional Perception in the Face of the COVID-19 Pandemic. Healthcare (Basel) 2023; 11:healthcare11070946. [PMID: 37046875 PMCID: PMC10094221 DOI: 10.3390/healthcare11070946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 03/15/2023] [Accepted: 03/21/2023] [Indexed: 03/29/2023] Open
Abstract
The COVID-19 crisis accelerated the adoption of technologies. Technological advancement is also expected in robotics applied to any sector, including in healthcare. The aim is to assess the professional perception of care robotics facing COVID-19. This study aimed to (1) select a tool for assessing different aspects of healthcare, (2) analyse the professional perception about the development, usefulness and helpfulness of technologies and robotics in the field of healthcare and (3) evaluate the correlation between the perceived helpfulness of care robotics and the selected tool. We implement five validated clinical tests which integrate 80 items about a person and their clinical situation. From the sample of 46 professionals, 95.65% affirmed that technology was moderately to completely useful for professional performance in the context of the pandemic, lowering to 67.39% when asked only about robotics; 93.48% stated that the inclusion of robotics in at least one health area affected by COVID-19 would have helped them. Finally, the variables extracted from clinical tests corresponded to the most relevant health areas as identified by the professionals. This research shows the potential of care robotics oriented towards healthcare from a care paradigm.
Collapse
Affiliation(s)
- Alexandra González Aguña
- Henares University Hospital, Community of Madrid Health Service (SERMAS), 28822 Madrid, Spain
- Research Group MISKC, Department of Computer Science, University of Alcala, Polytechnic Building, University Campus, Barcelona Road Km. 33.6, 28805 Alcalá de Henares, Spain; (B.G.d.D.); (S.P.R.); (M.F.B.); (M.L.J.R.); (J.M.S.G.)
- Correspondence:
| | - Blanca Gonzalo de Diego
- Research Group MISKC, Department of Computer Science, University of Alcala, Polytechnic Building, University Campus, Barcelona Road Km. 33.6, 28805 Alcalá de Henares, Spain; (B.G.d.D.); (S.P.R.); (M.F.B.); (M.L.J.R.); (J.M.S.G.)
- Meco Health Centre, Community of Madrid Health Service (SERMAS), 28880 Madrid, Spain
| | - Sandra Páez Ramos
- Research Group MISKC, Department of Computer Science, University of Alcala, Polytechnic Building, University Campus, Barcelona Road Km. 33.6, 28805 Alcalá de Henares, Spain; (B.G.d.D.); (S.P.R.); (M.F.B.); (M.L.J.R.); (J.M.S.G.)
- Meco Health Centre, Community of Madrid Health Service (SERMAS), 28880 Madrid, Spain
| | - Marta Fernández Batalla
- Research Group MISKC, Department of Computer Science, University of Alcala, Polytechnic Building, University Campus, Barcelona Road Km. 33.6, 28805 Alcalá de Henares, Spain; (B.G.d.D.); (S.P.R.); (M.F.B.); (M.L.J.R.); (J.M.S.G.)
| | - María Lourdes Jiménez Rodríguez
- Research Group MISKC, Department of Computer Science, University of Alcala, Polytechnic Building, University Campus, Barcelona Road Km. 33.6, 28805 Alcalá de Henares, Spain; (B.G.d.D.); (S.P.R.); (M.F.B.); (M.L.J.R.); (J.M.S.G.)
- Computer Science Department, University of Alcala, 28805 Madrid, Spain
| | - José María Santamaría García
- Research Group MISKC, Department of Computer Science, University of Alcala, Polytechnic Building, University Campus, Barcelona Road Km. 33.6, 28805 Alcalá de Henares, Spain; (B.G.d.D.); (S.P.R.); (M.F.B.); (M.L.J.R.); (J.M.S.G.)
- Meco Health Centre, Community of Madrid Health Service (SERMAS), 28880 Madrid, Spain
| |
Collapse
|
6
|
Morrow E, Zidaru T, Ross F, Mason C, Patel KD, Ream M, Stockley R. Artificial intelligence technologies and compassion in healthcare: A systematic scoping review. Front Psychol 2023; 13:971044. [PMID: 36733854 PMCID: PMC9887144 DOI: 10.3389/fpsyg.2022.971044] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 12/05/2022] [Indexed: 01/18/2023] Open
Abstract
Background Advances in artificial intelligence (AI) technologies, together with the availability of big data in society, creates uncertainties about how these developments will affect healthcare systems worldwide. Compassion is essential for high-quality healthcare and research shows how prosocial caring behaviors benefit human health and societies. However, the possible association between AI technologies and compassion is under conceptualized and underexplored. Objectives The aim of this scoping review is to provide a comprehensive depth and a balanced perspective of the emerging topic of AI technologies and compassion, to inform future research and practice. The review questions were: How is compassion discussed in relation to AI technologies in healthcare? How are AI technologies being used to enhance compassion in healthcare? What are the gaps in current knowledge and unexplored potential? What are the key areas where AI technologies could support compassion in healthcare? Materials and methods A systematic scoping review following five steps of Joanna Briggs Institute methodology. Presentation of the scoping review conforms with PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews). Eligibility criteria were defined according to 3 concept constructs (AI technologies, compassion, healthcare) developed from the literature and informed by medical subject headings (MeSH) and key words for the electronic searches. Sources of evidence were Web of Science and PubMed databases, articles published in English language 2011-2022. Articles were screened by title/abstract using inclusion/exclusion criteria. Data extracted (author, date of publication, type of article, aim/context of healthcare, key relevant findings, country) was charted using data tables. Thematic analysis used an inductive-deductive approach to generate code categories from the review questions and the data. A multidisciplinary team assessed themes for resonance and relevance to research and practice. Results Searches identified 3,124 articles. A total of 197 were included after screening. The number of articles has increased over 10 years (2011, n = 1 to 2021, n = 47 and from Jan-Aug 2022 n = 35 articles). Overarching themes related to the review questions were: (1) Developments and debates (7 themes) Concerns about AI ethics, healthcare jobs, and loss of empathy; Human-centered design of AI technologies for healthcare; Optimistic speculation AI technologies will address care gaps; Interrogation of what it means to be human and to care; Recognition of future potential for patient monitoring, virtual proximity, and access to healthcare; Calls for curricula development and healthcare professional education; Implementation of AI applications to enhance health and wellbeing of the healthcare workforce. (2) How AI technologies enhance compassion (10 themes) Empathetic awareness; Empathetic response and relational behavior; Communication skills; Health coaching; Therapeutic interventions; Moral development learning; Clinical knowledge and clinical assessment; Healthcare quality assessment; Therapeutic bond and therapeutic alliance; Providing health information and advice. (3) Gaps in knowledge (4 themes) Educational effectiveness of AI-assisted learning; Patient diversity and AI technologies; Implementation of AI technologies in education and practice settings; Safety and clinical effectiveness of AI technologies. (4) Key areas for development (3 themes) Enriching education, learning and clinical practice; Extending healing spaces; Enhancing healing relationships. Conclusion There is an association between AI technologies and compassion in healthcare and interest in this association has grown internationally over the last decade. In a range of healthcare contexts, AI technologies are being used to enhance empathetic awareness; empathetic response and relational behavior; communication skills; health coaching; therapeutic interventions; moral development learning; clinical knowledge and clinical assessment; healthcare quality assessment; therapeutic bond and therapeutic alliance; and to provide health information and advice. The findings inform a reconceptualization of compassion as a human-AI system of intelligent caring comprising six elements: (1) Awareness of suffering (e.g., pain, distress, risk, disadvantage); (2) Understanding the suffering (significance, context, rights, responsibilities etc.); (3) Connecting with the suffering (e.g., verbal, physical, signs and symbols); (4) Making a judgment about the suffering (the need to act); (5) Responding with an intention to alleviate the suffering; (6) Attention to the effect and outcomes of the response. These elements can operate at an individual (human or machine) and collective systems level (healthcare organizations or systems) as a cyclical system to alleviate different types of suffering. New and novel approaches to human-AI intelligent caring could enrich education, learning, and clinical practice; extend healing spaces; and enhance healing relationships. Implications In a complex adaptive system such as healthcare, human-AI intelligent caring will need to be implemented, not as an ideology, but through strategic choices, incentives, regulation, professional education, and training, as well as through joined up thinking about human-AI intelligent caring. Research funders can encourage research and development into the topic of AI technologies and compassion as a system of human-AI intelligent caring. Educators, technologists, and health professionals can inform themselves about the system of human-AI intelligent caring.
Collapse
Affiliation(s)
| | - Teodor Zidaru
- Department of Anthropology, London School of Economics and Political Sciences, London, United Kingdom
| | - Fiona Ross
- Faculty of Health, Science, Social Care and Education, Kingston University London, London, United Kingdom
| | - Cindy Mason
- Artificial Intelligence Researcher (Independent), Palo Alto, CA, United States
| | | | - Melissa Ream
- Kent Surrey Sussex Academic Health Science Network (AHSN) and the National AHSN Network Artificial Intelligence (AI) Initiative, Surrey, United Kingdom
| | - Rich Stockley
- Head of Research and Engagement, Surrey Heartlands Health and Care Partnership, Surrey, United Kingdom
| |
Collapse
|
7
|
Locsin RC. Nursing and Humanities as Disciplinary Worlds in Nursing: A Review of Graham McCaffrey's Nursing and Humanities 2020 Book. Nurs Sci Q 2023; 36:95-99. [PMID: 36571316 DOI: 10.1177/08943184221135168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
The author in this article provides a review and critique of Graham McCaffrey's book Nursing and Humanities.
Collapse
Affiliation(s)
- Rozzano C Locsin
- Christine E. Lynn College of Nursing, Florida Atlantic University, Boca Raton, FL, USA
| |
Collapse
|
8
|
Dino MJS, Davidson PM, Dion KW, Szanton SL, Ong IL. Nursing and human-computer interaction in healthcare robots for older people: An integrative review. INTERNATIONAL JOURNAL OF NURSING STUDIES ADVANCES 2022; 4:100072. [PMID: 38745638 PMCID: PMC11080351 DOI: 10.1016/j.ijnsa.2022.100072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 03/01/2022] [Accepted: 03/02/2022] [Indexed: 10/18/2022] Open
Abstract
Objectives This study examined the published works related to healthcare robotics for older people using the attributes of health, nursing, and the human-computer interaction framework. Design An integrative literature review. Methods A search strategy captured 55 eligible articles from databases (CINAHL, Embase, IEEE Xplore, and PubMed) and hand-searching approaches. Bibliometric and content analyses grounded on the health and nursing attributes and human-computer interaction framework were performed using MAXQDA. Finally, results were verified using critical friend feedback by a second reviewer. Results Most articles were from multiple authorship, published in non-nursing journals, and originating from developed economies. They primarily focused on applying healthcare robots in practice settings, physical health, and communication tasks. Using the human-computer interaction framework, it was found that older adults frequently served as the primary users while nurses, healthcare providers, and researchers functioned as secondary users and operators. Research articles focused on the usability, functionality, and acceptability of robotic systems. At the same time, theoretical papers explored the frameworks and the value of empathy and emotion in robots, human-computer interaction and nursing models and theories supporting healthcare practice, and gerontechnology. Current robotic systems are less anthropomorphic, operated through real-time direct and supervisory inputs, and mainly equipped with visual and auditory sensors and actuators with limited capability in performing health assessments. Conclusion Results communicate the need for technological competency among nurses, advancements in increasing healthcare robot humanness, and the importance of conscientious efforts from an interdisciplinary research team in improving robotic system usability and utility for the care of older adults.
Collapse
Affiliation(s)
- Michael Joseph S. Dino
- School of Nursing, Johns Hopkins University, 525 N Wolfe St, Baltimore, MD 21205, USA
- Our Lady of Fatima University, 120 McArthur Highway, Marulas, Valenzuela City 1440, Philippines
| | - Patricia M. Davidson
- School of Nursing, Johns Hopkins University, 525 N Wolfe St, Baltimore, MD 21205, USA
- University of Wollongong, The Vice-Chancellor's Unit Building 36, University of Wollongong, NSW 2522, Australia
| | - Kenneth W. Dion
- School of Nursing, Johns Hopkins University, 525 N Wolfe St, Baltimore, MD 21205, USA
| | - Sarah L. Szanton
- School of Nursing, Johns Hopkins University, 525 N Wolfe St, Baltimore, MD 21205, USA
| | - Irvin L. Ong
- School of Nursing, Johns Hopkins University, 525 N Wolfe St, Baltimore, MD 21205, USA
- Our Lady of Fatima University, 120 McArthur Highway, Marulas, Valenzuela City 1440, Philippines
| |
Collapse
|
9
|
Zrínyi M, Lampek K, Pakai A, Vass D, Oláh A. Changing the Perceived Views of Student Nurses Concerning Healthcare Robots: A Video Intervention Approach. Comput Inform Nurs 2022; 40:797-800. [PMID: 36516030 DOI: 10.1097/cin.0000000000000946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Miklós Zrínyi
- Author Affiliations: Faculty of Health, University of Pécs (Drs Zrínyi, Lampek, and Pakai); Bay Zoltán Nonprofit Ltd for Applied Research, Budapest (Mr Vass); and Living Lab-Based Smart Care Research Center, Faculty of Health, University of Pécs (Dr Oláh), Hungary
| | | | | | | | | |
Collapse
|
10
|
Soriano GP, Yasuhara Y, Ito H, Matsumoto K, Osaka K, Kai Y, Locsin R, Schoenhofer S, Tanioka T. Robots and Robotics in Nursing. Healthcare (Basel) 2022; 10:healthcare10081571. [PMID: 36011228 PMCID: PMC9407759 DOI: 10.3390/healthcare10081571] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 08/15/2022] [Accepted: 08/16/2022] [Indexed: 11/29/2022] Open
Abstract
Technological advancements have led to the use of robots as prospective partners to complement understaffing and deliver effective care to patients. This article discusses relevant concepts on robots from the perspective of nursing theories and robotics in nursing and examines the distinctions between human beings and healthcare robots as partners and robot development examples and challenges. Robotics in nursing is an interdisciplinary discipline that studies methodologies, technologies, and ethics for developing robots that support and collaborate with physicians, nurses, and other healthcare workers in practice. Robotics in nursing is geared toward learning the knowledge of robots for better nursing care, and for this purpose, it is also to propose the necessary robots and develop them in collaboration with engineers. Two points were highlighted regarding the use of robots in health care practice: issues of replacing humans because of human resource understaffing and concerns about robot capabilities to engage in nursing practice grounded in caring science. This article stresses that technology and artificial intelligence are useful and practical for patients. However, further research is required that considers what robotics in nursing means and the use of robotics in nursing.
Collapse
Affiliation(s)
- Gil P. Soriano
- Department of Nursing, College of Allied Health, National University, Manila 1008, Philippines
- Graduate School of Health Sciences, Tokushima University, Tokushima 770-8509, Japan
- Correspondence: or
| | - Yuko Yasuhara
- Department of Nursing, Institute of Biomedical Sciences, Tokushima University, Tokushima 770-8509, Japan
| | - Hirokazu Ito
- Department of Nursing, Institute of Biomedical Sciences, Tokushima University, Tokushima 770-8509, Japan
| | - Kazuyuki Matsumoto
- Graduate School of Sciences and Technology for Innovation, Tokushima University, Tokushima 770-8506, Japan
| | - Kyoko Osaka
- Department of Psychiatric Nursing, Nursing Course of Kochi Medical School, Kochi University, Kochi 783-8505, Japan
| | - Yoshihiro Kai
- Department of Mechanical System Engineering, Tokai University, Hiratsuka 259-1292, Japan
| | - Rozzano Locsin
- Department of Nursing, Institute of Biomedical Sciences, Tokushima University, Tokushima 770-8509, Japan
- Christine E. Lynn College of Nursing, Florida Atlantic University, Boca Raton, FL 33431, USA
| | | | - Tetsuya Tanioka
- Department of Nursing, Institute of Biomedical Sciences, Tokushima University, Tokushima 770-8509, Japan
| |
Collapse
|
11
|
Rubeis G. Adiaphorisation and the digital nursing gaze: Liquid surveillance in long-term care. Nurs Philos 2022; 24:e12388. [PMID: 35355391 PMCID: PMC10078243 DOI: 10.1111/nup.12388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 01/11/2022] [Accepted: 03/13/2022] [Indexed: 12/01/2022]
Abstract
The nursing gaze, that is the specific ways of observing the patient in nursing practice, has been the object of ethical debates for decades. It has been argued that the specific feature of observing patients in nursing is the stereoscopic vision that allows nurses to see the patient at the same time as a subject and a body. However, with the increased use of technology in nursing and the focus on quantifiable biomedical data, some commentators see a shift from the view of the patient as subject to the patient as body, which results in a de-humanisation and objectification of patients. The new digital technologies in patient monitoring and surveillance add a further dimension to this topic. It is yet unclear how digital technologies affect the nursing gaze, and with it, nursing practice. Furthermore, the ethical implications of the digitally enhanced nursing gaze have yet to be analysed. It is the purpose of this study to make a first step in this direction. By focusing on digitally enhanced monitoring technologies in long-term care, these technologies are interpreted as liquid surveillance, an approach introduced by Zygmunt Bauman. The Baumanian concept of adiaphorisation, that is the detachment of social action from moral evaluation, is used as normative framework of the analysis. The analysis shows that the tendency to remove surveillance practices from moral evaluation by framing them as enablers of an active, healthy life and as tools for caring for the vulnerable, the stereoscopic vision of the nursing gaze is undermined.
Collapse
Affiliation(s)
- Giovanni Rubeis
- Department of Biomedical and Public Health Ethics, Karl Landsteiner University of Health Sciences, Krems, Austria
| |
Collapse
|
12
|
|
13
|
Simeoni R, Colonnelli F, Eutizi V, Marchetti M, Paolini E, Papalini V, Punturo A, Salvò A, Scipinotti N, Serpente C, Barbini E, Troscia R, Maccioni G, Giansanti D. The Social Robot and the Digital Physiotherapist: Are We Ready for the Team Play? Healthcare (Basel) 2021; 9:1454. [PMID: 34828501 PMCID: PMC8618922 DOI: 10.3390/healthcare9111454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 10/20/2021] [Accepted: 10/23/2021] [Indexed: 11/17/2022] Open
Abstract
Motivation: We are witnessing two phenomena. The first is that the physiotherapist is increasingly becoming a figure that must interact with Digital Health. On the other hand, social robots through research are improving more and more in the aspects of social interaction thanks also to artificial intelligence and becoming useful in rehabilitation processes. It begins to become strategic to investigate the intersections between these two phenomena. Objective: Therefore, we set ourselves the goal of investigating the consensus and opinion of physiotherapists around the introduction of social robots in clinical practice both in rehabilitation and assistance. Procedure: An electronic survey has been developed focused on social robot-based rehabilitation and assistance and has been submitted to subjects focused on physiotherapy sciences to investigate their opinion and their level of consent regarding the use of the social robot in rehabilitation and assistance. Two samples of subjects were recruited: the first group (156 participating subjects, 79 males, 77 females, mean age 24.3 years) was in the training phase, and the second (167 participating subjects, 86 males, 81 females, mean age 42.4 years) group was involved in the work processes. An electronic feedback form was also submitted to investigate the acceptance of the proposed methodology. Results: The survey showed a consistency of the results between the two samples from which interesting considerations emerge. Contrary to stereotypes that report how AI-based devices put jobs at risk, physiotherapists are not afraid of these devices. The subjects involved in the study believe the following: (a) social robots can be reliable co-workers but will remain a complementary device; (b) their role will be of the utmost importance as an operational manager in their use and in performance monitoring; (c) these devices will allow an increase in working capacity and facilitate integration. All those involved in the study believe that the proposed electronic survey has proved to be a useful and effective tool that can be useful as a periodic monitoring tool and useful for scientific societies. Conclusions: The evolution of social robots represents an unstoppable process as does the increase in the aging of the population. Stakeholders must not look with suspicion toward these devices, which can represent an important resource, but rather invest in monitoring and consensus training initiatives.
Collapse
Affiliation(s)
- Rossella Simeoni
- Faculty of Medicine and Surgery, Università Cattolica del Sacro Cuore, San Martino al Cimino, 01100 Viterbo, Italy; (R.S.); (F.C.); (V.E.); (M.M.); (E.P.); (V.P.); (A.P.); (A.S.); (N.S.); (C.S.); (E.B.); (R.T.)
| | - Federico Colonnelli
- Faculty of Medicine and Surgery, Università Cattolica del Sacro Cuore, San Martino al Cimino, 01100 Viterbo, Italy; (R.S.); (F.C.); (V.E.); (M.M.); (E.P.); (V.P.); (A.P.); (A.S.); (N.S.); (C.S.); (E.B.); (R.T.)
| | - Veronica Eutizi
- Faculty of Medicine and Surgery, Università Cattolica del Sacro Cuore, San Martino al Cimino, 01100 Viterbo, Italy; (R.S.); (F.C.); (V.E.); (M.M.); (E.P.); (V.P.); (A.P.); (A.S.); (N.S.); (C.S.); (E.B.); (R.T.)
| | - Matteo Marchetti
- Faculty of Medicine and Surgery, Università Cattolica del Sacro Cuore, San Martino al Cimino, 01100 Viterbo, Italy; (R.S.); (F.C.); (V.E.); (M.M.); (E.P.); (V.P.); (A.P.); (A.S.); (N.S.); (C.S.); (E.B.); (R.T.)
| | - Elena Paolini
- Faculty of Medicine and Surgery, Università Cattolica del Sacro Cuore, San Martino al Cimino, 01100 Viterbo, Italy; (R.S.); (F.C.); (V.E.); (M.M.); (E.P.); (V.P.); (A.P.); (A.S.); (N.S.); (C.S.); (E.B.); (R.T.)
| | - Valentina Papalini
- Faculty of Medicine and Surgery, Università Cattolica del Sacro Cuore, San Martino al Cimino, 01100 Viterbo, Italy; (R.S.); (F.C.); (V.E.); (M.M.); (E.P.); (V.P.); (A.P.); (A.S.); (N.S.); (C.S.); (E.B.); (R.T.)
| | - Alessio Punturo
- Faculty of Medicine and Surgery, Università Cattolica del Sacro Cuore, San Martino al Cimino, 01100 Viterbo, Italy; (R.S.); (F.C.); (V.E.); (M.M.); (E.P.); (V.P.); (A.P.); (A.S.); (N.S.); (C.S.); (E.B.); (R.T.)
| | - Alice Salvò
- Faculty of Medicine and Surgery, Università Cattolica del Sacro Cuore, San Martino al Cimino, 01100 Viterbo, Italy; (R.S.); (F.C.); (V.E.); (M.M.); (E.P.); (V.P.); (A.P.); (A.S.); (N.S.); (C.S.); (E.B.); (R.T.)
| | - Nicoletta Scipinotti
- Faculty of Medicine and Surgery, Università Cattolica del Sacro Cuore, San Martino al Cimino, 01100 Viterbo, Italy; (R.S.); (F.C.); (V.E.); (M.M.); (E.P.); (V.P.); (A.P.); (A.S.); (N.S.); (C.S.); (E.B.); (R.T.)
| | - Christian Serpente
- Faculty of Medicine and Surgery, Università Cattolica del Sacro Cuore, San Martino al Cimino, 01100 Viterbo, Italy; (R.S.); (F.C.); (V.E.); (M.M.); (E.P.); (V.P.); (A.P.); (A.S.); (N.S.); (C.S.); (E.B.); (R.T.)
| | - Emanuele Barbini
- Faculty of Medicine and Surgery, Università Cattolica del Sacro Cuore, San Martino al Cimino, 01100 Viterbo, Italy; (R.S.); (F.C.); (V.E.); (M.M.); (E.P.); (V.P.); (A.P.); (A.S.); (N.S.); (C.S.); (E.B.); (R.T.)
| | - Riccardo Troscia
- Faculty of Medicine and Surgery, Università Cattolica del Sacro Cuore, San Martino al Cimino, 01100 Viterbo, Italy; (R.S.); (F.C.); (V.E.); (M.M.); (E.P.); (V.P.); (A.P.); (A.S.); (N.S.); (C.S.); (E.B.); (R.T.)
| | | | | |
Collapse
|
14
|
Hildt E. What Sort of Robots Do We Want to Interact With? Reflecting on the Human Side of Human-Artificial Intelligence Interaction. FRONTIERS IN COMPUTER SCIENCE 2021. [DOI: 10.3389/fcomp.2021.671012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
|
15
|
Hulin T, Panzirsch M, Singh H, Coelho A, Balachandran R, Pereira A, Weber BM, Bechtel N, Riecke C, Brunner B, Lii NY, Klodmann J, Hellings A, Hagmann K, Quere G, Bauer AS, Sierotowicz M, Lampariello R, Vogel J, Dietrich A, Leidner D, Ott C, Hirzinger G, Albu-Schäffer A. Model-Augmented Haptic Telemanipulation: Concept, Retrospective Overview, and Current Use Cases. Front Robot AI 2021; 8:611251. [PMID: 34179105 PMCID: PMC8232524 DOI: 10.3389/frobt.2021.611251] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 03/03/2021] [Indexed: 11/13/2022] Open
Abstract
Certain telerobotic applications, including telerobotics in space, pose particularly demanding challenges to both technology and humans. Traditional bilateral telemanipulation approaches often cannot be used in such applications due to technical and physical limitations such as long and varying delays, packet loss, and limited bandwidth, as well as high reliability, precision, and task duration requirements. In order to close this gap, we research model-augmented haptic telemanipulation (MATM) that uses two kinds of models: a remote model that enables shared autonomous functionality of the teleoperated robot, and a local model that aims to generate assistive augmented haptic feedback for the human operator. Several technological methods that form the backbone of the MATM approach have already been successfully demonstrated in accomplished telerobotic space missions. On this basis, we have applied our approach in more recent research to applications in the fields of orbital robotics, telesurgery, caregiving, and telenavigation. In the course of this work, we have advanced specific aspects of the approach that were of particular importance for each respective application, especially shared autonomy, and haptic augmentation. This overview paper discusses the MATM approach in detail, presents the latest research results of the various technologies encompassed within this approach, provides a retrospective of DLR's telerobotic space missions, demonstrates the broad application potential of MATM based on the aforementioned use cases, and outlines lessons learned and open challenges.
Collapse
Affiliation(s)
- Thomas Hulin
- Institute of Robotics and Mechatronics, German Aerospace Center (DLR), Wessling, Germany
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|