Artificial intelligence technologies and compassion in healthcare: A systematic scoping review.
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.
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?
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.
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.
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.
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.
Morrow E
，Zidaru T
，Ross F
，Mason C
，Patel KD
，Ream M
，Stockley R
... -
《Frontiers in Psychology》
An analysis of relationships among transformational leadership, job satisfaction, organizational commitment and organizational trust in two Turkish hospitals.
The purpose of this study was to investigate the relationships among employee organizational commitment, organizational trust, job satisfaction and employees' perceptions of their immediate supervisors' transformational leadership behaviors in Turkey. First, this study examined the relationships among organizational commitment, organizational trust, job satisfaction and transformational leadership in two Turkish public hospitals. Second, this investigation examined how job satisfaction, organizational trust and transformational leadership affect organizational commitment. Moreover, it was aimed to investigate how organizational commitment, job satisfaction and transformational leadership affect organizational trust. A quantitative, cross-sectional method, self-administered questionnaire was used for this study. Eight hundred four employees from two public hospitals in Turkey were recruited for collecting data. The overall response rate was 38.14%. The measurement instruments of survey were the Job Satisfaction Survey (developed by P. Spector), the Organizational Commitment Questionnaire (developed by J. Meyer and N. Allen), the Organizational Trust Inventory-short form (developed by L. Cummings and P. Bromiley) and the Transformational Leadership Inventory (TLI) (developed by P. M. Podsakoff). Five-point Likert scales were used in these measurement instruments. Correlation test (the Pearson's rank test) was used to examine relationships between variables. Also, multiple regression analysis was used to determine the regressors for organizational commitment and organizational trust. There were significant relationships among overall job satisfaction, overall transformational leadership and organizational trust. Regression analyses showed that organizational trust and two job satisfaction dimensions (contingent rewards and communication) were significant predictors for organizational commitment. It was found that one transformational leadership dimension (articulating a vision), two job satisfaction dimensions (pay and supervision) and two organizational commitment dimensions (affective commitment and normative commitment) were significant regressors for organizational trust. There is a lack of research in the health organizations regarding organizational commitment, organizational trust, job satisfaction and transformational leadership. The investigator of the proposed study intends to add to the literature and intends to prove that the proposed study would be important for healthcare organizations. A number of specific measures should be undertaken to reduce factors that negatively affect organizational commitment, organizational trust and job satisfaction of hospital personnel and to improve transformational leadership behaviors of hospital administrators.
Top M
，Tarcan M
，Tekingündüz S
，Hikmet N
... -
《-》
A study of the nature and level of trust between patients and healthcare providers, its dimensions and determinants: a scoping review protocol.
The aim of this scoping review is to systematically search the literature to identify the nature and or level of trust between the patient, the users of health services (eg, clients seeking health promotion and preventive healthcare services) and the individual healthcare providers (doctors, nurses and physiotherapists/ occupational therapists), across public and private healthcare sectors, at all levels of care from primary through secondary to tertiary care. It also aims to identify the factors that influence trust between patients, users of health services (clients) and providers of healthcare at all levels of care from primary care to tertiary care, and across all health sectors (public and private). The study will also identify the tools used to measure trust in the healthcare provider.
The scoping review will be conducted based on the methodology developed by Arksey and O'Malley's scoping review methodology, and Levac et al 's methodological enhancement. An experienced information specialist (HM) searched the following databases MEDLINE, EMBASE, the Cochrane Library, Cumulative Index to Nursing and Allied Health Literature. The search terms were both keywords in the title and/or abstract and subject headings (eg, MeSH, EMTREE) as appropriate. Search results were downloaded, imported and stored into a 'Refworks' folder specifically created for reference management. The preliminary search was conducted between 7 December 2017 and 14 December 2017. Quantitative methods using content analysis will be used to categorise study findings on factors associated with trust between patients, clients and healthcare providers. The collection of studies will be also examined for heterogeneity. Qualitative analysis on peer reviewed articles of qualitative interviews and focus group discussion will be conducted; it allows clear identification of themes arising from the data, facilitating prioritisation, higher order abstraction and theory development. A consultation exercise with stakeholders may be incorporated as a knowledge translation component of the scoping study methodology.
Ethical approval will be obtained for the research project from the Institutional Review Board. The International Medical University will use the findings of this scoping review research to improve the understanding of trust in healthcare, in its endeavour to improve health services delivery in its healthcare clinics and hospitals, and in its teaching and learning curriculum. The findings will also help faculty make evidence based decisions to focus resources and research as well as help to advance the science in this area. Dissemination of the results of the scoping review will be made through peer-reviewed publications, research reports and presentations at conferences and seminars.
Rasiah S
，Jaafar S
，Yusof S
，Ponnudurai G
，Chung KPY
，Amirthalingam SD
... -
《BMJ Open》
ResearchGate
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钛学术
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