Staff compassion in acute mental health wards: a grounded theory investigation.

BACKGROUND: Staff working on acute inpatient mental health wards face unique challenges in terms of short admissions, acuity, complexity and exposure to violence, suicide and self-harm. They experience high levels of stress and burnout, which can impact compassion. AIM: To qualitatively explore staff's understanding and conceptualisation of the development, loss and restoration of compassion within acute inpatient environments. METHOD: Eleven participants from a variety of professional backgrounds currently working on acute wards were interviewed. Using constructivist grounded theory, data were synthesised into theoretical categories and sub-categories. RESULTS: A conceptual model of the facilitators and inhibitors of compassionate care was developed, based on five categories that emerged from the data: A compassionate stance; the challenges of acute wards; feeling under threat; restoring compassion; and a compassionate organisation. CONCLUSIONS: Findings outline the process whereby staff compassion can be challenged or depleted, leading to a negative appraisal of the patient. Colleague support, knowing and understanding patients, and accessing a reflective space all supported the restoration of compassion. Staff reported lack of organisational compassion influenced their ability to maintain a compassionate stance. The importance of appropriate training and support structures is discussed, alongside recommendations to support the development of compassionate acute mental health care.

Healthcare at the Crossroads: The Need to Shape an Organizational Culture of Humanistic Teaching and Practice.

BACKGROUND: Changes in the organization of medical practice have impeded humanistic practice and resulted in widespread physician burnout and dissatisfaction. OBJECTIVE: To identify organizational factors that promote or inhibit humanistic practice of medicine by faculty physicians. DESIGN: From January 1, 2015, through December 31, 2016, faculty from eight US medical schools were asked to write reflectively on two open-ended questions regarding institutional-level motivators and impediments to humanistic practice and teaching within their organizations. PARTICIPANTS: Sixty eight of the 92 (74%) study participants who received the survey provided written responses. All subjects who were sent the survey had participated in a year-long small-group faculty development program to enhance humanistic practice and teaching. As humanistic leaders, subjects should have insights into motivating and inhibiting factors. APPROACH: Participants' responses were analyzed using the constant comparative method. KEY RESULTS: Motivators included an organizational culture that enhances humanism, which we judged to be the overarching theme. Related themes included leadership supportive of humanistic practice, responsibility to role model humanism, organized activities that promote humanism, and practice structures that facilitate humanism. Impediments included top down organizational culture that inhibits humanism, along with related themes of non-supportive leadership, time and bureaucratic pressures, and non-facilitative practice structures. CONCLUSIONS: While healthcare has evolved rapidly, efforts to counteract the negative effects of changes in organizational and practice environments have largely focused on cultivating humanistic attributes in individuals. Our findings suggest that change at the organizational level is at least equally important. Physicians in our study described the characteristics of an organizational culture that supports and embraces humanism. We offer suggestions for organizational change that keep humanistic and compassionate patient care as its central focus.

Artificial intelligence technologies and compassion in healthcare: A systematic scoping review.

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.

Views of institutional leaders on maintaining humanism in today's practice.

OBJECTIVE: To explore leadership perspectives on how to maintain high quality efficient care that is also person-centered and humanistic. METHODS: The authors interviewed and collected narrative transcripts from a convenience sample of 32 institutional healthcare leaders at seven U.S. medical schools. The institutional leaders were asked to identify factors that either promoted or inhibited humanistic practice. A subset of authors used the constant comparative method to perform qualitative analysis of the interview transcripts. They reached thematic saturation by consensus on the major themes and illustrative examples after six conference calls. RESULTS: Institutional healthcare leaders supported vision statements, policies, organized educational and faculty development programs, role modeling including their own, and recognition of informal acts of kindness to promote and maintain humanistic patient-care. These measures were described individually rather than as components of a coordinated plan. Few healthcare leaders mentioned plans for organizational or systems changes to promote humanistic clinician-patient relationships. CONCLUSIONS: Institutional leaders assisted clinicians in dealing with stressful practices in beneficial ways but fell short of envisaging systems approaches that improve practice organization to encourage humanistic care. PRACTICE IMPLICATIONS: To preserve humanistic care requires system changes as well as programs to enhance skills and foster humanistic values and attitudes.

Compassion Is a Necessity and an Individual and Collective Responsibility Comment on "Why and How Is Compassion Necessary to Provide Good Quality Healthcare?".

Compassion is a complex process that is innate, determined in part by individual traits, and modulated by a myriad of conscious and unconscious factors, immediate context, social structures and expectations, and organizational "culture." Compassion is an ethical foundation of healthcare and a widely shared value; it is not an optional luxury in the healing process. While the interrelations between individual motivation and social structure are complex, we can choose to act individually and collectively to remove barriers to the innate compassion that most healthcare professionals bring to their work. Doing so will reduce professional burnout, improve the well-being of the healthcare workforce, and facilitate our efforts to achieve the triple aim of improving patients' experiences of care and health while lowering costs.

Can compassionate healthcare be measured? The Schwartz Center Compassionate Care Scale™.

OBJECTIVE: Assess psychometric characteristics of an instrument to measure patient ratings of treating physicians' compassionate care in a recent hospitalization. METHODS: We used Cronbach's alpha to examine scale reliability, exploratory and confirmatory factor analysis to examine scale structure of two sets of items on compassionate care. We used Mokken analysis to determine if items in each set belonged to a unidimensional scale. RESULTS: Results indicated that both sets of items had strong reliability when used to rate individual physicians (Cronbach's α=.97 and .95). A one factor model was a good fit to both sets of items. Mokken analysis supported unidimensional scales. Both sets of items correlated with an overall measure of patient satisfaction with physicians and even more strongly with an item measuring emotional support. CONCLUSIONS: A patient-rated scale reliably measured hospital physicians' compassion and correlated significantly with an item measuring overall patient satisfaction and a specific measure of satisfaction with emotional support. Measurement of compassionate healthcare should be included in research, educational assessment, and quality improvement programs. PRACTICE IMPLICATIONS: Clinicians should participate in efforts to enhance their ability to demonstrate compassionate care including eliciting and sharing information and acting collaboratively to ameliorate patients' socioemotional concerns and needs.