Compassion in Healthcare

2020 ◽  
Author(s):  
Joshua Hordern
Keyword(s):  
Machine Learning ◽  
Healthcare Workers ◽  
Religious Diversity ◽  
Human Condition ◽  
Political Life ◽  
Civic Life ◽  
Burn Out ◽  
Healthcare Practice ◽  
Pass Through ◽  
The Life Course

This book gives an account of the nature and content of compassion and its role in healthcare. The argument considers how and why contested beliefs about political life, suffering, the human condition, time, and responsibility make a difference to ‘compassion’. While compassion appears to be a straightforward aspect of life and practice, the appearance is deceptive. Compassion is plagued by both conceptual and practical ills and needs some quite specific kinds of therapy. The first step therefore is to diagnose precisely what is wrong with ‘compassion’ including its debilitating political entanglements, the vagueness of its meaning and the risk of burn-out it threatens. With diagnosis in hand, three therapies are prescribed for compassion’s ills: (i) an understanding of patients and healthcare workers as those who pass through the life-course, encountering each other as wayfarers and pilgrims; (ii) a grasp of the nature of compassion in healthcare; and (iii) an embedding of healthcare within the realities of civic life. With this therapy applied, the argument shows how compassionate relationships acquire their content in healthcare practice. First, the form that compassion takes is shown to depend on how different doctrines of time, tragedy, salvation, responsibility, fault, and theodicy set the terms of people’s lives and relationships. Second, how such compassion matters to practice and policy is worked out in the detail of healthcare professionalism, marketisation, and technology, drawing on the author’s collaborations. Covering everything from conception to old age, and from machine learning to religious diversity, this book draws on philosophy, theology, and everyday experience to stretch the imagination of what compassion might mean in healthcare practice.

What’s Wrong with ‘Compassion’?

2020 ◽  
pp. 24-52
Author(s):  
Joshua Hordern
Keyword(s):  
Machine Learning ◽  
Frail Elderly ◽  
Healthcare Workers ◽  
Political Liberalism ◽  
The Political ◽  
Complex Relationship ◽  
Liberal Democracies ◽  
Social Death ◽  
Burn Out ◽  
Healthcare Practice

This chapter diagnoses various ills which beset the language and practice of ‘compassion’. To begin with, problems in the political context for compassion in healthcare are considered, especially the complex relationship between patriotism, political liberalism, and health. In light of this, problems for compassion which require therapy are diagnosed. To some people, compassion seems an unreasonable demand to place on healthcare workers in modern, liberal democracies. This seems to be corroborated by the indeterminacy of compassion’s meaning, leading to a corruption in practice whereby compassion becomes acquiescence to the wishes of sufferers. Moreover, placing a demand for compassion upon healthcare workers seems liable to lead to burn-out. Two contrasting trends in healthcare practice exacerbate problems for compassion further: first, the possible decomposition of healthcare roles in light of machine learning, stripping out previous expectations for compassionate relationships, and, second, the overwhelming challenge of social death among the frail elderly.

Contextual Integrity Up and Down the Data Food Chain

2019 ◽  
Vol 20 (1) ◽  
pp. 221-256 ◽  
Author(s):  
Helen Nissenbaum
Keyword(s):  
Machine Learning ◽  
Food Chain ◽  
Lower Order ◽  
Higher Order ◽  
Learning Systems ◽  
Civic Life ◽  
Information Flows ◽  
Contextual Integrity ◽  
Information Type ◽  
Motion Detectors

Abstract According to the theory of contextual integrity (CI), privacy norms prescribe information flows with reference to five parameters — sender, recipient, subject, information type, and transmission principle. Because privacy is grasped contextually (e.g., health, education, civic life, etc.), the values of these parameters range over contextually meaningful ontologies — of information types (or topics) and actors (subjects, senders, and recipients), in contextually defined capacities. As an alternative to predominant approaches to privacy, which were ineffective against novel information practices enabled by IT, CI was able both to pinpoint sources of disruption and provide grounds for either accepting or rejecting them. Mounting challenges from a burgeoning array of networked, sensor-enabled devices (IoT) and data-ravenous machine learning systems, similar in form though magnified in scope, call for renewed attention to theory. This Article introduces the metaphor of a data (food) chain to capture the nature of these challenges. With motion up the chain, where data of higher order is inferred from lower-order data, the crucial question is whether privacy norms governing lower-order data are sufficient for the inferred higher-order data. While CI has a response to this question, a greater challenge comes from data primitives, such as digital impulses of mouse clicks, motion detectors, and bare GPS coordinates, because they appear to have no meaning. Absent a semantics, they escape CI’s privacy norms entirely.

Investigating Psychological Differences between Nurses and Other Healthcare Workers from Asia-Pacific Region during the Early Phase of the Coronavirus Disease 2019 (COVID-19): A Machine Learning Approach (Preprint)

2021 ◽  
Author(s):  
YanHong Dong ◽  
Mei Chun Yeo ◽  
Mei Chun Yeo ◽  
Rivan Danuaji ◽  
Thang H Nguyen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Psychological Distress ◽  
Healthcare Workers ◽  
Psychological Impact ◽  
Asia Pacific ◽  
Pacific Region ◽  
Asia Pacific Region ◽  
Psychological Outcome ◽  
Psychological Differences ◽  
Medical Healthcare

BACKGROUND As the pandemic evolves, frontline work challenges continue to impose significant psychological impact on nurses. However, there is a lack of data how nurses fared compared to other healthcare workers in Asia-Pacific region. OBJECTIVE This study aims to investigate 1) psychological differences between nurses, doctor and non-medical healthcare workers, and 2) psychological outcome characteristics of nurses from different Asia-Pacific countries. METHODS Decision-tree type machine learning models (LIghtGBM, Gradientboost, and RandomForest) were adopted to predict psychological impact on nurses. The SHAP (SHapley Additive exPlanations) values of these models were extracted to identify the distinctive psychological distress characteristic. RESULTS Nurses had relatively higher percentages of normal or no-change in psychological distress symptoms relative to other healthcare workers (86.3% - 96.8% vs 80.7% - 92.3%). Among those without psychological symptoms, nurses constituted a higher proportion than doctors and non-medical healthcare workers (40.8%, 25.8%, and 33.4%, respectively). CONCLUSIONS Different contexts, cultures, and points in pandemic curve may have contributed to differing patterns of psychological outcomes amongst nurses in various Asia-Pacific countries. It is important that all healthcare workers practise self-care and render peer support to bolster psychological resilience for effective coping. CLINICALTRIAL Not applicable

Introduction

2020 ◽  
pp. 1-23
Author(s):  
Joshua Hordern
Keyword(s):  
Social Theory ◽  
Political Context ◽  
Human Condition ◽  
The Political ◽  
Cautionary Tale ◽  
Healthcare Practice ◽  
The Human Condition

This chapter situates the enquiry by considering the transitions which healthcare practice is undergoing because of turns in healthcare thinking towards philosophy, person-centredness, and social theory. Such changes accentuate a problem inherent in other trends in modern healthcare which have tended to reduce the scope for exploring the human condition and morally worthy ways of living life within it. The historic response of Christian ethicists to such transitions and trends is reviewed as a kind of cautionary tale which, by distinguishing different theological approaches, discloses the contested nature of an enquiry such as this. Options for the proper mode of the enquiry are thereby considered, with an argument made for a version of ‘faithful secularity’ being predominant, drawing on Nigel Biggar and Luke Bretherton, while incorporating other insights. The structure of the book is then outlined, the political context is introduced, some distinctions are highlighted, and a guide to reading is offered.

scholarly journals Healthcare workers’ legal liability and immunity during the COVID-19 pandemic

2020 ◽  
pp. 1-8
Author(s):  
Nasser Hammad Al-Azri
Keyword(s):  
Public Good ◽  
Healthcare System ◽  
Disaster Response ◽  
Healthcare Workers ◽  
Healthcare Professionals ◽  
Legal Liability ◽  
Working Environment ◽  
The Public ◽  
Healthcare Workforce ◽  
Healthcare Practice

Abstract The COVID-19 pandemic is the most unprecedented crisis facing modern healthcare governance in a century. Many healthcare activities are attracting scrutiny from ethical and legal perspectives. Therefore, healthcare professionals are concerned about legal ambiguity regarding legal liability and immunity in their areas of practice. Law is a key response activity that promotes a sense of safety and security among healthcare workers. This article describes why it is important formally to address issues of altered operations in healthcare practice during emergencies. Furthermore, this article provides suggestions regarding solutions to the issue of legal liability during disasters. Implementing ethical and legal clarity during disaster response is a necessity for a strong healthcare system at every level from international to local in order to achieve a stable healthcare workforce operating for the public good within a safe and secure working environment.

Doctors, Politics and Pay Disputes: ‘pressure Group Politics’ Revisited

1972 ◽  
Vol 2 (4) ◽  
pp. 421-442 ◽  
Author(s):  
Theodore R. Marmor ◽  
David Thomas
Keyword(s):  
Public Policy ◽  
Medical Association ◽  
Political Life ◽  
The Political ◽  
Civic Life ◽  
The Third ◽  
Internal Politics ◽  
Medical Groups ◽  
Group Politics ◽  
The Impact

Studies of medical politics usually emphasize one of the following types of inquiries: (a) analyzing the internal politics of medical organizations, as with Oliver Garceau's classic study of the American Medical Association; (b) describing and explaining the roles individual physicians play in the political life of the community as voters, officials, or citizen participants in civic life; or, (c) assessing the impact of medical groups and organizations on public policy, particularly health policy. Harry Eckstein's widely known study of the British Medical Association is primarily a study of the third type, a discussion of the channels of influence, the tactics, and the effectiveness of the BMA in shaping public policy to its ends.

Time, Scheduling and Cinema-Going

2011 ◽  
Vol 139 (1) ◽  
pp. 88-95 ◽  
Author(s):  
Mark Jancovich
Keyword(s):  
Life Course ◽  
Social Contexts ◽  
Social Activities ◽  
Historical Time ◽  
Change Over Time ◽  
Time Scheduling ◽  
Consumption Change ◽  
Pass Through ◽  
The Life Course ◽  
Over Time

The article considers the ways in which the meanings of film consumption are shaped by their timing or scheduling within people's lives. It begins by considering the ways in which these meanings are shaped in relation to historical time, and how the meanings of film consumption change over time. It then moves on to consider the ‘life course’, or the ways in which meanings of film consumption are affected by the different stages that people pass through across a lifetime. Finally, the article considers more cyclical patterns and routines such as those of the year, week and day. In the process, it seeks to demonstrate that film consumption is about much more than the interpretation of individual programs, and involves a series of social activities that are meaningful within broader social contexts.

scholarly journals Protecting the front line: a cross-sectional survey analysis of the occupational factors contributing to healthcare workers’ infection and psychological distress during the COVID-19 pandemic in the USA

BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e042752 ◽  
Author(s):  
Tsion Firew ◽  
Ellen D Sano ◽  
Jonathan W Lee ◽  
Stefan Flores ◽  
Kendrick Lang ◽  
...  
Keyword(s):  
Mental Health ◽  
Psychological Distress ◽  
Healthcare Workers ◽  
Anxiety Symptoms ◽  
Front Line ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Convenience Sample ◽  
Burn Out ◽  
The Usa

ObjectiveThe COVID-19 pandemic has been associated with significant occupational stressors and challenges for front-line healthcare workers (HCWs), including COVID-19 exposure risk. Our study sought to assess factors contributing to HCW infection and psychological distress during the COVID-19 pandemic in the USA.DesignWe conducted a cross sectional survey of HCWs (physicians, nurses, emergency medical technicians (EMTs), non-clinical staff) during May 2020. Participants completed a 42-item survey assessing disease transmission risk (clinical role, work environment, availability of personal protective equipment) and mental health (anxiety, depression and burn-out).SettingThe questionnaire was disseminated over various social media platforms. 3083 respondents from 48 states, the District of Columbia and US territories accessed the survey.ParticipantsUsing a convenience sample of HCWs who worked during the pandemic, 3083 respondents accessed the survey and 2040 participants completed at least 80% of the survey.Primary outcomePrevalence of self-reported COVID-19 infection, in addition to burn-out, depression and anxiety symptoms.ResultsParticipants were largely from the Northeast and Southern USA, with attending physicians (31.12%), nurses (26.80%), EMTs (13.04%) with emergency medicine department (38.30%) being the most common department and specialty represented. Twenty-nine per cent of respondents met the criteria for being a probable case due to reported COVID-19 symptoms or a positive test. HCWs in the emergency department (31.64%) were more likely to contract COVID-19 compared with HCWs in the ICU (23.17%) and inpatient settings (25.53%). HCWs that contracted COVID-19 also reported higher levels of depressive symptoms (mean diff.=0.31; 95% CI 0.16 to 0.47), anxiety symptoms (mean diff.=0.34; 95% CI 0.17 to 0.52) and burn-out (mean diff.=0.54; 95% CI 0.36 to 0.71).ConclusionHCWs have experienced significant physical and psychological risk while working during the COVID-19 pandemic. These findings highlight the urgent need for increased support for provider physical and mental health well-being.

scholarly journals Vulnerability and Protective Factors for PTSD and Depression Symptoms Among Healthcare Workers During COVID-19: A Machine Learning Approach

2022 ◽  
Vol 12 ◽  
Author(s):  
Liana C. L. Portugal ◽  
Camila Monteiro Fabricio Gama ◽  
Raquel Menezes Gonçalves ◽  
Mauro Vitor Mendlowicz ◽  
Fátima Smith Erthal ◽  
...  
Keyword(s):  
Mental Health ◽  
Machine Learning ◽  
Social Isolation ◽  
Healthcare Workers ◽  
Intervention Programs ◽  
Depression Symptoms ◽  
Learning Approach ◽  
Professional Recognition ◽  
Machine Learning Approach

Background: Healthcare workers are at high risk for developing mental health problems during the COVID-19 pandemic. There is an urgent need to identify vulnerability and protective factors related to the severity of psychiatric symptoms among healthcare workers to implement targeted prevention and intervention programs to reduce the mental health burden worldwide during COVID-19.Objective: The present study aimed to apply a machine learning approach to predict depression and PTSD symptoms based on psychometric questions that assessed: (1) the level of stress due to being isolated from one's family; (2) professional recognition before and during the pandemic; and (3) altruistic acceptance of risk during the COVID-19 pandemic among healthcare workers.Methods: A total of 437 healthcare workers who experienced some level of isolation at the time of the pandemic participated in the study. Data were collected using a web survey conducted between June 12, 2020, and September 19, 2020. We trained two regression models to predict PTSD and depression symptoms. Pattern regression analyses consisted of a linear epsilon-insensitive support vector machine (ε-SVM). Predicted and actual clinical scores were compared using Pearson's correlation coefficient (r), the coefficient of determination (r2), and the normalized mean squared error (NMSE) to evaluate the model performance. A permutation test was applied to estimate significance levels.Results: Results were significant using two different cross-validation strategies to significantly decode both PTSD and depression symptoms. For all of the models, the stress due to social isolation and professional recognition were the variables with the greatest contributions to the predictive function. Interestingly, professional recognition had a negative predictive value, indicating an inverse relationship with PTSD and depression symptoms.Conclusions: Our findings emphasize the protective role of professional recognition and the vulnerability role of the level of stress due to social isolation in the severity of posttraumatic stress and depression symptoms. The insights gleaned from the current study will advance efforts in terms of intervention programs and public health messaging.

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