KJC Korea
Journal Central

In France, public debates and discussions concerning euthanasia began over 20 years with the introduction of palliative care and acceptance of a patient’s right to discontinue life-sustaining treatment. More recent legislation in France allows deep and continuous sedation until death for terminally ill patients who are in extreme pain. The trend in France has been a trend toward greater access to palliative care and a more expansive set of rights and freedoms for patients approaching the end of life. This article summarizes the recent history of French legislation concerning euthanasia and argues that guiding objective in these legislative changes has been formal recognition, not of a patient’s right to die, but of a patient’s right to die without pain. In the conflict between the right to die and the right to life, the French have prioritized the former because what they desire, above all else, is the right to avoid suffering.

This article discusses the case of an elderly patient with a severe stroke for whom hemicraniectomy was proposed to lower intracranial pressure. Although patients in this situation can increase their chances of survival with hemicraniectomy, expected quality of life following the procedure remains uncertain. This case is analyzed using the four topics chart, which consists of medical indication, patient preference, quality of life, and contextual features. In relation to contextual features, the conflict of interest experienced by the family as caregivers and the influence of the Life-Sustaining Treatment Decision-making Act are discussed. It is argued that in order to make medical decisions that are in the patient’s best interest, shared decision-making between physicians and family members should be based on information obtained through the four topics chart.

The use of artificial intelligence (AI) in healthcare settings has become increasingly common. Many hope that AI will remove constraints on human and material resources and bring innovations in diagnosis and treatment. However, the deep learning techniques and resulting black box problem of AI raise important ethical concerns. To address these concerns, this article explores some of the relevant ethical domains, issues, and themes in this area and proposes principles to guide use of AI in healthcare. Three ethical themes are identified, including respect for person, accountability, and sustainability, which correspond to the three domains of data acquisition, clinical setting, and social environment. These themes and domains were schematized with detailed explanations of relevant ethical issues, concepts, and applications, such as explainability and accountability. Additionally, it is argued that conflicts between ethical principles should be resolved through deliberative democratic methods and a consensus building process.

This article reports on a study that examined thematic trends in published research, in Korea and abroad, on moral distress in nursing. After extracting English abstracts from 38 domestic and 159 foreign publications, degreecentrality analysis and topic modeling were performed using the NetMiner 4 program. The common core keywords found in the domestic and international abstracts are “nurse, moral distress, moral sensitivity, intensive care unit, end-of-life care, experience, burnout, and care.” The core keywords in the domestic abstracts are “education program, person-centered care, job satisfaction, empowerment, hospital, long-term care facility, nursing practice environment, nursing student, turnover intention, clinical nursing practice, and emergency.” The core keywords in the international abstracts are “patient, family, healthcare provider, palliative care, decision-making, ethical issue, child, dementia patient, management, person, life, and staff.” Topic modeling found three topics that are common to both domestic and international abstracts and two topics that differ. This study suggests that although there are common core subject areas in both domestic and international research, some subject areas are studied more actively abroad and require the attention of domestic researchers.

The purpose of this study was to identify the factors affecting ethical competence in nurses. This study was conducted a cross-sectional descriptive design with a convenience sample of 100 nurses from a university affiliated hospital in Seoul. The study collected data on items drawn from CENAS (The Clinical Ethics Need Assessment Survey), ethics education needs, ethical confidence, moral sensitivity, and ethical competence. The data were analyzed using descriptive statistics, a t-test, a one-way ANOVA, correlation analysis, and multiple linear regression analysis with SPSS Win 21 program. The results indicate that the main factor influencing nurses’ ethical competence is as ethical confidence (β = .53), which accounted for 42.0% of variance. These results suggest development of ethical education program for nurses for improving nurses’ ethical capabilities.