BMC Medical Ethics最新文献

Background: As dementia progresses, individuals with Alzheimer's disease and related forms of dementia often lose decision-making capacity, raising complex ethical challenges related to autonomy, surrogate decision-making, dignity, privacy, and justice. This review examines the dilemmas in caring for patients who are no longer capable of providing informed consent, comparing Lebanon's situation with those of countries across the Global North and South, and proposes practical, culturally grounded recommendations for improvement.

Objective: To conduct a comprehensive thematic review comparing international practices with Lebanon's ethical, legal, and institutional approaches to caring for individuals with advanced dementia who lack capacity.

Methods: A systematic yet flexible review approach, guided by the PRISMA framework, was applied. Studies focusing on Alzheimer's disease and other related dementias were retrieved from PubMed, Scopus, PsycINFO, Web of Science, and the Cochrane Library up to April 2025. A total of 121 studies, including 112 international and 9 from Lebanon, met the inclusion criteria. These included qualitative, quantitative, and policy sources. Studies were thematically analyzed for ethical relevance across five themes.

Results: Five major ethical themes emerged: surrogate decision-making, patient autonomy, surveillance and technology, legal frameworks, and cultural and economic factors. A clear North-South divide was observed, with countries in the Global North generally relying on formal legal safeguards, advance directives, and structured institutional ethics oversight. In contrast, Lebanon and comparable countries in the Global South often operated with informal, family-centered models, limited legal clarity, and minimal institutional ethics support.

Conclusion: Lebanon reflects broader Global South patterns: strong familial caregiving traditions, but inadequate legal and institutional frameworks to ensure dignity-based, ethically consistent care. This review proposes culturally sensitive reforms in law, public education, and ethics infrastructure to better protect the rights and dignity of individuals with advanced dementia.

Background: A majority of AI ethics frameworks focus on high-level principles but lack actionable guidance. Effectively implementing AI in projects requires the operationalization of AI ethics, translating principles into requirements. This paper proposes a novel method for operationalizing AI ethics through co-creation workshops.

Methods: The study adopted a qualitative, participatory research approach. Stakeholders from the VALIDATE project, a Horizon Europe action developing an AI-based clinical decision support system for stroke patient stratification, were divided into five diverse teams. The workshops aimed to: (i) determine the low-level ethical requirements stakeholders considered essential for the project, and (ii) identify requirements not included in the EU Trustworthy AI Guidelines. The methodology included storytelling, content analysis to identify ethical issues and dilemmas, eliciting quantifiable requirements using a standardized planning language (Planguage), and a procedural feedback process.

Results: The workshops identified explainability, privacy, model robustness, model validity, epistemic authority, fairness, and transparency as key ethical issues. Participants drafted low-level requirements related to privacy, explainability, transparency, and validity. Six issues (time sensitivity, validity, prevention of harm to patients, patient-inclusive care, quality of life, and lawsuit prevention) could not be mapped to the EU Guidelines. Participants did not draft requirements in relation to the latter issues. Challenges included the diverse interpretations of concepts, such as validity. Participants generally had favorable impressions of the workshops, although they found formulating requirements in Planguage format more challenging than storytelling and topic prioritization.

Conclusions: The workshops elicited concrete, quantifiable, and actionable requirements, which were useful in developing a project-specific ethical framework. The proposed methodology is resource-efficient and requires fewer AI ethics experts than existing methods while remaining compatible with established guidelines. Procedural feedback results suggest that participants and facilitators would benefit from additional training in the use of Planguage. Potential challenges included the impact of power dynamics among participants on discussions, blind spots due to overlooked issues, and the absence of stroke patients among the participants.

Background: Intensive care unit (ICU) admissions among older patients are increasing, posing significant challenges to already strained healthcare systems. Decision-making around ICU admission in times of limited resources may provide important knowledge about difficult prioritisations, particularly for older patients. Thus, the aim was to investigate ICU-admission decisions for older patients with COVID-19.

Methods: A mixed-methods approach. We audio-recorded ten COVID Rounds and nine Moral Case Deliberations for 34 patients across three Swedish hospitals during the pandemic, and collected data from medical records of 329 patients aged ≥ 65 diagnosed with COVID-19. Data were analysed using qualitative content analysis and multiple regression.

Results: Among 239 patients with documented decisions in medical records, 56% included explicit justifications. The justifications included considerations of medical benefit (not-too- ill/too-ill), general condition (good/frail), age (not-too-old/high age), professional duty (benefit of the doubt/do no harm) and "worth giving it a go" (grit and will to live/lack of will and coping). A minority (31%) of decisions favoured ICU admission. Justifications supporting admission were predominantly drawn from discussions in COVID Rounds and MCDs, where patient grit was a recurring argument. In regression analyses, age ≥ 80 years was the only factor significantly associated with not being admitted to ICU and having a documented justification. Few decisions explicitly referred to COVID-19-specific factors.

Conclusion: Our findings reflect patterns similar to pre-pandemic ICU decision-making, suggesting continuity in clinical reasoning. However, the limited documentation of justifications-especially in favour of admission-warrants attention, emphasising the need for clearer reasoning in medical records. Our findings identify chronological age as a key triage factor, normatively supported by the ethical principles of non-maleficence, justice, and Sweden's legal priority-setting principle of Needs and Solidarity-which emphasises care only when benefit is likely. We therefore advocate for national (and potentially international) guidance on triage systems that support a palliative approach for very old patients. While grit may be relevant to ICU admission due to its link to potential benefit, its use raises ethical concerns, particularly in relation to Needs and Solidarity and Human Dignity. We recommend its cautious application pending further research.

Purpose: Current literature seldom discusses the functions and duties of individuals participating in medical research and the importance they attribute to their research involvement. To fill this void, our study investigated participants' perceptions of their roles and responsibilities in the research context and compared these perceptions with those of research staff.

Methods: A cross-section qualitative study with 21 semi-structured interviews with participants purposefully selected from clinical and non-clinical trials, and research staff. We also conducted two focus group discussions: one with participants from clinical trials and one from non-clinical trials. We analysed data using thematic analysis methods.

Results: The responsibilities of research participants are understood differently between research participants and research staff. Two broad themes emerged from the findings: relational responsibilities of research participants and functional responsibilities of participants.

Conclusion: There are differences in perceived responsibilities between researchers and participants, and this disconnect needs to be recognised. Researchers should focus on how best to communicate responsibilities to enhance awareness and achieve mutual understanding.

Background: Chronic Kidney Disease affects 13% of China's population, with hemodialysis consuming 1-3% of national healthcare expenditure. Hemodialysis patients face complex physical-psychological burdens, while physicians in Traditional Chinese Medicine (TCM) hospitals navigate unique ethical dilemmas arising from dual Western-TCM practice paradigms, cultural expectations, and systemic healthcare pressures. This study employed Social-Ecological Systems Theory to analyze these multilayered challenges and developed a structured ethical model.

Methods: This study followed a qualitative phenomenological research design. Maximum variation purposive sampling was employed to recruit 28 hemodialysis physicians from six TCM hospitals across five cities in Shandong Province, China. Data were collected through focus group and in-depth individual interviews with 28 hemodialysis physicians from November 2024 to January 2025, and were analyzed following Colaizzi's descriptive analysis framework. The framework of the Society Ecosystems Theory was applied to analyze how multilevel systemic interactions shape ethical challenges, thereby constructing a multidimensional conceptual model.

Results: Ethical challenges encountered by hemodialysis physicians were categorized into three themes with seven subthemes and 17 subcategories. Based on these findings, a three-tiered model was developed: macro-system challenges involving policy, organizational, and cultural dimensions; meso-system challenges emerging from interprofessional dynamics, particularly doctor-doctor, doctor-nurse, and doctor-patient relationships; and micro-system challenges pertaining to individual difficulties.

Conclusion: The conceptual model reveals the multi-level nature of ethical challenges in hemodialysis practice, spanning systemic policies, interprofessional relationships, and individual dilemmas. The findings specifically call for targeted interventions at each level: policy reforms to address resource constraints, team-based strategies to improve clinical collaborations, and support systems to alleviate practitioners' ethical distress. These evidence-based insights empower stakeholders to develop comprehensive solutions addressing the interconnected challenges identified.

Background: Artificial intelligence (AI) offers significant potential to drive advancements in healthcare; however, the development and implementation of AI models present complex ethical, legal, social, and technical challenges, as data practices often undermine regulatory frameworks in various regions worldwide. This study explores stakeholder perspectives on the development and deployment of AI algorithms for diabetic retinopathy (DR) screening, with a focus on ethical risks, data practices, governance, and emerging shortcomings in the Global South AI discourse.

Methods: Fifteen semi-structured interviews were conducted with ophthalmologists, program officers, AI developers, bioethics experts, and legal professionals. Thematic analysis was guided by OECD principles for responsible AI stewardship. Interviews were analyzed using MAXQDA software to identify themes related to AI trustworthiness and ethical governance.

Results: Six key themes emerged regarding the perceived trustworthiness of AI: algorithmic effectiveness, responsible data collection, ethical approval processes, explainability, implementation challenges, and accountability. Participants reported critical shortcomings in AI companies' data collection practices, including a lack of transparency, inadequate consent processes, and limited patient awareness about data ownership. These findings highlight how unchecked data collection and curation practices may reinforce data colonialism in low and middle-income healthcare systems.

Conclusion: Ensuring trustworthy AI requires transparent and accountable data practices, robust patient consent mechanisms, and regulatory frameworks aligned with ethical and privacy standards. Addressing these issues is vital to safeguarding patient rights, preventing data misuse, and fostering responsible AI ecosystems in the Global South.

Background: Workplace dignity is a fundamental ethical concern in nursing, directly related to professional identity, human rights, and the moral foundations of care. Despite increasing global attention, few qualitative studies have explored how nurses themselves perceive and articulate workplace dignity, particularly within sociocultural contexts marked by rapid healthcare transformation.

Methods: This qualitative study was conducted in January 2025 at a tertiary hospital in Hangzhou, China. Sixteen registered nurses were recruited through purposive sampling and interviewed using semi-structured face-to-face interviews. Data were analyzed using Colaizzi's method.

Results: Nurses described workplace dignity as a subjective experience shaped by respect, equality, and recognition of self-worth. Influencing factors included sociodemographic characteristics, patient-related factors, organizational factors, and social factors.

Conclusion: Workplace dignity is dynamic and socially constructed. Enhancing dignity requires supportive management, fair compensation, positive workplace culture, and improved societal recognition of the nursing profession.