Ana Morais

Background Dementia care involves ethically complex situations across diverse clinical, social care, and policy contexts, yet practice-oriented ethical guidance remains limited. Existing ethical frameworks rarely capture the full complexity of practice across European contexts. This article presents the development and pilot external validation of an Ethical Framework for Decision-Making in Dementia Care, designed for professional caregivers. Methods Within COST Action CA21137 (Ethics in Dementia – EDEM), a multidisciplinary European consortium developed the framework through an iterative, deliberative, and consensus-seeking process involving workshops, online meetings, and adaptation of international bioethical norms. An exploratory and preliminary Content Validity Index (CVI) study with external experts assessed the framework’s relevance, clarity, simplicity, and applicability. Results The resulting principle-based framework provides non-prescriptive ethical guidance across domains including dignity, autonomy, consent, justice, solidarity, privacy, and public responsibility. The CVI assessment indicated adequate overall content validity (S-CVI/Ave = 0.85), with highest agreement for relevance (0.96) and lowest for applicability (0.75). Conclusions The EDEM-Framework offers a structured, exploratory, and practice-oriented contribution to clinical ethics in dementia care. It may strengthen ethical decision-making when supported by appropriate implementation strategies and ethics infrastructures.

Aggregating snippets from the semantic memories of many individuals may not yield a good map of an individual’s semantic memory. The authors analyze the structure of semantic networks that they sampled from individuals through a new snowball sampling paradigm during approximately 6 weeks of 1-hr daily sessions. The semantic networks of individuals have a small-world structure with short distances between words and high clustering. The distribution of links follows a power law truncated by an exponential cutoff, meaning that most words are poorly connected and a minority of words has a high, although bounded, number of connections. Existing aggregate networks mirror the individual link distributions, and so they are not scale-free, as has been previously assumed; still, there are properties of individual structure that the aggregate networks do not reflect. A simulation of the new sampling process suggests that it can uncover the true structure of an individual’s semantic memory