Maria Villalobos

The European Union Artificial Intelligence (AI) Act was adopted in 2024 to protect public interests from AI-related harms. We aimed to determine whether the AI Act captures the most relevant values of stakeholders (understood as any person potentially affected by the AI system, including, but not limited to, the direct users) related to a high-risk AI Clinical Decision Support System (CDSS) for cardiovascular disease. This system is intended to be implemented in primary care. A secondary analysis was carried out based on empirical data previously generated using ethics and design methodologies that had identified stakeholder values. These values were translated into the Trustworthy AI requirements of the High-Level Expert Group on AI and then contrasted with the AI Act. These requirements do not capture all identified stakeholder values. We describe three groups of untranslatable values and propose three additional complementary requirements. The AI Act mainly supports the requirements of human agency and oversight; transparency; and diversity, nondiscrimination, and fairness; but only partially, limited by its product safety nature. To address this gap, contractual strategies could provide a more legally robust ground for general practitioners to align the AI-CDSS with stakeholders’ values, comply with their duty of care, and promote trustworthy AI-CDSSs.

The beginning of university life can be a stressful event for students. The close social relationships that they can experience can have positive effects on their well-being. The objective of this paper is to estimate the effect of perceived social support on the changes of the hedonic and eudaimonic well-being of Chilean university students during the transition from the first to the second academic year. Overall, 205 students participated with an average age of 19.14 years, evaluated during their first academic year and the succeeding one. For the evaluation of perceived social support, the Spanish version of the Perceived Social Support Questionnaire “MSPSS” was used, and PERMA-profiler was used to measure hedonic and eudaimonic well-being. Changes through the time of hedonic well-being and social support and the correlations between the variables were analyzed. Changes in the perception of social support were analyzed according to four categories of hedonic well-being. The prediction of social support for eudaimonic well-being was evaluated. Results indicated that the perception of students’ social support did not change over time. Statistically significant differences were found in hedonic well-being scores in the two measurements, being significantly higher in the first measurement than in the second one. More than 50% of the participants presented a positive balance of affections. The perception of social support is associated with the two types of well-being. Students who had a high balance of affections had a greater perception of general social support than the groups of positive evolution of affections and a low balance of affections. In the case of the friends and family support dimensions, the perception in the high-balance group of affections concerning the low-scale group is greater. Improving the perception of social support increases the eudaimonic well-being of university students. The perception of support that students had during the beginning of their university life benefits their general well-being, which contributes to their mental health.

Introduction The paradigm shift to a knowledge‐based economy has incremented the use of personal information applied to health‐related activities, such as biomedical research, innovation, and commercial initiatives. The convergence of science, technology, communication and data technologies has given rise to the application of big data to health; for example through eHealth, human databases and biobanks. Methods In light of these changes, we enquire about the value of personal data and its appropriate use. In order to illustrate the complex ground on which big data applied to health develops, we analyse the current situation of the European Union and two cases: the Catalan VISC+/PADRIS and the UK Biobank, as perspectives. Discussion and conclusions Personal health‐related data in the context of the European Union is being increasingly used for big data projects under diverse schemes. There, public and private sectors participate distinctively or jointly, pursuing very different goals which may conflict with individual rights, notably privacy. Given that, this paper advocates for stopping the unjustified accumulation and commercialisation of personal data, protecting the interests of citizens and building appropriate frameworks to govern big data projects for health. A core tool for achieving such goals is to develop consent mechanisms which allow truly informed but adaptable consent, conjugated with the engagement of donors, participants and society.

The study explores communication strategies of ethno-nationalist terrorists with respect to their framing and identity building. Strategies of eight ethno-nationalist terrorist groups were analyzed using 70 articles published on the groups’ websites. Three cluster-analytic procedures and a correlational analysis were applied to (1) strategies of problem definition, (2) cause and responsibility attribution, (3) treatment recommendations, and (4) identity building. The analysis revealed various dimensions on which terrorists frame their content. No group-specific strategies of framing and identity building have been found yet, suggesting that the strategies were universal across terrorist groups, and they were applied on a case-by-case basis. Knowledge about these strategies should advance counter-terrorism efforts, and assist in development of alternative identities among ethnic groups at risk of conflict.