1,721,982 research outputs found

    Understanding the impact of Artificial Intelligence on physician-patient relationship: a revisitation of conventional relationship models in the light of new technological frontiers

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    The physician-patient relationship has undergone a transition throughout the ages. The introduction of Artificial Intelligence (AI) in recent years, however, is redefining this relationship. The four main relationship models described by Emanuel in 1992 are known as paternalistic, informative, interpretive, and deliberative. The aim of this study is to understand how conventional models of doctor-patient relationships are changing when considering the impact AI has on medical practice. The introduction of AI could strengthen the physician’s role resulting in the so-called digital paternalism or even undermining the physician’s role. Also, doctors and patients could experience decision paralysis when AIs’ recommendations are difficult to understand or explain to patients and it may affect the organizational aspects of healthcare contexts. It becomes necessary to define the source of the information presented to the patient. On another hand, AI could increase the patient’s trust in the doctor by knowing that various therapeutic choices are being discussed and fully explained. It’s complicated to understand whether the trust relationship established between doctor and patient remains bi-univocal, by incorporating AI in the clinician’s figure, or whether AI must be introduced as a separate entity implying an asymmetry in this relationship. Shared decision-making, guidelines and training, together with an effort in communication are fundamental to best incorporate AI into clinical practice. It is relevant to educate doctors on the new models of relationships that can be created, in addition to studying patient populations within the context of these models’ framework

    The ECOLHE Erasmus + Project and the University to the Test of Digital Teaching and Learning: The Italian Case

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    The pandemic emergency has underscored the critical need for universities to accelerate their digital transformation to support proper teaching and learning processes. This paper presents findings from the Italian component of a broader international research project, which investigates the transformative impact of the digital revolution on Higher Education, under the umbrella of the Bologna Process, promoted by the European Community since 1999, to push the valorisation of Information and Communication Technologies to support the increasing needs of lifelong learning in the learning economy. The study posits that the mere availability of technological infrastructure is insufficient to ensure the effective integration of learning and knowledge technologies among faculty, students, and researchers. The Italian case reveals a complex landscape characterised by advancements and persistent challenges, indicative of a protracted and uneven digital integration process. But, overall, a strategic approach capable of showing a new vision and a systemic perspective to accompany this disruptive innovation is important

    Competence profiles updates for the future digital society: a comparative approach.

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    The essay illustrates a comparative analysis oriented to understanding the national digital strategies of countries’ partners involved in the Erasmus+ Project RE-EDUCO. Digital transformation in Europe will rapidly accelerate. New technologies play a central role in this process, influencing how people live, interact, study and work. The mismatch between labour supply and demand is among the most recurring complaints that can be read in European and supranational documents that outline the digital society’s developments. The essay examines this mismatch, performed through ETM, applied to the comparative analysis of the reports elaborated by the five partner countries involved in the project. The essay starts with an overview of the issue and methodology adopted to continue with the analysis and discussion data, and some summary conclusions suggested by this work
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