Exploring Music-Based Interventions for Executive Functioning and Emotional Well-Being in Stroke Rehabilitation: A Scoping Review.

Purpose: Stroke is one of the leading causes of disability with life-long implications requiring assessment and treatment of several functional domains. This review identifies the results from research into music-based interventions (MBIs), including music therapy (MT), for executive functions (EFs) and emotional well-being (EWB) in adults with stroke and highlights opportunities for clinical practice and future research.

Methods: APA PsycInfo (EBSCOhost), and CINAHL (EBSCOhost) were searched, in addition to grey literature.

Co-construct, implement and evaluate a multi-level intervention to prevent a sedentary lifestyle in children-Study protocol of the CIPRES study.

Background: A sedentary lifestyle is commonly associated with a higher risk of chronic disease development. Among school-aged children from European countries, screen-time represents a significant portion of sedentary time with 39.8% of children spending more than 2h/day in front of a screen on average.

Modeling opinion polarization on social media: Application to Covid-19 vaccination hesitancy in Italy.

The SARS-CoV-2 pandemic reminded us how vaccination can be a divisive topic on which the public conversation is permeated by misleading claims, and thoughts tend to polarize, especially on online social networks. In this work, motivated by recent natural language processing techniques to systematically extract and quantify opinions from text messages, we present a differential framework for bivariate opinion formation dynamics that is coupled with a compartmental model for fake news dissemination. Thanks to a mean-field analysis we demonstrate that the resulting Fokker-Planck system permits to reproduce bimodal distributions of opinions as observed in polarization dynamics.

From agent-based models to the macroscopic description of fake-news spread: the role of competence in data-driven applications.

Fake news spreading, with the aim of manipulating individuals' perceptions of facts, is now recognized as a major problem in many democratic societies. Yet, to date, little has been understood about how fake news spreads on social networks, what the influence of the education level of individuals is, when fake news is effective in influencing public opinion, and what interventions might be successful in mitigating their effect. In this paper, starting from the recently introduced kinetic multi-agent model with competence by the first two authors, we propose to derive reduced-order models through the notion of social closure in the mean-field approximation that has its roots in the classical hydrodynamic closure of kinetic theory.