COVID-19 Posttraumatic Effects on Perinatal Psychological Distress: A Cross-Sectional Study at the End of the Pandemic Health Emergency.

Introduction: Psychological distress in pregnant and postpartum women increased during the COVID-19 pandemic. However, the impact of the pandemic in perinatal women at the end of the health emergency has been rarely studied. This study is aimed at investigating the psychological health of pregnant and postpartum women at the end of the COVID-19 public health emergency, hypothesizing that the COVID-19-related fears influence perinatal psychological distress via the mediation of the COVID-19-related posttraumatic impact and loneliness.

Multilevel IRT models for the analysis of satisfaction for distance learning during the Covid-19 pandemic.

The Covid-19 pandemic played a relevant role in the diffusion of distance learning alternatives to "traditional" learning based on classroom activities, to allow university students to continue attending lessons during the most severe phases of the pandemic. In such a context, investigating the students' perspective on distance learning provides useful information to stakeholders to improve effective educational strategies, which could be useful also after the end of the emergency to favor the digital transformation in the higher educational setting. Here we focus on the satisfaction in distance learning for Italian university students.

: Antecedents of Self-Disclosure across Different Social Networking Sites.

Previous research investigating antecedents of online self-disclosure pointed out two perspectives: social compensation and enhancement hypotheses, showing controversial findings. Furthermore, most contributions have focused on social networking sites (SNSs) considered mainstream, like Facebook and Instagram, and such results are often considered universally valid for all SNSs. Tumblr is a less-studied SNS with peculiar features—such as anonymity, higher control over the presentation of personal aspects, supportive communities—that could particularly lead individuals to self-disclose.

Gradient dynamics in reinforcement learning.

Despite the success achieved by the analysis of supervised learning algorithms in the framework of statistical mechanics, reinforcement learning has remained largely untouched by physicists. Here we move towards closing the gap by analyzing the dynamics of the policy gradient algorithm. For a convex problem, namely the k-armed bandit, we show that the learning dynamics obeys a drift-diffusion motion described by a Langevin equation, the coefficients of which can be tuned by the learning rate.

Understanding the psychosocial determinants of Italian parents' intentions not to vaccinate their children: an extended theory of planned behaviour model.

Objective: This study aimed to identify the psychosocial factors involved in Italian parents' intentions not to vaccinate their children. For this purpose, we used an extended version of the Theory of Planned Behaviour, which included both proximal and distal factors influencing intention not to vaccinate children.

Design: Participants included 447 Italian parents, each completed an online questionnaire, which measured intention not to vaccinate children, attitude toward not vaccinating, subjective norms, perceived behavioural control, anticipated regret, negative attitude toward vaccines, risk perception, trust in healthcare institutions, trust in science and religious morality.