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Curr Psychol ; : 1-14, 2023 May 19.
Article in English | MEDLINE | ID: covidwho-2327830

ABSTRACT

A longitudinal psycholinguistic study was conducted with 107 students from different Italian universities that produced daily photo-diary entries for two weeks, one at the beginning and the other at the end of the first Italian lockdown period, imposed in view of the rapid dissemination of COVID -19. The task was to take a daily photo accompanied by a short description (text). The texts accompanying the photos were analysed using Linguistic Inquiry and Word Count (LIWC) software to analyze linguistic markers representing psychological processes related to the experience of the pandemic and the lockdown, identifying potential changes in psycholinguistic variables useful for understanding the psychological impact of such harsh and extended restricted living conditions on Italian students. LIWC categories related to negation, anger, cognitive mechanisms, tentative discourse, past, and future increased statistically significantly between the two time points, while word count, prepositions, communication, leisure, and home decreased statistically significantly. While male participants used more articles at both time points, females used more words related to anxiety, social processes, past, and present at T1 and more related to insight at T2. Participants who lived with their partner showed higher scores on negative emotions, affect, positive feelings, anger, optimism, and certainty. Participants from southern Italy tended to describe their experiences from a collective and social perspective rather than an individual perspective. By identifying, discussing, and comparing these phenomena with the broader literature, a spotlight is shed for the first time on the psycholinguistic analysis of students at the national level who faced the first COVID -19 lockdown in Italy.

2.
Community Psychology in Global Perspective. ; 8(2):59-80, 2022.
Article in English | Scopus | ID: covidwho-2054208

ABSTRACT

The aim of this research was to explore Italian students’ lockdown experience during the COVID-19 pandemic to understand their emotions and the coping strategies they played out during their daily lives at home through photo diaries. The research was carried out in six Italian universities involving 109 participants. The task required each student to take one photo per day for one week in T1 and one in T2, representing their mood during their daily life at home and to give it a title and a brief description. Overall, 1,526 photographs with texts were collected. The main subjects of the photographs were objects, the most frequent coping strategy was self-distraction, and most participants expressed emotions of joy and anticipation but also sadness and fear. Then, the associations between the characteristics of their photos and the emotions and coping strategies from their diary entries were analyzed. For example, emotional support and joy were positively associated with family, pets, and food, while fear and sadness were represented with objects. Implications of the results are discussed, including considerations about using photo diaries during collective disasters. © 2022, University of Salento. All rights reserved.

3.
59th IEEE Conference on Decision and Control (CDC) ; : 3889-3894, 2020.
Article in English | Web of Science | ID: covidwho-1576698

ABSTRACT

The purpose of this work is to give a contribution to the understanding of the COVID-19 contagion in Italy. To this end, we developed a modified Susceptible-Infected-Recovered (SIR) model for the contagion, and we used official data of the pandemic up to March 30th, 2020 for identifying the parameters of this model. The non standard part of our approach resides in the fact that we considered as model parameters also the initial number of susceptible individuals, as well as the proportionality factor relating the detected number of positives with the actual (and unknown) number of infected individuals. Identifying the contagion, recovery and death rates as well as the mentioned parameters amounts to a non-convex identification problem that we solved by means of a two-dimensional grid search in the outer loop, with a standard weighted least-squares optimization problem as the inner step.

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