Si specifica inoltre che la simulazione contiene calcoli effettuati con dati e algoritmi di pubblico dominio e deve quindi essere considerata come un mero ausilio al calcolo svolgibile manualmente o con strumenti equivalenti.Unexpectedly, Italy was the first Western country to face COVID-19 outbreak, but promptly it was the first one to adopt stringent procedures to stem the spread of infection. Cineca, l’Università di Modena e Reggio Emilia e il Focus Group IRIS non si assumono alcuna responsabilità in merito all’uso che il diretto interessato o terzi faranno della simulazione. La presente simulazione è stata realizzata sulla base delle specifiche raccolte sul tavolo ER del Focus Group IRIS coordinato dall’Università di Modena e Reggio Emilia e delle regole riportate nel DM 598/2018 e allegata Tabella A. Si consideri che Anvur calcola i valori degli indicatori all'ultima data utile per la presentazione delle domande. La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. La simulazione si basa sui dati IRIS e sugli indicatori bibliometrici alla data indicata e non tiene conto di eventuali periodi di congedo obbligatorio, che in sede di domanda ASN danno diritto a incrementi percentuali dei valori. Si ricorda che il superamento dei valori soglia (almeno 2 su 3) è requisito necessario ma non sufficiente al conseguimento dell'abilitazione. Il report seguente simula gli indicatori relativi alla propria produzione scientifica in relazione alle soglie ASN 2021-2023 del proprio SC/SSD. īehavioral Changes After the COVID-19 Lockdown in Italy Cucchiarini, Veronica Caravona, Laura Macchi, Laura Perlino, Federico L. ![]() FRONTIERS IN PSYCHOLOGY, 12(10 March 2021). Behavioral Changes After the COVID-19 Lockdown in Italy. The results indicate possible applicative implications of the adopted communicative tools.Ĭucchiarini, V., Caravona, L., Macchi, L., Perlino, F., Viale, R. Across all message types there was a high intention to adopt protective behaviors. The neutral condition was the most memorable, but no condition was more effective than the others. Our second manipulation, identical in Study 1 and 2, compared four types of communication (emotional, exponential growth, both of them, or neutral). ![]() By contrast, among the students, results showed that for the critical group with a lower risk perception (less inclined to adopt prevention behavior) descriptive norms, which implicitly convey the risk perception of peers, were as effective as the government injunctive norm. Through our first manipulation which explored the effectiveness of social norms in relation to different sources, we found that, in the national sample, the injunctive norm conveyed by the government was the most effective in promoting behavioral intentions. To meet these goals, data were collected through a self-administered online questionnaire submitted to a sample of undergraduate students from a University in Lombardy–the region most affected by the pandemic in the first wave- (Study 1), and to a national sample composed of Italian citizens (Study 2). At the same time, it is necessary to understand how the message should be presented, and the relationships between messages, sources and targets. Knowing what source will be most effective to convey a specific message is fundamental in enabling individuals to focus on and comply with the rules. It also aims at identifying the messages and sources that were most effective in managing communication correctly in such a crucial phase that is likely characterized by a fall in perceived health risk (due to the flattening of the epidemic curve) and a simultaneous rise in perceived economic and social risks (due to the enduring calamity). This study aims at identifying the tools necessary for COVID-19 health emergency management, with particular reference to the period following the first lockdown, a crucial phase in which it was important to favor the maintenance of protective behaviors.
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