When Italians Follow the Rules against COVID Infection: A Psychological Profile for Compliance

Abstract

The 2019 coronavirus (COVID-19) outbreak has drastically changed people’s lifestyles and forced them to adopt new behaviors. To assess Italians’ reported compliance to the behavioral provisions issued by the Italian Ministry of Health against the COVID-19 pandemic and identify the socio-demographic and psychological profile of a person who is more likely to comply with them, we conducted a quantitative study with 1556 participants. Notably, in Italy, after a month of lockdown, the reported compliance with anti-COVID prescriptions was high overall. Moreover, personality traits, risk perception, well-being levels, and emotional activations appeared to play a role in promoting or hindering people’s reported compliance. These findings emphasize the importance of being aware of the reported compliance’s antecedents for defining advanced pro-compliance policies and messages and thus better manage each stage of the COVID-19 pandemic in Italy and, plausibly, in other countries.

Through the Second Wave: Analysis of the Psychological and Perceptive Changes in the Italian Population during the COVID-19 Pandemic

“…Since December 2019 and until January 2021, the outbreak of SARS-CoV-2 has led to a pandemic of illness (COVID-19) that has caused 226,236,577 million cases and 4,654,548 deaths worldwide [1,2]. The containment measures and quarantine periods implemented by the various governments around the world had an impact on the psychological and psychosocial equilibria of all the communities around the world, and they continue to affect day-to-day life [3,4].…”

What Went Wrong? Predictors of Contact Tracing Adoption in Italy during COVID-19 Pandemic

“…People's health status could be another valuable direction for future work, thus investigating whether the willingness to download and use the CT app is different between healthy individuals and those with COVID-19. Unfortunately, a recent publication based on a survey reported that just 0.8% referred to have been infected by Covid-19 [60], and thus a larger sample size would be needed to investigate such a difference. Despite the aforementioned limitations, our work contributed to defining the factors (extracted from several psychological models) capable of promoting the adoption of contact tracing systems.…”

“…Despite the aforementioned limitations, our work contributed to defining the factors (extracted from several psychological models) capable of promoting the adoption of contact tracing systems. Encouraging the adoption of contact tracing systems can help to control virus spread together with other measures such as wearing masks, physical distancing, and handwashing [60], although the efficacy of these apps to control the pandemic is not fully demonstrated [61].…”

Forecast of Omicron Wave Time Evolution

“…Not many details are known so far about its infection characteristics [3,4] apart from alarming hints (1) that it is spreading at least four times quicker than the β-mutant with a short doubling time of t 2 = 3 days [5], and (2) that the existing vaccines, tailored to prevent infections from the earlier alpha (α), beta (β), gamma (γ) and delta (δ) mutants, are less efficient against the action of the omicron mutant especially without the current booster campaigns [5][6][7][8][9]. The α, β, γ, and δ mutants have caused the first four COVID-19 waves, respectively [7,8,[10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25], with side effects on societies and markets [26][27][28][29]. Positively, the omicron mutant seems to lead to, on average, milder symptoms and, thus, to smaller hospitalization fractions compared to the earlier mutants [30,31].…”