*3.6. Statistical Analysis*

Descriptive analyses were conducted to describe demographic characteristics, and COVID-19 related aspects in the Italian population, considering the different Italian territorial areas. Student's t-test was performed to compare our data on anxiety, general psychological symptomatology, and PTSD symptomatology with data from the general Italian population, reported by previous studies. Specifically, our data on anxiety were compared with those reported by Corno et al. [22], SCL-90 outcomes were compared with the data given by Holi et al. [12], and PTSD indices were compared with the results of Ashbaugh et al. [23].

Analyses of Variance (ANOVAs) were performed to explore the potential difference in the impact of COVID-19 in the Italian territorial areas. The differences between North Italy, Central Italy, and South Italy were reported for State and Trait Anxiety, psychopathological symptomatology (Somatization, Obsessive-Compulsive, Interpersonal Sensitivity, Depression, Anxiety, Anger-Hostility, Phobic Anxiety, Paranoid Ideation, Psychoticism, and Sleep Disturbance), and PTSD symptomatology (IES-R). Furthermore, within-subjects ANOVA designs were adopted to compare the respondents' self-reporting mood before and during the COVID-19 emergency.

Logistic regressions were performed to explore the influence of demographic factors and experiences which were COVID-19 related in determining risk for state anxiety (STAI), psychopathological symptoms (SCL-90), and PTSD symptomatology (IES-R).

All data were analyzed using Statistical Package for Social Sciences (SPSS) version 24.0 and Statistica 10.0 (StatSoft.inc., Tulsa, OK, USA). *p*-values of less than 0.05 were considered statistically significant. To better control the results for the multiple comparison analyses, the Bonferroni correction was adopted; in these cases, an adjusted *p*-value of less than 0.01 was considered statistically significant.
