Italian Adaptation and Psychometric Properties of the Prejudice Against Immigrants Scale (PAIS): Assessment of Validity, Reliability, and Measure Invariance

Anxiety Symptoms, COVID-19-Related Stress Reactions in the Italian General Population, and Validation of the Italian COVID Stress Scales (CSS-I)

Background. The COVID Stress Scales (CSS) assess COVID-related stress experienced in the past week related to danger and contamination fears, socioeconomic consequences, xenophobia, compulsive checking, and reassurance seeking, and traumatic stress symptoms. Our objective was to provide a translation into Italian, replication, and psychometric validation of the CSS in the general population. Moreover, we aimed to test the convergent and discriminant validity of the Italian CSS (CSS-I) with respect to anxiety, stress, and depressive symptoms in the general Italian population. Method. Adult participants (n = 935) over the age of 18 years were recruited from the general population in Italy. Psychological status was assessed using multiple validated measures, including the CSS, Depression, Anxiety and Stress Scales-21 (DASS-21), and the Prejudice Against Immigrants Scale (PAIS). Results. Our confirmatory factor analysis supported a 6-factor model, including danger fears (DAN), socioeconomic consequences (SEC), xenophobia (XEN), compulsive checking and reassurance seeking (CHE), contamination fears (CON), and traumatic stress symptoms (TSS). Strong reliability of the CSS-I (Cronbach's α = 0.863-0.936) and convergent validity with the DASS-21 and PAI were established with positive correlations between total and scale scores across measures. Conclusions. The CSS-I is a valid and reliable instrument to measure COVID-19-related distress in the Italian population.

Proud to support social equality: Investigating the roles of pride, guilt, anger, and disgust in attitudes towards immigrants

Previous research has demonstrated that low social dominance orientation (social equality orientation) promotes empathy with disadvantaged group members. In three studies, we tested a model relating preference for egalitarianism to positive attitudes towards immigrants through emotional experiences (pride, guilt, moral anger/ anger, disgust). Studies 1 and 2 showed that social equality orientation was positively related to proimmigrant attitudes through increased pride in helping immigrants, controlling for participants’ gender, age, and political orientation. Such a preference for egalitarianism was unrelated to proimmigrant attitudes through guilt for not helping immigrants and moral anger concerning mistreatment of immigrants. By focusing on emotional experience concerning proimmigrant national initiatives (e.g., integrating immigrants into the labor market), Study 3 corroborated the indirect effect of social equality orientation on proimmigrant attitudes through increased pride, controlling for participants’ gender, age, political orientation, as well as competitive jungle and dangerous world beliefs. Although much weaker, we also found a positive association between social equality orientation and proimmigrant attitudes through reduced anger, while no significant association through guilt and disgust was found. Results suggest that, relative to guilt, anger, and disgust, pride is the key channel through which preference for egalitarianism is related to positive attitudes towards immigrants. Implications and future directions for research are discussed.

Twitter as social media arena for polarised social representations about the (im)migration: The controversial discourse in the Italian and international political frame

Grounded in social representation theory and its empirical investigation into the ‘social arena’, inspired by the ‘modelling paradigmatic approach’, the research presented in this article is part of a larger project aimed at reconstructing the ‘multi-voice’, and ‘multi-agent’ discourse about (im)migration. Specifically, this contribution’s focus is on the exploration of shaping and sharing social representations about (im)migrants through communication via the social medium ‘Twitter’. A total of 1,958 tweets (967 Italian and 991 English tweets) were analysed through Systeme Portable Pour L’Analyse Des Donnees Textuelles [Portable System for Textual Data Analysis]SPAD in two lexical correspondence analyses. The results show a dichotomous discourse organising a semantic space structured around five different factors for the two distinct Twitter corpora: both clearly show polarised social representations of ‘immigrants–migrants’, leading to exclusion–inclusion policies depending on the discursive agent’s ideological affiliation in the Italian and the international political frame. Used as a propaganda tool, Twitter echoes the related pro- and anti-immigration polemical representations of opposite political leaders in posts that are positioned differently in relation to the progressive/conservative ideology.