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. 2020 Oct 2:11:554561.
doi: 10.3389/fpsyg.2020.554561. eCollection 2020.

Rethinking the Role of Affect in Risk Judgment: What We Have Learned From COVID-19 During the First Week of Quarantine in Italy

Massimiliano Barattucci  1 , Alice Chirico  2 , Goran Kuvačić  3 , Andrea De Giorgio  1
Affiliations

Rethinking the Role of Affect in Risk Judgment: What We Have Learned From COVID-19 During the First Week of Quarantine in Italy

Massimiliano Barattucci et al. Front Psychol. .

Abstract

Due to COVID-19 spreading in Italy, on March 11 the Prime Minister of Italy declared a lockdown and imposed severe restrictive measures impacting citizens' freedom at several levels. People were required to stay at home and go out only to satisfy basic needs. Several risk models have postulated a link among online searching behavior, affect, anxiety, and complaints by individuals toward government restrictions (GR), which emerged as also related to an increased perception of knowledge toward risk. However, to date, no study has addressed how these key risk-related aspects (i.e., affect, anxiety, perceived knowledge on risk, and risk dimensions) can act jointly to orient online health information-seeking behavior, and people's complaints toward GR imposed during the lockdown. This study investigated the mechanisms underlying online health information-seeking behavior and people's complaints toward the government's restrictions during a COVID-19 emergency in the Italian population. Drawing from the health belief model (HBM), which postulates a link between sociodemographic variables, risk, and affect dimensions in emergency, we assumed risk factors as predictors of affect and anxiety, which, in turn, were posited as mediators between risk dimensions, online health information-seeking behavior, and complaints toward GR. Participants (1,031) were involved during the first week of the quarantine (March 11-18) and completed an online survey composed of (i) an adapted version of the Italian Risk Perception Questionnaire; (ii) the Italian Positive (PA) and Negative Affect (NA) Schedule (PANAS-10); (iii) the State Anxiety Scale (STAI-Y1); (iv) ad hoc personal knowledge measure about novel coronavirus; (v) ad hoc item measuring information search behavior regarding the novel coronavirus; (vi) ad hoc measure of the complains regarding GR; and (vii) sociodemographic questions. General linear models and structural equation modeling (SEM) were carried out to test the model. Sociodemographic and cognitive factors predicted the participants' affect and anxiety, which, in turn, motivated and fully mediated both information search behavior and complaint toward GR. This research can offer useful suggestions for policy-makers during the COVID-19 emergency, and it advanced the knowledge on the risk-emotion link in emergency situations.

Keywords: SARS-CoV-2; anxiety; behavior; emotions; quarantine.

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Figures

FIGURE 1
FIGURE 1
The first week of lockdown in Italy: epidemiological and variable trends. All variables have been standardized. Due to the numerical difference of epidemiological data between Northern and Southern Italy, we divided the real values by 1,000 and have thus reported them in the y-axis.
FIGURE 2
FIGURE 2
Research model and hypotheses.
FIGURE 3
FIGURE 3
Final structural model on study variables.
See this image and copyright information in PMC

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References

    1. Agresti A., Kateri M. (2011). “Categorical data analysis,” in International Encyclopedia of Statistical Science, ed. Lovric M. (Berlin: Springer; ), 206–208.
    1. Arapakis I., Jose J. M., Gray P. D. (2008). “Affective feedback: an investigation into the role of emotions in the information seeking process,” in Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, New York, NY, 395–402.
    1. Baumgartner S. E., Hartmann T. (2011). The role of health anxiety in online health information search. Cyberpsychol. Behav. Soc. Netw. 14 613–618. - PubMed
    1. Bawden D., Robinson L. (2009). The dark side of information: overload, anxiety and other paradoxes and pathologies. J. Inf. Sci. 35 180–191. 10.1177/0165551508095781 - DOI
    1. Brewer N. T., Chapman G. B., Gibbons F. X., Gerrard M., McCaul K. D., Weinstein N. D. (2007). Meta-analysis of the relationship between risk perception and health behavior: the example of vaccination. Health Psychol. 26 136–145. - PubMed