How to Improve Compliance with Protective Health Measures during the COVID-19 Outbreak: Testing a Moderated Mediation Model and Machine Learning Algorithms

Paolo Roma, Merylin Monaro, Laura Muzi, Marco Colasanti, Eleonora Ricci, Silvia Biondi, Christian Napoli, Stefano Ferracuti and Cristina Mazza
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Paolo Roma: Department of Human Neuroscience, Sapienza University of Rome, 00185 Rome, Italy
Merylin Monaro: Department of General Psychology, University of Padova, 35131 Padova, Italy
Laura Muzi: Department of Dynamic and Clinical Psychology, Sapienza University of Rome, 00185 Rome, Italy
Marco Colasanti: Department of Human Neuroscience, Sapienza University of Rome, 00185 Rome, Italy
Eleonora Ricci: Department of Human Neuroscience, Sapienza University of Rome, 00185 Rome, Italy
Silvia Biondi: Department of Human Neuroscience, Sapienza University of Rome, 00185 Rome, Italy
Christian Napoli: Department of Medical Surgical Science and Translational Medicine, Sapienza University of Rome, 00189 Rome, Italy
Stefano Ferracuti: Department of Human Neuroscience, Sapienza University of Rome, 00185 Rome, Italy
Cristina Mazza: Department of Neuroscience, Imaging and Clinical Sciences, University “G.d’Annunzio”, 66100 Chieti-Pescara, Italy

IJERPH, 2020, vol. 17, issue 19, 1-17

Abstract: In the wake of the sudden spread of COVID-19, a large amount of the Italian population practiced incongruous behaviors with the protective health measures. The present study aimed at examining psychological and psychosocial variables that could predict behavioral compliance. An online survey was administered from 18–22 March 2020 to 2766 participants. Paired sample t -tests were run to compare efficacy perception with behavioral compliance. Mediation and moderated mediation models were constructed to explore the association between perceived efficacy and compliance, mediated by self-efficacy and moderated by risk perception and civic attitudes. Machine learning algorithms were trained to predict which individuals would be more likely to comply with protective measures. Results indicated significantly lower scores in behavioral compliance than efficacy perception. Risk perception and civic attitudes as moderators rendered the mediating effect of self-efficacy insignificant. Perceived efficacy on the adoption of recommended behaviors varied in accordance with risk perception and civic engagement. The 14 collected variables, entered as predictors in machine learning models, produced an ROC area in the range of 0.82–0.91 classifying individuals as high versus low compliance. Overall, these findings could be helpful in guiding age-tailored information/advertising campaigns in countries affected by COVID-19 and directing further research on behavioral compliance.

Keywords: COVID-19; compliance; efficacy; risk perception; civic engagement; personality (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

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