Self-Reported Mental Health and Psychosocial Correlates during the COVID-19 Pandemic: Data from the General Population in Italy

Daniela Marchetti, Roberta Maiella, Rocco Palumbo (), Melissa D’Ettorre, Irene Ceccato, Marco Colasanti, Adolfo Di Crosta, Pasquale La Malva, Emanuela Bartolini, Daniela Biasone, Nicola Mammarella, Piero Porcelli, Alberto Di Domenico and Maria Cristina Verrocchio
Additional contact information
Daniela Marchetti: Department of Psychological, Health and Territorial Sciences, G. d’Annunzio University of Chieti-Pescara, 31, Via dei Vestini, 66100 Chieti, Italy
Roberta Maiella: Department of Psychological, Health and Territorial Sciences, G. d’Annunzio University of Chieti-Pescara, 31, Via dei Vestini, 66100 Chieti, Italy
Rocco Palumbo: Department of Psychological, Health and Territorial Sciences, G. d’Annunzio University of Chieti-Pescara, 31, Via dei Vestini, 66100 Chieti, Italy
Melissa D’Ettorre: Department of Psychological, Health and Territorial Sciences, G. d’Annunzio University of Chieti-Pescara, 31, Via dei Vestini, 66100 Chieti, Italy
Irene Ceccato: Department of Psychological, Health and Territorial Sciences, G. d’Annunzio University of Chieti-Pescara, 31, Via dei Vestini, 66100 Chieti, Italy
Marco Colasanti: Department of Psychological, Health and Territorial Sciences, G. d’Annunzio University of Chieti-Pescara, 31, Via dei Vestini, 66100 Chieti, Italy
Adolfo Di Crosta: Department of Psychological, Health and Territorial Sciences, G. d’Annunzio University of Chieti-Pescara, 31, Via dei Vestini, 66100 Chieti, Italy
Pasquale La Malva: Department of Psychological, Health and Territorial Sciences, G. d’Annunzio University of Chieti-Pescara, 31, Via dei Vestini, 66100 Chieti, Italy
Emanuela Bartolini: Department of Neurosciences, Imaging and Clinical Sciences, G. d’Annunzio University of Chieti-Pescara, 11, Via Luigi Polacchi, 66100 Chieti, Italy
Daniela Biasone: NHS, Department of Mental Health, Mental Health Service, snc (ex ospedale “SS. Annunziata”), Via Valignani, 66100 Chieti, Italy
Nicola Mammarella: Department of Psychological, Health and Territorial Sciences, G. d’Annunzio University of Chieti-Pescara, 31, Via dei Vestini, 66100 Chieti, Italy
Piero Porcelli: Department of Psychological, Health and Territorial Sciences, G. d’Annunzio University of Chieti-Pescara, 31, Via dei Vestini, 66100 Chieti, Italy
Alberto Di Domenico: Department of Psychological, Health and Territorial Sciences, G. d’Annunzio University of Chieti-Pescara, 31, Via dei Vestini, 66100 Chieti, Italy
Maria Cristina Verrocchio: Department of Psychological, Health and Territorial Sciences, G. d’Annunzio University of Chieti-Pescara, 31, Via dei Vestini, 66100 Chieti, Italy

Data, 2023, vol. 8, issue 6, 1-7

Abstract: The COVID-19 pandemic tremendously impacted people’s day-to-day activities and mental health. This article describes the dataset used to investigate the psychological impact of the first national lockdown on the general Italian population. For this purpose, an online survey was disseminated via Qualtrics between 1 April and 20 April 2020, to record various socio-demographic and psychological variables. The measures included both validated (namely, the Impact of the Event Scale-Revised, the Perceived Stress Scale, the nine-item Patient Health Questionnaire, the seven-item Generalized Anxiety Disorder scale, the Big Five Inventory 10-Item, and the Whiteley Index-7) and ad hoc questionnaires (nine items to investigate in-group and out-group trust). The final sample comprised 4081 participants (18–85 years old). The dataset could be helpful to other researchers in understanding the psychological impact of the COVID-19 pandemic and its related preventive and protective measures. Furthermore, the present data might help shed some light on the role of individual differences in response to traumatic events. Finally, this dataset can increase the knowledge in investigating psychological distress, health anxiety, and personality traits.

Keywords: psychological distress; personality; trust; health anxiety; dataset (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2306-5729/8/6/111/pdf (application/pdf)
https://www.mdpi.com/2306-5729/8/6/111/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jdataj:v:8:y:2023:i:6:p:111-:d:1172893

Access Statistics for this article

Data is currently edited by Ms. Cecilia Yang

More articles in Data from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().