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

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.

Dataset: http://doi.org/10.17632/985sfwcj9k.3, accessed on 24 May 2023.

Dataset License: CC BY 4.0.

1. Summary

The rapid spread of the coronavirus disease 2019 (COVID-19) prompted worldwide governments to take unprecedented measures to contain the virus. Many countries implemented physical and social distancing policies, imposing regional or nationwide lockdowns.

In Italy, by the end of January 2020, the Council of Ministers announced a state of emergency related to the health risk. Less than two months later, in March 2020, concomitantly with the World Health Organization declaring COVID-19 a global pandemic, the first nationwide lockdown was decreed. The resulting restrictions notably included the prohibition of leaving one’s house without a valid reason, the adoption of online teaching activities due to the closing of educational institutions, and the closure of all facilities deemed non-essential (e.g., museums, retail businesses, restaurants). This first lockdown lasted until late spring 2020, when, as a result of the downtrend of the contagion curves, most containment measures were loosened.

The pandemic and resulting prolonged isolation took a toll on the mental health of the Italian general and specific populations [1,2]. Accordingly, various studies conducted during the first national lockdown reported that Italians were experiencing high levels of psychological distress [3], especially in the dimensions of perceived stress [4], depression [5], and anxiety [6]. Similarly, high post-traumatic stress disorder (PTSD) symptoms were recorded [7].

The international literature also identified several variables associated with a worse mental health outcome during the COVID-19 pandemic. Among socio-demographic characteristics, for instance, being female was consistently associated with higher levels of psychological distress [8]. Among psychological variables, for example, the Big Five personality trait of neuroticism and high levels of health anxiety were frequently associated with poorer mental health [9,10].

The present dataset was collected via an online survey during the first national lockdown in Italy to investigate how the COVID-19 pandemic affected the general population’s mental health. The contained data might help us understand the psychological impact of the pandemic and its related preventive and protective measures. Furthermore, these data might help determine the role of individual differences, both socio-demographic and psychological, in response to a potentially traumatic event. The present article describes the survey, its generated dataset, and the included variables.

Previous publications [11,12] were partially based on the present dataset and investigated the relationship between individual differences and the psychological and behavioral response to the COVID-19 pandemic.

2. Data Description

The dataset consists of the following two sheets: the first one, labeled “Raw Data”, includes the raw data collected during the COVID-19 lockdown in Italy; the second one, labeled “Items and Code Book”, presents information on all the included variables (descriptions, labels, positions), original English items of standardized questionnaires, original Italian items and their translation in English, survey responses, and variables coding.

The considered variables were socio-demographic data, information about mental disorders, psychological distress (stress, anxiety, depression), health anxiety, trust, and personality.

The dataset is freely available on the Mendeley Data repository at http://doi.org/10.17632/985sfwcj9k.3 (last accessed on 14 June 2023).

2.1. Informed Consent

The first page of the survey informed the participants about the study’s aim and procedures and provided notes on data protection, researchers’ contacts, and the estimated time to complete the survey. The participants were also informed that the survey was anonymous and voluntary and that they could opt out of the study at any time. Once the respondents provided their informed consent to participate in the study, they were assigned a unique identification number, labeled “ID”, which is available in column A of the dataset.

2.2. Socio-Demographic and Mental Health Variables

The demographic information included age (column C), gender (column D), marital status (column E), educational level (column F), and employment status (column G).

The mental health information asked whether the participants were diagnosed with a mental disorder (column I) and whether participants received any form of psychological support in the past 10 years (column J).

2.3. Personality Traits

The personality traits were assessed using the Big Five Inventory 10-Item (BFI-10) [13], a measure developed based on the 44-item Big Five Inventory. The BFI-10 measures the following personality traits: agreeableness/antagonism, conscientiousness/lack of direction, emotional stability/neuroticism, extraversion/introversion, and openness/closedness to experience. The items are rated on a five-point Likert scale ranging from one = “disagree strongly” to five = “agree strongly”. The BFI-10 was found to have good reliability in all subscales [14].

In the present dataset, the responses to the BFI-10 items are listed in columns K to T, and the reverse-scored responses to the BFI-10 items are listed in columns U to Y. The BFI-10 agreeableness, conscientiousness, emotional stability, extraversion, and openness subscales’ scores are listed in columns Z to AD.

2.4. Psychological Distress

The seven-item Generalized Anxiety Disorder scale (GAD-7) [15] was administered to measure anxiety symptoms. The instructions were modified from “over the past 2 weeks” to “since the beginning of the COVID-19 emergency”. The GAD-7 consists of seven items rated on a four-point Likert scale ranging from zero = “never” to three = “nearly every day”. The total score indicates the severity of anxiety symptoms as follows: normal (0–4), mild (5–9), moderate (10–14), and severe (15–21) [16]. The GAD-7 has excellent psychometric properties, including reliability and validity [15].

The present dataset lists the responses to the GAD-7 items in columns AE to AK. The GAD-7 total score and GAD-7 dummy (presence vs. absence of anxiety) are listed in columns AL and AM, respectively.

The nine-item Patient Health Questionnaire (PHQ-9) [17] was included in the survey to assess the severity of depressive symptoms. The instruction was modified from “over the past 2 weeks” to “since the beginning of the COVID-19 emergency”. Based on the participant’s response to the frequency of any symptom (0 = “not at all”, 1 = “several days”, 2 = “more than half of the days”, 3 = “nearly every day”), a total score ranging from 0 to 27 was obtained. A higher score indicates more severe depression. The total score of the PHQ-9 questionnaire was interpreted as follows: normal (0–4), mild (5–9), moderate (10–14), and severe (15–21) depression [17,18]. The PHQ-9 has good psychometric properties and internal consistency [17].

The present dataset lists the responses to the PHQ-9 items in columns BE to BM. The PHQ-9 total score and PHQ-9 dummy (presence vs. absence of depression) are listed in columns BN and BO, respectively.

Perceived stress was assessed using the Perceived Stress Scale (PSS) [19], a 14-item questionnaire initially developed as a global measure of stress over the last 30 days. The items were rated on a five-point scale from zero = “never” to four = “very often”. The total PSS-14 score ranged between 0 and 56 points, with higher scores indicating a higher level of perceived stress. The PSS is a valid measure with good psychometric properties [20].

In the present dataset, the responses to the PSS items are listed in columns BP to CC, and the reverse-scored responses to the PSS items are listed in columns CD to CJ. The PSS total score is listed in column CK.

2.5. Trust

Nine items were selected from the literature to evaluate trust.

The following three items measured the belief, called general trust, that most people are trustworthy most of the time [21,22,23,24]: “If given a chance, most people try to take advantage of you”, “Most people are too busy looking out for themselves to be helpful” and “You can’t trust strangers anymore”. These items used a five-point rating scale from one = “I don’t agree at all” to five = “I agree absolutely”.

Moreover, six items evaluated the in-group and out-group trust [25], three of which emphasized “familiarity” and referred to family, neighborhood, and acquaintances. In contrast, the other three emphasized “remoteness” and referred to strangers and people of other religions and nationalities. Each item used a four-point rating scale from one = “not at all” to four = “completely”.

The present dataset lists the responses to the trust items in columns AN to AV.

2.6. Health Anxiety

The Whiteley Index-7 (WI-7) [26] was administered to measure health anxiety. Each item had a dichotomous response format (yes/no), resulting in a total score between zero (low health anxiety) and seven (high health anxiety). The WI-7 demonstrates good reliability and validity [27].

The present dataset lists the responses to the WI-7 items and the WI-7 total score in columns AW to BC and BD, respectively.

2.7. Psychological Impact of the COVID-19 Pandemic

Consistent with recent studies [11,28], the Impact of Event Scale-Revised (IES-R) [29] was included in the survey to evaluate the psychological impact of the COVID-19 pandemic. The IES-R is a 22-item screening tool used for measuring an individual’s response to a traumatic event. It has three subscales (intrusion, avoidance, and hyperarousal) and a total subjective stress score. The items are rated on a four-point Likert scale ranging from zero = “not at all” to four = “extremely”. A cut-off score of 33 provided the best accuracy for detecting high levels of PTSD symptoms [29]. The IES-R was initially designed and validated to refer to a specific traumatic event and time frame. In this study, “COVID-19 pandemic” and “during the emergency” were used as references for the specific traumatic event and time frame, respectively.

The present dataset lists the responses to the IES-R items in columns CL to DG. The IES-R avoidance, intrusion, hyperarousal subscales’ scores and IES total score are listed in columns DH to DK.

3. Methods

Data were collected in Italy between 1 April and 20 April 2020. Respondents participated in an online survey, implemented through the Qualtrics platform, that was disseminated throughout the entire Italian peninsula. A convenience sample of respondents was recruited through personal contacts, word-of-mouth, and public posts on social media (e.g., Facebook) on both institutional and private pages. Using a snowball sampling technique, participants were recruited to share the survey’s link with others within their network. Inclusion criteria were people who are over the age of 18 and a resident of Italy. Participants did not receive any form of compensation for their participation. A summary of the final sample’s (N = 4081; M_Age = 35.01, SD_Age = 13.60) socio-demographic characteristics is reported in

Table 1. Socio-demographic characteristics of the final sample.

Variable	N	%
Gender
Male	1272	31.17
Female	2809	68.83
Education
Elementary school	27	0.66
Middle school	278	6.81
High school	1720	42.15
University degree	1618	39.65
Higher degree	438	10.73
Marital Status
Unmarried	1362	33.37
In a relationship	1081	26.49
Married or cohabitant	1452	35.58
Separated or divorced	143	3.51
Widowed	43	1.05
Working Status
Unemployed	297	7.28
Unemployed, not looking for a job	184	4.51
Student	1274	31.22
Employed in the private sector	848	20.78
Employed in the public sector	539	13.21
Independent contractor	461	11.30
Healthcare professional	150	3.67
Retired	125	3.06
Other	203	4.97

.

The study was conducted in accordance with the Declaration of Helsinki of 1975, revised in 2008, and was approved by the Ethical Committee of the Department of Psychological, Health and Territorial Sciences at G. d’Annunzio University of Chieti-Pescara (protocol number: 20004).

Microsoft Excel and IBM SPSS Statistics (version 22.0) were used to recode, compute, and analyze the collected data where needed.

Researchers interested in using the present dataset should keep in mind some limitations. First, the survey was conducted online, resulting in data that might suffer from sampling bias. Moreover, the data are exclusively based on self-report instruments, and thus, might be subject to various kinds of response bias. Finally, these data are cross-sectional and were collected one month into the first lockdown when the first peak of contagion was reached in Italy, providing a picture of the Italian population’s psychological response at that specific time. Therefore, they might not generalize to other stages of the COVID-19 outbreak or countries that responded differently to the pandemic.

Despite these limits, the present dataset is useful for investigating the impact of the COVID-19 pandemic on mental health in various types of research, such as cross-cultural comparisons between different countries regarding the psychological response to the pandemic, analyzing the impact of COVID-19 on the Italian population in various phases of the public health emergency, and conducting analyses focused on specific sub-groups. Lastly, the dataset provides an opportunity to compare data from the COVID-19 pandemic with future potential catastrophic events to examine differences in the general population’s psychological response.