Data on the effects of COVID-19 pandemic on people's expectations about their future

Abstract

The worldwide spread of the COVID-19 pandemic has unpredictably changed the way people live, by influencing their behaviors and beliefs. This article presents the raw data that have been used to investigate how the pandemic affected people's beliefs and expectations about their future. A total of 3991 participants (18–85 years old) were recruited through an online survey using the Qualtrics platform. The data collection was carried out during the Italian lockdown, between April 1st and April 20th, 2020. This survey collected information about psychological and socioeconomic variables related to the COVID-19 emergency. Respondents filled out a battery of questionnaires that included five measures. Three of the measures were specifically developed by the authors: 1. Expected repercussions of COVID-19; 2. Forethought scale; and 3. Perceived financial resources. The two other measures were standardized questionnaires: the Zimbardo Time Perspective Inventory Short Version (ZTPI-short) and the Positive and Negative Affect Schedule (PANAS). Data from tailored measures on the COVID-19 pandemic reflect people's beliefs about the future, in terms of expectation about the pandemic's effect, estimation of the time needed for the pandemic to resolve, and estimation of how long people could endure the lockdown situation from a financial perspective. The ZTPI questionnaire was administered to measure people's differences in terms of Deviation from Balanced Time Perspective (DBTP). The PANAS questionnaire, instead, was administered to investigate people's differences in terms of emotional mood states. The provided dataset could be useful to other researchers, considering that the data were collected during the lockdown imposed on Italian citizens to face the unprecedented emergency due to the COVID-19 pandemic. Therefore, the collected data may help to understand how people coped with the pandemic, both from a psychological and socioeconomic perspective. Finally, this dataset can be included in the broad context of data, procedures, and experimental materials that have been used to expand our knowledge in the study of time perspective, beliefs, and emotions.

Specifications Table

Subject	Psychology: Experimental and Cognitive Psychology
Specific subject area	Time perspective, mood states, beliefs
Type of data	Raw data and questionnaires (.xls) Descriptive statistics (Table 1) Expected repercussions of COVID-19 questionnaire (Table 2)
How data were acquired	Data were obtained through an online survey Instruments: Qualtrics
Data format	Raw data
Parameters for data collection	Respondents were adults between 18 and 85 years old who were resident in Italy during the lockdown due to the COVID-19 pandemic.
Description of data collection	The data were collected between April 1st and April 20th, 2020, in Italy. The respondents participated in an online survey through the Qualtrics platform.
Data source location	Institution: University “G. d'Annunzio” Chieti-Pescara City: Chieti Country: Italy
Data accessibility	Repository name: Mendeley Data Data identification number: http://dx.doi.org/10.17632/52zyny39yy.2 Direct URL to data: http://dx.doi.org/10.17632/52zyny39yy.2
Related research article	Ceccato I., Palumbo R., Di Crosta A., Marchetti D., La Malva P., Maiella R., Marin A., Mammarella N., Verrocchio M.C., Di Domenico A., (2021). “What's next?” Individual differences in expected repercussions of the COVID-19 pandemic, Personality and Individual Differences, 174, 110,674. http://dx.doi.org/10.1016/j.paid.2021.110674

Value of the Data

• •The dataset is useful since the data were collected during the initial phase of the COVID-19 pandemic, in a country (i.e., Italy) that was severely impacted by the emergency.
• •Researchers can use the dataset to analyze how pandemic impacted people's beliefs, mood states, and expectations about their future.
• •The dataset enables the study of how people coped with the pandemic, considering both psychological and socioeconomic aspects.
• •The data can be used to conduct cross-cultural comparisons, examining similarities and differences in people's reactions to the COVID-19 pandemic across the world.
• •The data enables subgroups comparison based on demographic characteristics (e.g., age, gender, work status).

1. Data Description

The dataset includes raw data collected during the COVID-19 lockdown in Italy (sheet 1). Investigated variables include demographic information, personality, affective state, and attitude related to the pandemic situation [1], [2], [3], [4]. The dataset includes the original Italian version and English translation of the questionnaires we developed, as well as the original English items of the standardized questionnaires (sheet 2). The dataset is freely available on the Mendeley Data repository: http://dx.doi.org/10.17632/52zyny39yy.2.

Demographic information of the sample, including age, gender, monthly income, educational level, working status, and geographical background are summarized in Table 1. Monthly income was categorized based on the Italian income brackets (IRPEF 2020).

Table 1.

Summary of the demographics data reported by the sample involved in the study.

Participants, N	3991
Age, Mean (SD)	35.11 (13.63)
18–29	48.6%
30–59	45.2%
60–85	6.2%
Female,%	68.8%
Monthly Income, Mean (SD)	€ 2010.25 (2018.49)
No income	8.3%
€ 1 - 1250	30.7%
€ 1251–2333	36.1%
€ 2334–4583	16.1%
€ > 4583	8.8%
Education,%
Elementary school	0.6%
Middle school	6.8%
High school	42.0%
University degree	39.9%
Higher degree	10.7%
Working status,%
Unemployed	7.2%
Unemployed not searching for a job (e.g. homemaker)	4.4%
Student	30.9%
Employee in private sector	20.8%
Employee in public sector	13.4%
Independent contractor	11.6%
Healthcare professional	3.6%
Retired	3.1%
Other	5.0%
Geographical background,%
North	17.7%
Center	42.1%
South & Islands	40.2%

Table 2 presents the results of the Principal Component Analysis (PCA) for the Expected repercussion of COVID-19 questionnaire, further described in the Experimental Design, Materials and Methods section. All the four items showed satisfactory loading and the questionnaire showed an acceptable internal consistency, α = 0.77.

Table 2.

Expected repercussions of COVID-19 questionnaire. Items included in the questionnaire and PCA results.

Item	Factor loading	Response scale
1. I believe this crisis will negatively affect my quality of life in the future	0.839	0 (not at all) – 100 (extremely)
2. I believe this crisis will negatively affect the way I socialize with other people in the future	0.832	0 (not at all) – 100 (extremely)
3. I believe this crisis will negatively affect my desire to travel in the future	0.774	0 (not at all) – 100 (extremely)
4. I believe this crisis will negatively impact the financial and economic status of my life in the future	0.597	0 (not at all) – 100 (extremely)

Note. Modified from Ceccato and colleagues [4].

2. Experimental Design, Materials and Methods

We collected the data via an online survey consisting in a battery of self-report questionnaires and implemented through the Qualtrics platform. Participants were recruited through personal contacts, word-of-mouth, and public posts on social media (e.g., Facebook) in both institutional and personal pages. We used a snowball sampling technique, asking participants to share the survey's link to others within their network.

Microsoft Excel and IBM SPSS Statistics (version 22.0) were used to compute and analyze the collected data. Demographic data including age, gender, educational level, and monthly income (measured in Euro) were obtained (see Table 1 for a summary). Three tailored measures for the COVID-19 emergency, developed and described by the authors in previously published studies [3], [9], were included in the survey: the Expected repercussions of COVID-19, the Forethought scale, and the Perceived financial resources. We also included two standardized validated measures: the Zimbardo Time Perspective Inventory Short Version (ZPTI-s) [10] and the Positive and Negative Affect Schedule (PANAS) [11].

The Expected repercussions of COVID-19 is a 4-item questionnaire (Table 2). This new measure was specifically created to investigate people's beliefs about the severity of the backlashes due to the pandemic on future life. The questionnaire examined four aspects of people life: quality of life, social relationships, traveling, and personal finances. Answers ranged from 0, not at all, to 100, extremely. The component structure of the questionnaire was assessed in a larger Italian sample (n = 4121), using principal Component Analysis (PCA). Results revealed an unidimensional structure, with all the four items showing satisfactory loadings (i.e., values > 0.40; see [12]) and explaining 49% of the total variance. Items and factor loadings are reported in Table 2. The questionnaire also showed an acceptable internal consistency, Cronbach's α = 0.77. The total score was created by averaging the four items, with higher scores reflecting worse expectations for the future.

The Forethought scale was extracted from the Attitudes toward the COVID-19 questionnaire [9]. This questionnaire assessed people's beliefs regarding the COVID­19 pandemic referring to specific perceptions, ideas, and expectations about the emergency. Specifically, the Forethought scale measured the expectations about the time needed for the pandemic to resolve (expressed in months). It was composed by two items (“In how many months do you think the situation will improve/be completely resolved?”). The two items were positively intercorrelated, r(3989) = 0.70, p < .001. Answers ranged from 0 to 36 months. The total score was the average of the two items, with higher scores reflecting longer predictions.

The Perceived financial resources is a single-item measure assessing the subjective perception of the economic situation of the respondents during the COVID-19 emergency (refer to the sheet 2 for details). Answers ranged from 0 to 24 months, with higher scores reflecting higher economical safety.

The Zimbardo Time Perspective Inventory - short form (ZTPI-s) was administered to measure the people's fundamental experiential dimensions of time, such as past, present, and future [6], [7], [10]. This standardized measure comprised 18 items, three for each time perspective. In the current sample internal consistency for the six subscales were acceptable, Cronbach's α ranging from 0.56 to 0.71. First, we computed six total scores by averaging appropriate items (see the dataset for item scoring): Past-Negative (PN), Past-Positive (PP), Present-Fatalistic (PH), Present-Hedonistic (PH), Future-Negative (FN), and Future-Positive (FP). We then computed the Deviation from Balanced Time Perspective (DBTP) score, following Rönnlund and colleagues’ formula [5]:

$$DBTP=\sqrt{{\left(PN-1.95\right)}^2+{\left(PP-4.40\right)}^2+{\left(PF-1.50\right)}^2+{\left(PH-3.90\right)}^2+{\left(FP-4.00\right)}^2+{\left(FN-1.80\right)}^2}$$

For each time frame, the optimal score was subtracted from the participant's score. Therefore, the DBTP values close to zero indicated an almost perfectly balanced time perspective, whereas large values indicate an increasing unbalance in time perspective.

The Positive and Negative Affect Schedule (PANAS) was included in the survey to measure positive and negative affect [8], [11]. It consists of two 10-item scales (Positive affect and Negative affect) containing adjectives describing different feelings. Each item is rated on a 5-point scale of 1 (not at all) to 5 (very much). The instructions were adapted to analyze participants’ feelings starting from the beginning of the COVID-19 emergency. In our sample the two subscales showed good internal consistency, Cronbach's α = 0.77 for the Positive affect scale, and Cronbach's α = 0.88 for the Negative affect scale.

Ethics Statement

Informed consent was obtained from all participants included in the study. They were informed that the survey was anonymous (no personal data or IP address collected), voluntary and that they could stop at any time.

CRediT Author Statement

Irene Ceccato: Conceptualization, Methodology, Formal analysis, Writing; Adolfo Di Crosta: Conceptualization, Methodology, Software, Investigation, Writing; Rocco Palumbo: Conceptualization, Methodology, Writing, Supervision; Daniela Marchetti: Conceptualization, Data curation, Supervision; Pasquale La Malva: Software, Investigation; Roberta Maiella: Investigation; Anna Marin: Software; Investigation; Nicola Mammarella: Resources; Supervision; Maria Cristina Verrocchio: Resources; Supervision; Alberto Di Domenico: Conceptualization; Resources; Supervision; Project Administration.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships which have or could be perceived to have influenced the work reported in this article.