2.1. Participants and Procedures

The present study was conducted in Italy in June and July 2020 (from June 11th to July 11th), in the immediate aftermath of the national lockdown related to the health emergency. Specifically, Italian workers were web-based recruited through different social media with a snowball sampling procedure and invited to complete an online survey. The link to the survey was sent, posted, and shared using different tools and social networks, e.g., mailing lists, Facebook, WhatsApp, and the like (for similar data collection strategy, see [84,87,88,89,90]).

Overall, 973 questionnaires were gathered. After deleting non-valid questionnaires (due to incompleteness of responses), a total of 830 valid questionnaires were retained resulting in a response rate of 85.5%. The final sample of participants was composed of 830 working adults (M = 261, F = 569, Average age = 47.36 y.o.). The socio-demographic features of participants are fully reported in Table 2.

Individual Characteristics of the Sample (n = 830).

Before data collection, two different power analyses were run to establish the recommended minimum sample size: (1) for detecting a significant bivariate effect and (2) for conducting a structural equation model (SEM) [91]. We set very conservative parameters in the perspective of a worse-case scenario. A small effect size of r = 0.20 was expected, with a power level set at 0.80 and a significant alpha level set at 0.05. The minimum sample size necessary to detect a significant bivariate effect was N = 194 [91]. Regarding the SEM, with the same previous parameters, we considered five latent and fifteen observed variables. Using the software developed by Soper [92], results of this power analysis indicated that the required minimum sample size to run a SEM and detect a significant effect was N = 376, whereas the minimum sample size for model structure was N = 200. Therefore, our sample size appeared more than adequate in terms of statistical power.

The present research was part of a larger project on the impact of job insecurity and was approved the Academic Committee of Sapienza University of Rome (Protocol number RM11816433B7B857).