Unknown

Dataset Information

0

Psychological well-being during the COVID-19 pandemic in Italy assessed in a four-waves survey.


ABSTRACT: COVID-19 pandemic had a negative impact on the mental health and well-being (WB) of citizens. This cross-sectional study included 4 waves of data collection aimed at identifying profiles of individuals with different levels of WB. The study included a representative stratified sample of 10,013 respondents in Italy. The WHO 5-item well-being scale (WHO-5) was used for the assessment of WB. Different supervised machine learning approaches (multinomial logistic regression, partial least-square discriminant analysis-PLS-DA-, classification tree-CT-) were applied to identify individual characteristics with different WB scores, first in waves 1-2 and, subsequently, in waves 3 and 4. Forty-one percent of participants reported "Good WB", 30% "Poor WB", and 28% "Depression". Findings carried out using multinomial logistic regression show that Resilience was the most important variable able for discriminating the WB across all waves. Through the PLS-DA, Increased Unhealthy Behaviours proved to be the more important feature in the first two waves, while Financial Situation gained most relevance in the last two. COVID-19 Perceived Risk was relevant, but less than the other variables, across all waves. Interestingly, using the CT we were able to establish a cut-off for Resilience (equal to 4.5) that discriminated good WB with a probability of 65% in wave 4. Concluding, we found that COVID-19 had negative implications for WB. Governments should support evidence-based strategies considering factors that influence WB (i.e., Resilience, Perceived Risk, Healthy Behaviours, and Financial Situation).

SUBMITTER: de Girolamo G 

PROVIDER: S-EPMC9606283 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

altmetric image

Publications


COVID-19 pandemic had a negative impact on the mental health and well-being (WB) of citizens. This cross-sectional study included 4 waves of data collection aimed at identifying profiles of individuals with different levels of WB. The study included a representative stratified sample of 10,013 respondents in Italy. The WHO 5-item well-being scale (WHO-5) was used for the assessment of WB. Different supervised machine learning approaches (multinomial logistic regression, partial least-square disc  ...[more]

Similar Datasets

| S-EPMC9445494 | biostudies-literature
| S-EPMC8364416 | biostudies-literature
| S-EPMC10038280 | biostudies-literature
| S-EPMC8718800 | biostudies-literature
| S-EPMC9453756 | biostudies-literature
| S-EPMC9002031 | biostudies-literature
| S-EPMC7385325 | biostudies-literature
| S-EPMC8085728 | biostudies-literature
| S-EPMC8296300 | biostudies-literature
| S-EPMC10712288 | biostudies-literature