Psychological well-being during the COVID-19 pandemic in Italy assessed in a four-waves survey.
Sci Rep
; 12(1): 17945, 2022 Oct 26.
Article
in English
| MEDLINE | ID: covidwho-2087316
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).
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
COVID-19
Type of study:
Observational study
/
Prognostic study
/
Randomized controlled trials
Limits:
Humans
Country/Region as subject:
Europa
Language:
English
Journal:
Sci Rep
Year:
2022
Document Type:
Article
Affiliation country:
S41598-022-22994-4
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