Psychological Factors Associated with General Quality of Life in the Context of COVID-19 Pandemic: A Cross-Sectional Study on a Multicultural Sample of Romanian Medical Students.
Alexandra Ioana MihăilescuOvidiu Popa-VeleaAdela Magdalena CiobanuLiliana Veronica DiaconescuAlexandra GraurIoana IoniţăMara CarsotePublished in: Healthcare (Basel, Switzerland) (2024)
The COVID-19 pandemic had a significant impact on the general quality of life (GQOL) of a large number of individuals, including those in the academic environment. This study investigated GQOL in a sample of 613 Romanian medicine students (81.57% were female; mean age = 21.40 ± 1.749 years) in relation to their Big Five personality characteristics, Perceived Stress and Fear of COVID-19. The study was conducted between June 2020 and March 2022. These variables were investigated with the Big Five Inventory-2: Extra-Short Form, the Fear of COVID-19 Scale (FCV-19S), the Perceived Stress Scale-10 and the Satisfaction with Life Scale (SWLS). Statistical analysis included hierarchical linear regression and t -tests. The results indicated a significant direct relationship between GQOL and the personality traits of Conscientiousness, Extraversion and Agreeableness. However, a significant inverse relationship was observed between GQOL and Perceived Stress and Neuroticism. Fear of COVID-19 was significantly higher in women, while no other socio-demographic variables were associated with GQOL. A total of 61.7% of the studied population returned to their original residency during the pandemic years. These results could be important for better understanding the vulnerability to significant epidemiological events in academic populations and for planning adequate preventive or interventional measures.
Keyphrases
- coronavirus disease
- sars cov
- medical students
- physical activity
- social support
- depressive symptoms
- mental health
- climate change
- big data
- respiratory syndrome coronavirus
- prefrontal cortex
- stress induced
- type diabetes
- polycystic ovary syndrome
- adipose tissue
- mass spectrometry
- risk factors
- pregnant women
- skeletal muscle
- high resolution
- neural network