Physical Activity and Mental Health After COVID-19: The Role of Levels and Domains of Physical Activity.

(1) Background: Physical activity (PA) plays a crucial role in preserving and enhancing mental health, particularly in the aftermath of major health crises such as the COVID-19 pandemic. However, the specific levels and domains of physical activity that have the greatest impact on alleviating symptoms of anxiety, depression, and stress in the post-COVID-19 period remain unclear. The aim of this study was to examine the influence of different levels and domains of PA on mental health parameters, specifically symptoms of anxiety, depression, and stress, in individuals who had recovered from COVID-19. (2) Methods: The study included initial measurements (2-4 weeks post-recovery) and final measurements (14-16 weeks post-recovery). The sample comprised 288 participants aged 20 to 60 years (M = 47.06; SD = 12.41), with 95 men and 193 women. PA was assessed using the long version of the IPAQ questionnaire, while mental health was evaluated using the long version of the DASS scale. (3) Results: Stepwise regression analysis revealed that low- (p = 0.010) and moderate-intensity (p = 0.022) PA was significantly associated with reductions in anxiety symptoms as well as lower stress levels (low PA: p = 0.014; moderate PA: p = 0.042). Total PA (p < 0.001) and vigorous-intensity PA (p = 0.008) emerged as significant predictors of reduced depression levels. Among the domains of PA, home-based activities had a statistically significant impact on all three mental health components: anxiety (p = 0.005), depression (p = 0.002), and stress (p = 0.041). Transport-related PA was significantly associated with anxiety (p = 0.011) and stress (p = 0.022), but not with depression. (4) Conclusions: The results suggest that a combined model incorporating different levels and domains of PA may represent an effective approach to improving mental health in individuals recovering from COVID-19. Further longitudinal studies are needed to establish more precise causal relationships.