P.0817 Sociodemographic and lifestyle predictors of mental health adaptability during COVID-19 compulsory confinement: a longitudinal study

ABSTRACT

Background: The outbreak of COVID-19 and the physical isolation measures taken by the governments to reduce its propagation might have negative psychological consequences on the population [1, 2]. In this study, we aimed to explore, for the first time, how mental health status fluctuated along the weeks of the emergency state in Portugal, and to identify which factors may shape these changes in mental health outcomes. Methods: A longitudinal survey study using a convenience sample was conducted, evaluating demographic, clinical, lifestyle and mental health variables in the Portuguese population at three different time-points. Mental health was assessed by means of the Depression, Anxiety and Stress Scale (DASS-21), and with quality of life (QoL) self-evaluation, satisfaction, and quality of sleep questions. Google Forms was used for the online survey, and social media and national newspapers were used to advertise and recruit possible volunteers. The first time-point took place between the 23rd of March and the 5th of April 2020, and the second and third time-points were 4 weeks and 8 weeks later, respectively. 748 participants (mean age = 39.52, % females = 79.95) provided data at all time-points. Repeated-measures analyses were performed to explore whether mental health significantly varied across time. Next, multiple regression models were used in order to identify the sociodemographic, clinical and lifestyle factors significantly associated with each dependent variable's change (DASS-21 subscales and QoL measures). The following predictors were tested in the multiple regression models age, sex, employment status, house balcony and/or terrace, living with children/teenagers/elderly, having a diagnosis of a psychiatric/physical disorder, consumption of substances several times a week, daily amount of time dedicated to sport/looking for COVID-19 related news, and the NEO-FFI subscales. Results We observed that depression (χ2F(2)=23.19, p<.001, Kendall's W=0.793), anxiety (χ2F(2)=97.04, p<.001, Kendall's W=0.745) and stress (χ2F(2)=35.11, p<.001, Kendall's W=0.788) symptoms seemed to improve as the weeks passed during the state of emergency, while the perception of quality of life (self-evaluation χ2F(2)=140.4, p<.001, Kendall's W=0.749;satisfaction χ2F(2)=82.02, p<.001, Kendall's W=0.765) and sleep (χ2F(2)=23.5, p<.001, Kendall's W=0.796) got worse. All multiple regression models were statistically significant (DASS-21 Depression F(17,730)=6.53;p<.001, R2=0.132;DASS-21 Anxiety F(17,730)=5.12;p<.001, R2=0.106;DASS-21 Stress F(17,730)=7.16;p<.001, R2=0.143;QoL self-evaluation F(17,730)=5.8;p<.001, R2=0.119;QoL satisfaction F(17,730)=6.9;p<.001, R2=0.138;Quality of sleep F(17,730)=1.98;p=.01, R2=0.044). Regarding the significant predictors, in summary, being female, younger, actively working, and extroverted appear to be protective factors of mental health adaptability during this particular period. On the contrary, having a psychiatric diagnosis or physical illness, and higher neuroticism seem to be risk factors for mental health worsening. Conclusions: Our results provide relevant and novel insights about the course of mental health changes and its predictors during the outbreak of COVID-19, which may help identify potential vulnerability groups. Importantly, the lack of a more diverse sample could limit the generalizability of our results, and other factors that were not considered in our analysis might also have a significant impact on mental health. No conflict of interest