*3.6. Prediction of Psychological Distress*

The results of the logistic regression analysis controlled for sex and age are presented in Table 6. This model shows a variance of 22.6% in the overall model, with percentages of correct classification of each model around 68.3%. The model had a good fit (Hosmer– Lemeshow Chi-square value = 4.929, *p* = 0.765) and made it possible to identify the predictor variables of psychological distress.

Model 1 (sociodemographic variables) indicated a predictive ability of 12.7% (χ<sup>2</sup> = 211.457, *p* < 0.001). Gender, specifically female (OR = 3.142, 95% CI = (2.566, 3.848)), educational level, employment status, and living with children or under 16 years of age were predictors. This model correctly classified 65% of the subjects with sensitivity and specificity parameters of 79.3% and 45.8%, respectively.

With model 2, relating to physical symptoms, the value of the variance explained amounted to 16% (χ<sup>2</sup> = 268.399, *p* < 0.001).

Participants who reported a greater number of symptoms in the 14 days prior to study participation (OR = 1.444, 95% CI = (1.339, 1.558)) were more likely to show psychological distress. This model correctly classified 65.4% of participants (sensitivity 81.3% and specificity 44.3%).

Model 3 showed a predictive capacity of 16.8% (χ<sup>2</sup> = 281.293, *p* < 0.001), slightly higher than the previous one, and included health-related variables. This model provided sensitivity and specificity values of 83.8% and 42.8%, correctly classifying 66.3% of the sample. Participants who scored higher on self-perceived health (OR = 0.563, 95% CI = 0.496, 0.640) were less likely to experience psychological distress. However, subjects who had been quarantined in the past 14 days for having symptoms were 2.878 times more likely to have psychological distress (95% CI = 1.456, 5.687).



\* *p* < 0.05; \*\* *p* < 0.01; NA: not applicable; R2 = model explained variance (sensitivity/specificity); OR (95% CI): odds ratio (confidence interval at the 95% level).

> Model 4 included contact history variables, which provided an explained variance rate of 13.1% (χ<sup>2</sup> = 217.047, *p* < 0.001). Having close contact with an individual with confirmed COVID-19 infection (OR = 1.499, 95% CI = 1.120, 2.007), as well as having had any contact with any person or material suspected of being infected (OR = 1.437, 95% CI = 1.108,

1.863) had predictive ability, correctly classifying 65.3% of participants (80% sensitivity and 45.6% specificity).

Finally, Model 5 (global model), which contained the variables with predictive capacity in the previous models, showed a predictive capacity of 22.6%, correctly classifying 68.5% of the participants (78% sensitivity and 54.9% specificity). The variables that showed greater weight, with ORs greater than 1, were sex (OR = 2.448, 95% CI = 1.980, 3.028), educational level (OR = 1.419, 95% CI = 1.170, 1.820), living with children or children under 16 years of age (OR = 1.580, 95% CI = 1.304, 1.915), number of symptoms presented in the last 14 days (OR = 1.327, 95% CI = 1.224, 1.440), having been quarantined in the past 14 days for presenting symptoms (OR = 2.443, 95% CI = 1214, 4.913), having had close contact with an individual with confirmed COVID-19 infection (OR = 1.347, 95% CI = 1.031, 1.759), and having had contact with any person or material suspected of being infected with COVID-19 (OR = 1.237, 95% CI = 0.958, 1.598). Other predictor variables with ORs less than 1 were self-perceived health in the last 14 days and employment status.

#### **4. Discussion**

In this study conducted in Portugal, 57% of the participants present psychological distress during the COVID-19 pandemic, revealing that they often feel oppressed and tense and that they cannot enjoy the activities they usually perform in their daily life (i.e., here is where the suffering is greatest). Other studies corroborate our results, showing the presence of psychological distress in people during the COVID-19 pandemic. In Spain, a study revealed that a high percentage (i.e., 72%) of participants were at risk of developing psychological problems [7]. In China, a study found that 22.8% of participants reported high levels of psychological distress [27]. In the United States, the percentage of individuals reporting psychological distress was 73% in a study conducted at the beginning of the COVID-19 pandemic [28]. In Italy, the psychological impact that the COVID-19 pandemic caused was around 48.6% [12]. Studies that focused their attention on the psychological impact during the pandemic reveal that the percentage of psychological distress is between 22.9% and 56.7% [20,29,30]. The percentage of psychological distress in our study and other studies reported here exceeds the pandemic data, so we can interpret this to mean that the COVID-19 pandemic has affected populations more severely than other previous pandemics.

Regarding the sociodemographic variables for which there is greater vulnerability to psychological problems during the COVID-19 pandemic, the most significant variable is sex; in this sense, in our study, 79.0% of participants with psychological distress were female. In addition, other variables that influence this vulnerability to psychological suffering are level of education (university studies: graduation, master's, and doctorate) (75.8%), working outside the home (69.2%), conditions of the usual dwelling (where 59.2% lived in a flat), and living with children or young people under the age of 16 (50.2%). People who are unemployed (10.3%) are the ones with the lowest percentage of psychological distress. The results show that there are statistically significant differences between psychological problems and sex. There is no statistical relationship between psychological suffering and age, that is, age does not influence whether or not one is suffering. Other studies corroborate the results of our study regarding the increased risk for women of developing psychological distress throughout the COVID-19 pandemic, an aspect that can be interpreted as an individual and biological risk factor. On the other hand, due to the closing of schools during the pandemic, women suffered disproportionately from the burden of caregiving, with increased responsibilities of work and household chores [7,12,16].

Regarding the level of education as a predictor of psychological distress, our study shows that there is greater psychological distress in people with higher levels of education (university studies: graduation, master's, and doctorate), with no evidence in other studies of the relationship between psychological suffering and education. The correlation presented by our study may indicate that the ease of access that people with a higher level of education have to credible scientific information and their perception of the severity of

the virus based on scientific evidence—together with uncertainty about the direction the pandemic may take, as there is little knowledge about the virus, and means of treatment and control—can lead this group of people to develop fear and anxiety [31].

In relation to people living with children or young people under 16 years of age, other studies are in line with these results, being explained by the fear of contagion of the children, by the burden of the caregiver, and by the difficulty in providing playful and fun activities for children, creating a feeling of boredom and being still in time [7,12,28,32–34].

In our study, the unemployed sample showed the lowest psychological distress. On the other hand, it is those who have to work outside the home (69.2%) who have greater psychological suffering, which can be justified by the fear of contracting COVID-19 and transmitting it to others, inadequate protection against contamination, discrimination, overwork, and exhaustion. The results of the studies by Gomez-Salgado et al. [7] and Jeong et al. [33] are in line with our results. Data from a study conducted in China contradict our results and argue that psychological distress during the pandemic is related to unqualified and low-skilled jobs and unemployment, as these situations create distress related to the socio-economic situation [27].

The data presented in this study reveal that there is no statistical relationship between psychological distress and age. The evidence shows different results taking into account different age groups—that is, there are studies that show that the younger population is more likely to develop psychological suffering, because they have more difficulty in dealing with adversities and also in understanding that the pandemic is an extreme situation, which implies drastic changes in the lifestyle of a society and does not result from individual decisions [7,30]. Other studies reveal that psychological distress is greatest in people over 60 years of age, as they are part of the group most at risk of developing COVID-19 [32,35].

Regarding the presence of symptoms of COVID-19, the most frequent were headaches (46.6%), rhinorrhea (30.1%), myalgia (24.7%), cough (15.3%), sore throat (14.7%), and in a smaller percentages, diarrhea (9.7%), dizziness (6.9%), chills (5.2%), respiratory distress (3.6%), and fever above 38 ◦C for one day (1.1%). With the exception of respiratory distress and the presence of fever greater than 38 ◦C for one day, all other physical symptoms related to COVID-19 are a predisposing factor to the existence of psychological distress. Other studies have found myalgias, dizziness, chills, and odynophagia to be associated with greater psychological distress [17]. In a study conducted in Spain, the presence of headache, rhinorrhea, myalgias, cough, sore throat, diarrhea, dizziness, chills, difficulty breathing, and fever higher than 38 ◦C for one day are also associated with increased psychological distress [7].

Of the participants with COVID-19 symptoms (4.5%), 18.1% were tested—69.2% had a negative result, 22.2% had a positive result, and 8.7% did not know the result. Only 3.1% of respondents indicate that they were quarantined for having had contact with a person infected with COVID-19.

In our study, health-related variables (presence of chronic diseases; taking medication regularly; needing to attend consultations in a health centre, hospital, or clinic regularly; having recently performed COVID-19 tests; and self-assessment of health perception) were related to the presence of psychological distress, as had already been described in the studies by Shehata et al. [36], Cybulski et al. [37], and Ripoll et al. [38]. Regarding the evaluation of the perception of the health of our sample, the results show that the group of people who do not experience psychological distress expressed a better evaluation of their health compared to the group that had psychological distress, although both made a good self-assessment of their health. Other studies corroborate our results, describing a relationship between the existence of comorbidities and the presence of psychological distress in patients with COVID-19 and in the general population, but this relationship was not statistically significant [8,39].

Regarding contact history in the 14 days prior to this survey, of our sample, 36.1% of participants claimed to have had close contact with an individual who tested positive for COVID-19 [35]. One percent of individuals claimed to have had random contact, and

43% claimed to have maintained or not known if they had had contact with any person or material suspected of being infected with COVID-19. Regarding the presence of an infected person in the close circles of the participants, 91.2% stated that they did not have infected family members. All variables (close contact with an individual with confirmed infection, casual contact with an individual with confirmed infection, contact with any person or material suspected of being infected with COVID-19, any member of the infected family) relating to the contact history have a statistically significant relationship with the presence of psychological distress. Data from other studies show that a history of contact with an infected person or objects predisposes one to develop psychological distress, namely the presence of acute stress and post-traumatic stress, which arise from the feeling of danger and risk of contracting the infection [7,40,41].

In order to describe the limitations of the present study, it is worth mentioning that the cross-sectional design used does not allow establishing a cause-effect relationship, although it does provide a very valuable description of the impact of the COVID-19 pandemic on psychological distress at the specific moment of confinement and of the greatest escalation of the infection curve in Portugal. On the other hand, the sampling procedure was not random, and the study participants were collected through email lists to universities and professional associations. Moreover, the sex variable was not represented in the actual proportion of the Portuguese population. Furthermore, it was not possible to compare the results of the present study with those obtained during the development of other pandemics, since the measures adopted in the current situation differ from those implemented in those past situations. Similarly, the results obtained in Portugal cannot be compared with those obtained in studies conducted on the same topic in other countries.

Future studies should carry out cause-effect analyses, perhaps at different epidemiological moments of the pandemic, to really study what has been and what will be the emotional impact of the COVID-19 pandemic in Portugal.
