Impact on the mental and physical health of the portuguese population during the COVID-19 confinement

Journal of Clinical Medicine Article Impact on the Mental and Physical Health of the Portuguese Population during the COVID-19 Confinement Fátima Frade 1,2 , Lia Jacobsohn 3,4, Juan Gómez-Salgado 5,6,* , Rosário Martins 7, Regina Allande-Cussó8, Carlos Ruiz-Frutos 5,6,† and João Frade 9,10,†   Citation: Frade, F.; Jacobsohn, L.; Gómez-Salgado, J.; Martins, R.; Allande-Cussó, R.; Ruiz-Frutos, C.; Frade, J. Impact on the Mental and Physical Health of the Portuguese Population during the COVID-19 Confinement. J. Clin. Med. 2021,10, 4464. https://doi.org/ 10.3390/jcm10194464 Academic Editor: Michele Roccella Received: 27 July 2021 Accepted: 22 September 2021 Published: 28 September 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1Escola Superior de Enfermagem de Lisboa, 1600-190 Lisboa, Portugal; [email protected] 2Centro de Administração e Políticas Públicas (CAPP), University of Lisbon, 1300-666 Lisbon, Portugal 3Escola Superior de Saúde, Universidade Atlântica, 2730-036 Barcarena, Portugal; [email protected] 4Centro de Medicina de Reabilitação do Alcoitão, 2649-506 Alcabideche, Portugal 5Department of Sociology, Social Work and Public Health, Faculty of Labour Sciences, University of Huelva, 21007 Huelva, Spain; [email protected] 6Safety and Health Postgraduate Programme, Universidad Espíritu Santo, Guayaquil 092301, Ecuador 7Escola Superior de Saúde, Instituto Politécnico de Viana do Castelo, 4900-347 Viana do Castelo, Portugal; [email protected] 8Nursing Department, University of Seville, 41009 Sevilla, Spain; [email protected] 9Instituto Politécnico de Leiria, Escola Superior de Saúde e Centre for Innovative Care and Health Technology (ciTechcare), 2411-901 Leiria, Portugal; [email protected] 10 Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, 4099-002 Porto, Portugal *Correspondence: [email protected]; Tel.: +34-959219700 † These authors have contributed equally and share the last position. Abstract: Confinement of the population has been one of the measures implemented by different governments to address the COVID-19 health crisis, and it has led to social isolation together with a disruption of daily activities. The aim of the study is to analyze psychological distress during the COVID-19 pandemic in Portugal. During the quarantine, a cross-sectional study was carried out on a sample of 2120 subjects over 18 years of age, resident and born in Portugal. Data were collected using a self-developed questionnaire that considered socio-demographic variables, physical symptoms, health conditions, and history of contact with COVID-19, as well as psychological alterations. The General Health Questionnaire (GHQ-12) was also included. Univariate and bivariate statistical analyses were performed. Predictive capacity was studied using logistic regression models. The results showed a higher percentage of individuals presenting psychological distress (57.2.0%), with a higher percentage identified among women (79.0%), and in people with a higher educational level (bachelor’s + master’s and doctorate) (75.8%). The predictor variables with the greatest weight were sex, educational level (graduation, master’s, and doctorate), living with children or under 16 years of age, presence of symptoms, and quarantine in the last 14 days for having symptoms. Good self-assessment of health and working at home appear to be protective against psychological distress. These results highlight the impact of the COVID-19 pandemic on psychological distress and provide an opportunity to consider the need to implement specific multidisciplinary public health and mental health interventions in this pandemic situation. Keywords: COVID-19; psychological distress; pandemic; public health; quarantine; mental health 1. Introduction In 2019, the world was surprised by a pandemic caused by the new coronavirus (SARS-CoV-2), which was called COVID-19. COVID-19 began in Wuhan, China, and soon spread to the rest of the world. As of February 2021, there were 111,102,016 cases of infection by the new coronavirus and 2,462,911 deaths worldwide [ 1 ]. In Portugal, the number of confirmed cases of COVID-19 infection is 798,074 and the number of deaths is 16,023 [ 2 ]. Being an unknown virus, much research has been done in relation to it and J. Clin. Med. 2021,10, 4464. https://doi.org/10.3390/jcm10194464 https://www.mdpi.com/journal/jcm J. Clin. Med. 2021,10, 4464 2 of 14 also in relation to the impact it has had on the physical and psychological health of people living through the pandemic caused by it. The main physical signs and symptoms of the infection are fever, dry cough, dyspnea, odynophagia, headache, myalgia, chills, nausea, vomiting, diarrhoea, hemoptysis, and conjunctival congestion. The main psychological effects of the virus influence people’s mental health, causing higher levels of stress, anxiety, psychological distress, and depression [3–8]. In the specific case of Portugal, in response to the rapid epidemiological evolution of the COVID-19 disease, and with the aim of containing the virus and moderating the social, health, and economic impact of the pandemic, a state of alarm was declared on 18 March 2020 [9] . During the state of emergency, mandatory confinement measures were adopted for infection control, like the limitation of free movement of citizens, favoring teleworking (except for essential professions for basic needs like health, food, and safety), face-to-face teaching activities were suspended in favor of online teaching (in different levels of education), and cultural, sporting, and religious activities were suspended. The obligation to maintain social distance, use of masks, and compliance with respiratory etiquette was maintained. Deconfinement began at the beginning of May. At this stage, the general infection control measures included the mandatory use of a mask; compliance with respiratory etiquette; maintaining social distance; avoiding contact with people who present symptoms suggestive of COVID-19; working from home whenever possible (telework); prioritizing using the telephone or electronic services to get in touch with other services, such as supermarkets, pharmacies, or other; contacting the health services in advance in case of need for medical care; and avoiding crowded places, unnecessary contacts (inside or outside the home), and promotion of or participation in events that bring together many people [2,9]. The impact of the COVID-19 pandemic on the physical and mental health of the population is undeniable, and the published evidence describes it as such [ 10 ]. Thus, it is estimated that 38.2% of the European population has psychological disorders related to COVID-19 [ 11 ]. Social distancing and self-isolation during the COVID-19 pandemic have challenged people’s mental health and general well-being, contributing to increased mental health problems which include depression, anxiety, mood disorder, psychological distress, post-traumatic stress disorder, insomnia, fear, stigma, lack of self-esteem, and lack of self-control [12]. The risk factors that compromise the psychological well-being of people experiencing the COVID-19 pandemic are fear of not having economic conditions for the goods of first necessity and for food, fear of quarantine, level of health perception, degree of risk control, and risk perception. Other studies reveal, as risk factors for psychological wellbeing, the perception of increased risk of SARS, a history of contact with people tested positive, feeling symptoms similar to those of SARS, loss of social contact and breaking of family routines, and increase of sedentary behaviors [ 7 , 12 – 16 ]. Given the variability in the risk factors for developing psychological distress, and the protective factors identified, it is worth considering the need for further studies to refine these results. Despite the agreement on the presence of psychological distress during the COVID-19 pandemic situation, the characteristics of the population are disparate, and more variables need to be controlled [13]. In Portugal, the few studies conducted during the COVID-19 pandemic show that the Portuguese population deteriorated in their mental health conditions during the pandemic, and the percentage of anxiety and depression is evident [ 14 ]. Other symptoms presented by the Portuguese population are poor sleep quality, insomnia, fear, anxiety, depression, and obsessive-compulsive symptoms due to COVID-19 [15,16]. Studies carried out in Portugal have focused on identifying the percentages of psychological factors in the Portuguese population during the pandemic and listing different symptoms. In our study, in addition to identifying the psychological factors present in the Portuguese population, we also identify the factors that predict their development, thus making it possible to plan action measures that can be implemented with the aim of J. Clin. Med. 2021,10, 4464 3 of 14 reducing the presence of these factors in other pandemic situations. Thus, the aim of this study is to analyze psychological distress in a Portuguese population sample during the COVID-19 pandemic to identify the existence of related sociodemographic and specific health factors. 2. Materials and Methods 2.1. Design The study design was cross-sectional and observational. 2.2. Sample The initial sample consisted of 3105 participants. Of these, 985 were discarded because they did not complete the questionnaire in its entirety. Thus, the final sample was 2120 people, recruited between April and October 2020. The inclusion criteria for participants were: (i) 18 years old or older; (ii) Portuguese residents during the COVID-19 pandemic, and (iii) having accepted the informed consent. 2.3. Variables Regarding socio-demographic variables, sex, age, marital status, level of education, employment status, number of people living with, living with a child or adolescent, and living with a disabled person were considered. Likewise, with regard to the specific situation related to COVID-19, the presence of symptoms, self-perceived level of health, and history of contact and/or exposure were also identified. Considering these variables as independent variables, psychological distress was set as a dependent variable. It is worth mentioning that whether the items related to COVID-19 symptoms were present in the last 14 days was asked about, and the response options were listed as those stipulated by the World Health Organization. These included fever of 38 ◦ C or higher, cough, headache, myalgia, dizziness, diarrhoea, sore throat, coryza, chills, and shortness of breath. Following Wang et al. [ 17 ], physical and mental health status were evaluated by dichotomous (“Yes/No”) questions, as follows: having a chronic illness, having a disability, being on medication, having been hospitalised in the last 14 days, and having attended a health service in the last 14 days. Other variables were contact history and health status, using the Ilder and Benyamini approach, with small variants, in the current pandemic situation [17–21]. 2.4. Instruments An ad hoc questionnaire was designed that included all the variables described. Psychological adjustment was assessed using the General Health Questionnaire (GHQ- 12), duly validated for the Portuguese population [ 22 ] and used as a screening tool for non-psychotic mental disorders in other pandemic situations [ 22 , 23 ]. This questionnaire consists of 12 items with four response options. If the participant chooses options 1 or 2, then the final score for this item is 0 points; however, if the participant selects options 3 and 4, the score of this item is 1 point. After calculating the total sum of these scores, the final range is between 0 and 12 points. For the present study, the overall score with reliability estimated by Cronbach’s alpha at 0.851 was used as a single factor. The cut-off point for the general population was 3, where subjects with scores greater than or equal to 3 were considered more likely to develop psychiatric morbidity [24,25]. 2.5. Procedures Initially, a rapid literature review was conducted regarding the psychological effects that other pandemics, and the protective measures implemented, had caused in the population. Based on these results, a preliminary version of the questionnaire was designed and assessed by a panel of experts composed of 10 professionals (three doctors, four nurses, J. Clin. Med. 2021,10, 4464 4 of 14 and three psychologists, two of them specialists in clinical psychology). Once the tool had been refined and the relevant modifications had been made, a pilot study was carried out on a sample of 57 subjects, identified by non-probabilistic sampling, over 18 years of age, seeking a similar proportion between men and women (50.9% and 49.1%, respectively). The mean age of this sample of subjects was 41.87 years (SD = 11.86), 56.1% reported being married, and 57.9% reported having completed a master’s or doctoral degree. No subjects in the pilot study reported problems in understanding the items, and no problems were detected in the design and visualization of the survey on different devices (PC, tablet, or smartphone). Qualtrics ® XM platform was the software used for the creation, design, and dissemination of the survey in this study. For the field study, a non-probabilistic snowball sampling was also implemented, based on the dissemination of the link via email lists to universities and professional associations, who were asked to help in this dissemination process. 2.6. Ethical Considerations The ethical principles set out in the Declaration of Helsinki [ 26 ] have been followed. Participants’ permission was obtained by means of an informed consent form where they expressed their voluntary desire to participate. Data were recorded in an anonymous way and treated confidentially. The project was approved by the Research Ethics Committee of Atlântica—Instituto Universitário. 2.7. Data Analyses A descriptive univariate and bivariate statistical analysis was carried out, after studying the normality of the data distribution, using SPSS (26.0) software (IBM, Armonk, NY, USA). Measures of central tendency and dispersion were used for quantitative variables, and frequencies and percentages for qualitative variables. For the bivariate analysis, Chi-squared and Student’s t-statistics were used. Crammer’s V and Cohen’s d effect size indices were also calculated, considering the following cut-off points: 0 to 0.19, insignificant; 0.20 to 0.49, small; 0.50 to 0.79, medium; 0.80 and above, high. After this, a logistic regression algorithm was run, controlling for sex and age, and including in the models tested the variables that proved to be significant (p< 0.05). Finally, a global predictive model was designed, which corresponds to model 5, where the relationship of all variables with the presence or absence of psychological problems is analyzed, that is, the predictive factors that predispose a person to the existence of psychological problems are analyzed by calculating the odds ratios (OR) with a 95% confidence interval. 3. Results 3.1. Psychological Distress Table 1shows the mean scores and standard deviations of the answers to the General Health Questionnaire questions given by the subjects. The mean score for the total of the 12 points scale was 3.97 (SD = 3.43). Establishing a cut-off point of 3 or more points, 57.2% of the 2120 study participants presented psychological distress. Item 5, “Have you felt constantly overwhelmed and stressed?” ( M = 2.68; SD = 0.90 ), and item 7, “Have you been able to enjoy your normal daily activities?” ( M = 2.62; SD = 0.89), were the ones with the highest scores. In opposition, item 11, “Have you thought that you are a worthless person?” (M = 1.44; SD = 0.78), and item 10, “Have you lost confidence in yourself?” (M = 1.69; SD = 0.85), presented lower scores. J. Clin. Med. 2021,10, 4464 5 of 14 Table 1. General Health Questionnaire (n= 2120). Items M (SD) 1. Have you been able to concentrate well on what you are doing? 2.40 (0.69) 2. Have your worries made you lose a lot of sleep? 2.47 (0.99) 3. Have you felt that you are playing a useful role in life? 1.98 (0.69) 4. Have you felt capable of making decisions? 2.09 (0.54) 5. Have you felt constantly overwhelmed and stressed? 2.68 (0.90) 6. Have you had the feeling that you cannot overcome your difficulties? 2.13 (0.88) 7. Have you been able to enjoy your normal daily activities? 2.62 (0.89) 8. Have you been able to adequately cope with problems? 2.26 (0.59) 9. Have you felt unhappy or depressed? 2.22 (0.99) 10. Have you lost confidence in yourself? 1.69 (0.85) 11. Have you thought that you are a worthless person? 1.44 (0.78) 12. Do you feel reasonably happy considering all the circumstances? 2.27 (0.67) Scale total (over 12 points) 3.97 (3.43) Presence of psychological distress (cut point ≥3) (%) Yes 57.2 No 42.8 3.2. Sociodemographic Variables and Psychological Distress With regard to the sociodemographic variables (Table 2), statistically significant differences were found between both groups as regards sex ( χ2 = 163.137, p< 0.001, V = 0.277). No statistically significant differences were observed in the presence of psychological distress with age (χ2= 1.394, p= 0.163, V = 0.063). Table 2. Association between sociodemographic variables and psychological distress during the COVID-19 pandemic (n= 2120). Psychological Distress n(%) No (n= 908) Yes (n= 1212) χ2/tpEffect Size Sex Male 684 (32.3) 47.2 21.0 163.137 <0.001 0.277 Female 1436 (67.7) 52.8 79.0 Age (mean (SD)) 38.84 (13.00) 39.31 (14.60) 38.49 (11.66) 1.394 0.163 0.063 Marital Status Single 837 (39.5) 43.6 36.4 13.353 0.001 0.079 Married or living as a couple 1090 (51.4) 46.9 54.8 Separated/divorced/widowed 193 (9.1) 9.5 8.8 Educational level Secondary school 628 (29.6) 36.8 24.3 41.666 <0.001 0.140 University education (graduation) 721 (34.0) 28.9 37.9 University education (master’s or PhD) 771 (36.4) 34.4 37.9 Employment status Working away from home 1450 (68.4) 67.3 69.2 8.328 0.016 0.063 Working from home 474 (22.4) 24.9 20.5 Not working 196 (9.2) 7.8 10.3 Type of dwelling Flat or Apartment 1210 (57.1) 54.3 59.2 5.011 0.025 0.049 House 910 (42.9) 45.7 40.8 Living with children or under-16 youngsters No 1146 (54.1) 59.8 49.8 21.108 <0.001 0.100 Yes 974 (45.9) 40.2 50.2 Living with disabled people No 1994 (94.1) 94.6 93.6 0.850 0.357 0.020 Yes 126 (5.9) 6.4 5.4 J. Clin. Med. 2021,10, 4464 6 of 14 Of the total number of subjects who presented psychological distress (1212 subjects, 57% of the sample), 79% were women, 54.8% were married or cohabiting, 75.8% had completed university studies (university studies: graduation, master’s, and doctorate), and 69.2% worked outside the home. Regarding the conditions of the usual dwelling, 59.2% lived in a flat, and 50.2% lived with children under 16 years of age. Statistically significant differences were also found regarding the variables marital status ( χ2 = 13.353, p= 0.001, V = 0.079), employment status ( χ2 = 8.328, p= 0.016, V = 0.063 ), and type of dwelling (χ2= 5.011, p= 0.025, V = 0.063). The percentage of high education (graduation + master’s and PhD) status among those with psychological distress was 75.8%. In addition, as regards participants living with children or youngsters under the age of 16 (50.2%), a low percentage of psychological distress was described. 3.3. Physical Symptoms in the Past 14 Days and Psychological Distress Regarding the presence of symptoms in the 14 days prior to participation in the study, the following was distribution was obtained (Table 3): headache (46.6%), coryza (30.1%), myalgia (24.7%), cough (15.3%), sore throat (14.7%), and to a lesser extent, subjects reported suffering from diarrhea (9.7%), dizziness (9.7%), chills (5.2%), dyspnea (3.6%), and fever above 38 ◦C for at least one day (1.1%). Table 3. Association between physical symptoms in the past 14 days and psychological distress during the COVID-19 pandemic (n= 2120). Psychological Distress n(%) No (n= 908) Yes (n= 1212) χ2/t pEffect Size Fever (>38 ◦C for at least 1 day) No 2101 (99.1) 99.3 98.9 0.991 0.319 0.022 Yes 19 (0.9) 0.7 1.1 Cough No 1848 (87.2) 90.5 84.7 16.021 <0.001 0.087 Yes 272 (12.8) 9.5 15.3 Headache No 1350 (63.7) 77.4 53.4 129.709 <0.001 0.247 Yes 770 (36.3) 22.6 46.6 Myalgia No 1702 (80.3) 86.9 75.3 43.855 <0.010 0.144 Yes 418 (19.7) 13.1 24.7 Dizziness No 2013 (95.0) 97.5 93.1 20.948 <0.001 0.099 Yes 107 (5.0) 2.5 6.9 Diarrhea No 1944 (91.7) 93.6 90.3 7.645 0.006 0.060 Yes 176 (8.3) 6.4 9.7 Sore throat No 1870 (88.2) 92.1 85.3 22.785 <0.001 0.104 Yes 250 (11.8) 7.9 14.7 Coryza No 1632 (77.0) 86.5 69.9 80.425 <0.001 0.195 Yes 488 (23.0) 13.5 30.1 Chills No 2042 (96.3) 98.3 94.8 18.419 <0.001 0.093 Yes 78 (3.7) 1.7 5.2 Breathing difficulty No 2055 (96.9) 97.7 96.4 3.032 0.082 0.038 Yes 65 (3.1) 2.3 3.6 Number of symptoms (mean (SD)) 1.24 (1.45) 0.80 (1.16) 1.58 (1.55) −13.150 <0.001 0.559 J. Clin. Med. 2021,10, 4464 7 of 14 For all variables described in Table 3, statistically significant differences were found between the presence of physical symptoms and psychological distress (p< 0.005), excluding respiratory distress (p= 0.082) and fever (>38 ◦C for at least 1 day) (p= 0.319). Statistically significant differences were also observed for the mean number of symptoms ( χ2 = − 13.150, p< 0.001, Cohen’s d = 0.559), with a mean effect size. The group of subjects with psychological distress had a higher number of symptoms (M = 1.58, SD = 1.55 ) compared to the group without this psychological morbidity (M = 0.80, SD = 1.16). 3.4. Health-Related Variables and Psychological Distress Regarding health-related variables, the results show (Table 4) that 29% of the respondents reported having a chronic disease, and that 35.8% of the respondents are currently taking medication. In the same way, 0.4% of the subjects referred to having been hospitalized in the last 14 days, and 5.3% referred to having received health care in a health center, clinic, or hospital, while 4.5% of the participants had symptoms of COVID-19 and 18.1% reported diagnostic testing. Table 4. Association between health-related variables and psychological distress during the COVID-19 pandemic (n= 2120). Psychological Distress n(%) No (n= 908) Yes (n= 1212) χ2/tpEffect Size Chronic diseases No 1505 (71.0) 75.4 67.7 15.058 <0.001 0.084 Yes 614 (29.0) 24.6 32.3 Currently taking any medication No 1361 (64.2) 70.9 59.2 31.270 <0.001 0.121 Yes 759 (35.8) 29.1 40.8 Health care in a health centre, clinic, or hospital in the past 14 days No 2007 (94.7) 96.0 93.6 5.868 0.015 0.053 Yes 113 (5.3) 4 6.4 Recent hospitalization in the past 14 days No 2111 (99.6) 99.8 99.4 1.568 0.211 0.027 Yes 9 (0.4) 0.2 0.6 Self-rated health in the past 14 days * 4.02 (0.81) 4.26 (0.73) 3.85 (0.83) 11.930 <0.001 0.520 Recent testing for COVID-19 in the past 14 days No 1736 (81.9) 86.6 78.4 23.424 <0.001 0.105 Yes 384 (18.1) 13.4 21.6 Recent quarantine in the past 14 days for having symptoms (n= 2106) ** n= 2040 n= 66 No 2040 (96.9) 98.7 95.5 16.725 <0.001 0.089 Yes 66 (3.1) 1.3 4.5 Note: * Likert-type scale from 1 (very bad) to 5 (very good); ** Fisher’s exact test. All the variables described in Table 4are related to the presence of psychological distress, excluding recent hospitalization in the last 14 days ( χ2 = 1.568, p= 0.211, Cohen’s d = 0.027). Considering the subjects’ assessment of their self-perceived health in the last 14 days, statistically significant differences were also found between the two groups (t = 11.930, p< 0.001, Cohen’s d = 0.520), with a mean effect size. The group of subjects without psychological distress (M = 4.26, SD = 0.73) expressed a better self-perception of their health compared to the group with psychological distress (M = 3.85, SD = 0.83), although both groups have good self-rated health in the last 14 days (M = 4.02, SD = 0.81). J. Clin. Med. 2021,10, 4464 8 of 14 3.5. Variables Related to Contact History in the Past 14 Days and Psychological Distress As regards contact history in the last 14 days (Table 5), 36.1% of the participants reported having had or not knowing if they had had close contact with an individual with confirmed infection with COVID-19. Of these, 37.1% of respondents claimed that the contact was casual, and 43.0% stated they had had or did not know if they had had contact with any person or material suspected of being infected with COVID-19. As for the presence of people infected with COVID-19 in the participants’ immediate circle, 91.2% indicated not having any infected family member. A statistically significant relationship with the presence of psychological distress (p ≤ 0.001 in all cases) was found for all contact history variables in the last 14 days. Nevertheless, the effect sizes were negligible. Table 5. Association between contact history variables in the past 14 days and psychological distress during the COVID-19 pandemic (n= 2120). Psychological Distress n(%) No (n= 908) Yes (n= 1212) χ2pEffect Size Close contact with an individual with confirmed infection with COVID-19 No 1354 (63.9) 73.0 57.0 57.618 <0.001 0.165 Yes or does not know 766 (36.1) 27.0 43.0 Casual contact with an individual with confirmed infection with COVID-19 No 1333 (62.9) 70.7 57.0 41.690 <0.001 0.140 Yes or does not know 787 (37.1) 29.3 43.0 Contact with any person or material suspicious of being infected with COVID-19 No 1208 (57.0) 66.5 49.8 58.953 <0.001 0.167 Yes or does not know 912 (43.0) 33.5 50.2 Any infected family member No 1933 (91.2) 93.6 89.4 11.691 0.001 0.074 Yes or does not know 187 (8.8) 6.4 10.6 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% ( χ2= 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% (χ2= 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% ( χ2 = 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). J. Clin. Med. 2021,10, 4464 9 of 14 Table 6. Prediction of psychological distress. Variables Model 1 OR (95% CI) Sociodemographic Model 2 OR (95% CI) Physical Symptoms Model 3 OR (95% CI) Health Related Model 4 OR (95% CI) Contact History Model 5 Global Model OR (95% CI) Regression Model R2= 0.127 (79.3/45.8%) R2= 0.160 (81.3/44.3%) R2= 0.168 (83.8/42.8%) R2= 0.131 (80/45.6%) R2= 0.226 (78/54.9%) Sociodemographic Sex (ref. males) 3.142 ** (2.566, 3.848) 2.744 ** (2.254, 3.340) 2.898 ** (2.373, 3.539) 3.172 ** (2.616, 3.845) 2.448 ** (1.980, 3.028) Marital Status (ref. single) Married or living as a couple 0.938 (0.755, 1.167) NA NA NA NA Separated/divorced/widowed 0.763 (0.542, 1.075) NA NA NA NA Educational level (ref. secondary school) University education graduation) 1.541 ** (1.210, 1.962) NA NA NA 1.419 ** (1.170, 1.820) University education (master’s or PhD) 1.327 * (1.039, 1.695) NA NA NA 1.163 (0.906, 1.494) Employment status (ref. working away home) Working from home 0.679 ** (0.541, 0.852) NA NA NA 0.784 * (0.618, 0.995) Not working 1.091 (0.784, 1.520) NA NA NA 0.961 (0.684, 1.351) Type of dwelling (ref. apartment) 0.856 (0.712, 1.030) NA NA NA NA Living with children or under-16 youngsters (ref. no) 1.587 ** (1.309, 1.926) NA NA NA 1.580 ** (1.304, 1.915) Physical symptoms Number of symptoms NA 1.444 ** (1.339, 1.558) NA NA 1.327 ** (1.224, 1.440) Health related Chronic diseases (ref. no) NA NA 0.898 (0.695, 1.160) NA NA Currently taking any medication (ref. no) NA NA 1.184 (0.929, 1.509) NA NA Health care in a health centre, clinic, or hospital in the past 14 days (ref. no) NA NA 1.017 (0.653, 1.582) NA NA Self-rated health in the past 14 days* NA NA 0.563 ** (0.496, 0.640) NA 0.672 ** (0.589, 0.767) Recent testing for COVID-19 in the past 14 days (ref. no) NA NA 1.230 (0.953, 1.588) NA NA Recent quarantine in the past 14 days for having symptoms (ref. no) NA NA 2.878 ** (1.456, 5.687) NA 2.443 * (1.214, 4.913) Contact history Close contact with an individual with confirmed infection with COVID-19 (ref. no) NA NA NA 1.499 ** (1.120, 2.007) 1.347 * (1.031, 1.759) Casual contact with an individual with confirmed infection with COVID-19 (ref. no) NA NA NA 0.948 (0.707, 1.271) NA Contact with any person or material suspected of being infected with COVID-19 (ref. no) NA NA NA 1.437 ** (1.108, 1.863) 1.237 (0.958, 1.598) Any infected family member (ref. no) NA NA NA 1.304 (0.925, 1.836) NA *p< 0.05; ** p< 0.01; NA: not applicable; R 2 = 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% ( χ2 = 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,