Studying the Experience of the Confinement Measures Implemented during the COVID-19 Pandemic in Greece

Abstract

The confinement measures implemented to limit the spread of SARS-CoV-2 disrupted daily life and increased the risk of poor mental and physical health. The COVID-19 pandemic also resulted in unprecedented disruptions to healthcare access due to both supply and demand factors, creating barriers to disease management. Thus, the objective of this study was to investigate the factors that influenced views on coping with confinement measures. For this study, we used data from the Eurobarometer 93.1. The sample consisted of 1016 individuals aged 15 years and over. The sample design was multi-staged and random (probability). For the purpose of the study, a multinomial logistic regression model was fitted and used views on the experience of coping with confinement measures as the outcome variable. Several demographic, health-related, and economic factors were used as independent variables. According to the results, residents of more densely populated areas, females, and individuals who consider their personal health an important issue had more negative views of their experience during confinement measures. This was also true for individuals from financially worse-off households. The study results indicate a direct influence of economic and health-related factors on the experience of coping with the implemented confinement measures.

1. Introduction

Due to its rapid spread around the globe in a short period of time, coronavirus disease 2019 (COVID-19) was characterized as a pandemic by the World Health Organization on 11 March 2020, almost three months after it was first discovered in Wuhan, Hubei Province, China, in December 2019 [1]. As of 18 July 2022, 559,469,605 confirmed cases and 6,361,157 deaths have been reported globally [2]. Thus, the COVID-19 pandemic is a global health catastrophe that seems to have been happening for as long as anyone can remember [3].

However, what began as a health crisis quickly turned into a financial crisis [4]. Therefore, the COVID-19 pandemic negatively influenced the global economy and financial markets [5]. In this sense, the pandemic constitutes an economic shock that has influenced the markets’ normal functioning and has led to a broad range of economic impacts.

Since economic shocks can affect supply, demand, or both [6], the pandemic itself and the measures implemented to limit the virus’ spread disrupted global supply chains and economic activities. In particular, the restrictions on the free movement of labor and transport negatively affected the output of the economy (supply shocks), which led to massive job and income losses (demand shocks) [7].

The COVID-19 pandemic has had far-reaching impacts on how we live, work, and connect with one another as well as on the economic, human, social, and environmental systems that support well-being over time [8]. Thus, it is not surprising that it has caused massive, tragic economic, emotional, mental, physical, and psychological suffering [9].

Consequently, the pandemic and its management have disrupted daily life and have increased the risk of poor mental and physical health [10,11].

The influence of economic factors on health is among the most important mechanisms through which the pandemic response has affected health [12]. Evidently, socio-economic status (SES) is linked to increased morbidity and mortality [13]. The explanations of social inequalities in health fall into three broad categories: (1) material/structural, (2) behavioral/lifestyle, and (3) psychosocial mechanisms [14]. Specifically, the higher prevalence of unfavorable material circumstances, unhealthy behavior, unfavorable psychosocial characteristics, and unfavorable childhood circumstances in lower socioeconomic groups explains, to a large extent, the socioeconomic inequalities in health [15].

Furthermore, during health emergencies such as the COVID-19 pandemic, financial spending on health services or medications can have a direct economic impact, while significant healthcare costs can force households to limit other key expenses. Therefore, the required funds may be supplemented by potentially distressing means, such as by entering into financial debt. Moreover, the inability to work—due to illness or caregiving—can create indirect economic impacts through loss of income and the associated financial distress [16].

In terms of mental health, due to health, social, economic, and individual impacts, the COVID-19 pandemic brings with it multiple psychological stressors and may result in psychological distress [17]. Among these stressors, financial concerns, i.e., worry over job security and lack of resources, are among the most stressful [18]. Furthermore, the COVID-19 pandemic has exposed hundreds of millions of individuals to severe financial uncertainty [19] through job and income losses [20], increasing job insecurity [21], and financial insecurity [22]. Uncertainties are detrimental to mental health, causing psychological distress and emotional exhaustion by draining resources invested in regulating mood and maintaining stability [23]. Because financial instability is associated with adverse psychological outcomes, the COVID-19 pandemic has increased the risk of psychological distress for many people [24,25].

An increased prevalence of mood, anxiety, sleep, and stress-related disorders caused by the influence of factors such as worrying about catching the virus, worsening living conditions, isolation, reduced income, school and university closures, and changes in working life has also been reported during the pandemic [26].

It is also evident that social isolation is a major risk factor for morbidity and mortality and is as harmful as other risk factors such as smoking, lack of exercise, obesity, and high blood pressure [27]. Moreover, social isolation can also cause depression, anxiety, suicidality, personality disorders, psychoses, and deterioration of cognitive functions [28]; furthermore, it is also considered to affect the immune system [29].

In addition, migraines, sleep disorders, persistent exhaustion, and difficulty concentrating are among the most frequent lockdown-related physical symptoms [30]. Furthermore, the measures implemented to curb the virus’ spread have entailed unprecedented disruptions to our lives and work associated with risks to physical health, such as physical inactivity—the fourth leading risk factor, accounting for 6% of global mortality following hypertension (13%), smoking (9%), and diabetes (6%) [31].

Moreover, the COVID-19 pandemic resulted in unprecedented disruptions to healthcare services [32]. For instance, resources were redirected from chronic disease care to COVID-19 management [33]. The disruption in access to healthcare has also been linked to demand-side factors, such as an inability to access healthcare services due to transport restrictions during lockdowns, reduced healthcare-seeking behaviors due to fear or to preserve the health system capacity, and worsening poverty, which may limit one’s ability to pay [34].

In Greece, the first COVID-19 case was diagnosed on 26 February 2020, while the first patient died on 12 March 2020. As of 18 July 2022, 3,843,142 confirmed cases and 30,476 deaths have been reported [2].

During the first wave, non-pharmaceutical interventions started with the cancellation of the carnival one day after the first case was reported, i.e., on 27 February 2020. On 10 March, schools and universities closed; as of 10 March, 89 cases and zero deaths had been reported. Between 12 March and 14 March, movie theaters, gyms, courtrooms, malls, cafés, restaurants, beauty parlors, museums, archaeological sites, organized beaches, and ski resorts closed; as of 14 March, 228 cases and three deaths had been reported. On 18 March, all stores except supermarkets and pharmacies closed; as of 18 March, 418 cases and five deaths had been reported. The first nationwide lockdown was imposed on 23 March 2020 (23 March–4 May); as of 23 March, 695 cases and 17 deaths had been reported [35]. As of 10 July, i.e., the date that data collection for the survey used in this study started, 3732 cases and 193 deaths had been reported, while as of 22 July, i.e., the date that data collection ended, 4077 cases and 200 deaths had been reported [36].

Thus, due to the impact of the pandemic and the containment measures that came into effect to curb infections, especially during the second and fourth quarters of 2020, the country’s economy contracted by 8.2% in 2020 [37].

Based on the previous points, the objective of this study was to investigate the experience of confinement measures during the COVID-19 pandemic in Greece.

2. Materials and Methods

For this study, we used data from the Eurobarometer 93.1 [38]. During the Eurobarometer 93.1, face-to-face interviews were feasible in Greece, and they were conducted in people’s homes or on their doorsteps. A multi-stage, random (probability) design was applied and was the basic sample design for the face-to-face interviews. The sampling points were systematically drawn from each of the regional administrative units after stratification by individual units and area types. Thus, they represent the entire territory of the country according to the distribution of the resident population in terms of metropolitan, urban, and rural areas based on the Eurostat Nomenclature of Territorial Units for Statistics (NUTS II) (or equivalent). The sample consisted of 1016 individuals aged 15 years and over. Interviews were conducted with a Computer-Assisted Personal Interviewing (CAPI) technique. Fieldwork was conducted between 10 and 22 July 2020 [39].

The outcome variable of the study corresponds to the question, “thinking about the measures taken to fight the coronavirus outbreak, in particular the confinement measures, would you say that it was an experience easy or difficult to cope with? An experience…?” The potential answers were: (a) very easy to cope with and even an improvement to your daily life; (b) fairly easy to cope with; (c) both easy and difficult to cope with; (d) fairly difficult to cope with; (e) very difficult to cope with and endangering your mental and physical health conditions; and (f) do not know/not applicable. A multinomial logit model was fitted because of the non-existence (due to categories 1 and 5) of direct ordering.

As regressors in the analysis, the following variables were used: (a) type of community (1: rural area or village, 2: small- or medium-sized town, and 3: large town), (b) gender (0: female; 1: male), (c) age, (d) health as one of the two most important issues an individual is facing (0: not mentioned, 1: mentioned), (e) health as one of the two most important issues Greece is facing (0: not mentioned, 1: mentioned), (f) household’s financial situation (1: very good, 2: rather good, 3: rather bad, 4: very bad, and 5: do not know), (g) personal job situation (1: very good, 2: rather good, 3: rather bad, 4: very bad, and 5: do not know), (h) situation of the Greek economy (1: very good, 2: rather good, 3: rather bad, 4: very bad, and 5: do not know), (i) employment situation in Greece (1: very good, 2: rather good, 3: rather bad, 4: very bad, and 5: do not know).

The answers “do not know” and “not applicable” were recoded as missing. The Helmert contrast was applied to the variables “type of community”, “household’s financial situation”, “personal job situation”, “situation of the Greek economy”, and “employment situation in Greece”. The Helmert contrast compares each level (except the last) of a variable with natural ordering in the levels with the mean of the subsequent levels. The dummy variables “gender”, “health as one of the two most important issues an individual is facing”, and “health as one of the two most important issues Greece is facing” were treated as such. Age was treated as a continuous variable.

The Independence of Irrelevant Alternatives (IIA) assumption was tested through the suest-based Hausman test. The model’s goodness of fit was tested using the generalized Hosmer and Lemeshow test.

The analysis was performed with the STATA 17 statistical software package. Specifically, the commands desmat [40], mlogit, mlogtest [41], and mlogitgof [42] were used.

3. Results

According to the results of the descriptive analysis, the mean age was found to be equal to 50.079 years (±17.007 years). Approximately 49 percent of the respondents (49.016%) were men, and 51 percent (50.984%) were women. In addition, approximately 30 percent of the respondents (29.823%) were residents of rural areas or villages, while approximately 18 percent of the respondents (18.110%) were residents of small- or medium-sized towns. Furthermore, approximately 52 percent of the respondents (52.067%) were residents of large towns.

Approximately three percent (3.054%) of the respondents declared that it was very easy to cope with the confinement measures; they considered these measures to improve their daily life. However, approximately thirteen percent (13.498%) of the respondents found it very difficult to cope with the confinement measures; they considered these measures to endanger their mental and physical health (

Table 1. Experience with the confinement measures.

Category	% (n) Valid Percent (%)
Very easy to cope with and even an improvement to your daily life	3.051 (31) (3.054)
Fairly easy to cope with	19.094 (194) (19.113)
Both easy and difficult to cope with	25.689 (261) (25.714)
Fairly difficult to cope with	38.582 (392) (38.621)
Very difficult to cope with and endangering your mental and physical health conditions	13.484 (137) (13.498)
Not applicable	0.098 (1)

).

According to the multinomial logistic regression model (

Table 2. Multinomial logistic regression model.

Variable	Coefficient	p-Value	95% Confidence Interval (CI)
Category: Very Easy to Cope with and Even an Improvement to Your Daily Life *
Community type
Rural area or village vs. small/medium-sized town or large town	1.248	0.004	0.389	2.108
Small/medium-sized town vs. large town	1.939	0.002	0.692	3.186
Gender	0.504	0.229	−0.317	1.325
Health as one of the two most important issues an individual is facing	−0.216	0.643	−1.130	0.698
Household’s financial situation
Very good vs. rather good, rather bad, and very bad	2.668	0.003	0.938	4.398
Rather good vs. rather bad and very bad	2.358	<0.001	1.144	3.571
Rather bad vs. very bad	2.054	0.058	−0.073	4.181
Constant	−1.658	<0.001	−2.478	−0.837
Category: Fairly Easy to Cope with *
Community type
Rural area or village vs. small/medium-sized town or large town	0.251	0.354	−0.279	0.780
Small/medium-sized vs. large town	0.490	0.140	−0.161	1.140
Gender	0.614	0.010	0.150	1.079
Health as one of the two most important issues an individual is facing	−1.035	0.001	−1.634	0.436
Household’s financial situation
Very good vs. rather good, rather bad, and very bad	0.696	0.339	−0.731	2.122
Rather good vs. rather bad and very bad	1.295	<0.001	0.789	1.801
Rather bad vs. bery bad	0.993	0.002	0.360	1.625
Constant	0.358	0.137	−0.113	0.830
Category: Both Easy and Difficult to Cope with *
Community type
Rural area or village vs. small/medium-sized town and large town	−0.115	0.661	−0.628	0.398
Small/medium-sized town vs. large town	0.441	0.157	−0.170	1.051
Gender	0.438	0.051	−0.003	0.878
Health as one of the two most important issues an individual is facing	−1.162	<0.001	−1.729	−0.594
Household’s financial situation
Very good vs. rather good, rather bad, and very bad	0.315	0.665	−1.108	1.737
Rather good vs. rather bad and very bad	1.131	<0.001	0.651	1.612
Rather bad vs. very bad	1.138	<0.001	0.557	1.720
Constant	0.661	0.005	0.204	1.118
Category: Fairly Difficult to Cope with *
Community type
Rural area or village vs. small/medium-sized town and large town	0.096	0.693	−0.382	0.574
small/medium-sized town vs. large town	0.374	0.210	−0.211	0.959
Gender	0.767	<0.001	0.353	1.181
Health as one of the two most important issues an individual is facing	−0.504	0.039	−0.984	−0.025
Household’s financial situation
Very good vs. rather good, rather bad, and very bad	0.094	0.894	−1.288	1.476
Rather good vs. rather bad and very Bad	0.949	<0.001	0.494	1.404
Rather bad vs. very bad	1.289	<0.001	0.761	1.817
Constant	0.757	0.001	0.312	1.201

* Reference Category: Very difficult to cope with and endangering your mental and physical health conditions.

), community type, gender, health as one of the two most important issues an individual is facing, and household’s financial situation, explained the differences between the categories of the outcome variable and the reference category.

According to the suest-based Hausman test, the IIA assumption was not violated (

Table 3. Suest-based Hausman test of independence of irrelevant alternatives (IIA) assumption.

Category	p-Value
Very easy to cope with and even an improvement to your daily life	0.996
Fairly easy to cope with	0.771
Both easy and difficult to cope with	0.839
Fairly difficult to cope with	0.965
Very difficult to cope with and endangering your mental and physical health conditions	0.861

).

With respect to the comparison between the “very easy to cope with, and even an improvement to your daily life” and the “very difficult to cope with, and endangering your mental and physical health conditions” categories, residents of rural areas or villages (coefficient: 1.248, 95% confidence interval (CI: 0.389–2.108)) as well as residents of small- or medium-sized towns (coefficient: 1.939, 95%, CI: 0.692–3.186) were more likely to find it much easier to cope with confinement measures, which they considered to contribute to improving their daily lives. The same also held true for more financially better-off households (coefficient: 2.668, 95%, CI: 0.938–4.398 and coefficient: 2.358, 95%, CI: 1.144–3.571).

Furthermore, with respect to the comparison between the “fairly easy to cope with” category and the “very difficult to cope with and endangering your mental and physical health conditions” category, men (coefficient: 0.614, 95% CI: 0.150–1.079) and financially better-off households (coefficient: 1.295, 95% CI: 0.789–1.801 and coefficient: 0.993, 95% CI: 0.360–1.625) were more likely to cope with the confinement measures fairly easily. However, individuals who considered health as one of the two most important issues that they face (coefficient: −1.035, 95%, CI: −1.634–(−0.436)) were more likely to have difficulty coping with the confinement measures, which they considered to be endangering the condition of their mental and physical health.

Moreover, with respect to the comparison between the “both easy and difficult to cope with” and the “very difficult to cope with, and endangering your mental and physical health conditions” categories, individuals who considered health as one of the two most important issues that they face (coefficient: −1.162, 95%; CI: −1.729–(−0.594)) were more likely to have difficulty coping with the confinement measures, which they considered to be endangering the condition of their mental and physical health. However, households that were financially better-off (coefficient: 1.132, 95%, CI: 0.651–1.612 and coefficient: 1.138, 95% CI: 0.557–1.720) were more likely to cope with the confinement measures with both ease and difficulty.

Additionally, with respect to the comparison between the “fairly difficult to cope with” and the “very difficult to cope with and endangering your mental and physical health conditions” categories, men (coefficient: 0.767, 95%, CI: 0.353–1.181) and households that were financially better-off (coefficient: 0.949, 95%, CI: 0.494–1.404 and coefficient: 1.289, 95%, CI: 0.761–1.817) were more likely to have a fair amount of difficulty coping with the confinement measures. However, individuals who considered health as one of the two most important issues they face (coefficient: −0.504, 95% CI: −0.984–(−0.025)) were more likely to have difficulty coping with the confinement measures, which they considered to be endangering the condition of their mental and physical health.

According to the generalized Hosmer and Lemeshow test, the model had a good fit (p = 0.279).

4. Discussion

According to the results, the experience with the confinement measures implemented in Greece was dependent on the type of community, gender, whether health was one of the two most important issues an individual was facing, and the household’s financial situation.

Although urban areas had more COVID-19 cases than rural ones during the first months of the pandemic [43], SARS-CoV-2 spread in non-urban areas during the summer period due to population movement for the holidays [44]. Thus, the influence of the “type of community” variable did not reflect the influence of transmission dynamics. Rather, it showed that denser urban areas were more vulnerable during the COVID-19 pandemic in terms of living conditions and quality of life because they are characterized by poorer living conditions, such as old building stock and lack of direct sunlight, open public spaces, parks, gardens, and vegetation as well as poor infrastructure, noise, air pollution, and building density [45]. Thus, it is not surprising that in Greece, the residents of urban areas were more affected than residents of rural areas concerning everyday life, fun/relaxation, food, house expenses, health, education and education services, holidays, and social events [46].

Regarding gender, the international literature indicates that women have been more susceptible to mental health problems, physical health problems, and well-being-related problems during the COVID-19 period than men [47,48]. Women’s mental health is more likely to be affected when economic conditions worsen, while they also report greater concern for their finances [49]. In addition, women were affected by the massively increased childcare demands due to school closures [50]. Furthermore, based on the Survey of Health, Ageing, and Retirement in Europe (SHARE) Corona data [51], women in Greece report a statistically significantly higher proportion of forgoing healthcare (10.68%) than men (6.61%) due to fear of catching the novel coronavirus. It is evident that forgoing healthcare is associated with unfavorable health-related outcomes, a higher risk of hospitalization, and decreased quality of life [52]. Thus, the Corona SHARE data analysis partly explains the influence of gender on how confinement measures were experienced.

On the other hand, the influence of “health as one of the two most important issues an individual is facing” is probably largely due to the management of pre-existing conditions during the pandemic and the influence of confinement measures on both pre-existing conditions and the development of psychological distress. In contrast, the influence of confinement measures on the development of new somatic conditions requires further research. Based on our analysis of the SHARE Corona survey [51] data and concerning the management of pre-existing conditions, we should highlight that 11.13% of the respondents declared that they had a medical appointment postponed by their healthcare providers due to COVID-19, while 3.63% of the respondents declared that their healthcare providers have denied the scheduling of a medical appointment since the outbreak. Supply-side factors, such as ceasing most of the Greek health system’s regular activities and redirecting available resources to COVID-19 treatment [53], are included among the major factors that explain, in combination with demand-side factors, such as income reduction [54], the results above. Additionally, concerning the development of psychological distress, a significant percentage of the Greek population reported clinically important anxiety, depression, and post-traumatic stress symptoms during the pandemic [55].

The household’s economic situation was found to be statistically significant and to confirm the literature since it is included among the factors that directly affect an individual’s health [56]. In addition, a family’s financial situation is a key driver of a member’s sense of well-being [57]. Furthermore, one’s economic situation likely influences their ability to cope with COVID-19; individuals who are better-off financially may be better able to cope with massive life disruptions resulting from the pandemic, such as homeschooling one’s children, affording personal protective equipment, and having resources to withstand the shortages caused by the COVID-19 outbreak [58]. It is evident that the measures implemented to reduce the spread of COVID-19 in Greece caused adverse effects on incomes [59]. Loss of income or unstable income is not only related to the inability to afford rent, utilities, internet, or other daily expenses during and even after the pandemic [60] but is also associated with exposure to health and safety risks [61]. Furthermore, the perceived financial threat would likely be higher than usual during times of economic crisis, such as the COVID-19 economic crisis, as the probability of financial setbacks increases with the worsening of the economic environment [62]. Moreover, because the economic situation was unstable during the pandemic, lifestyle behaviors were severely influenced worldwide [63]. Thus, it is not surprising to say that no event since World War II has triggered such pronounced global impacts on human behavior in such a short period of time [64].

The pandemic has resulted in a severe economic contraction, affecting most economic sectors in countries at all levels of gross domestic product (GDP) [65]. In addition, induced changes to daily life and income losses [66]. In this sense, it has caused severe disruptions in daily life [67] and poses an unprecedented challenge for the world as people seek ways to cope with this serious threat to their well-being [68]. Individuals have experienced a wide range of adversities not only due to the virus (experiencing illness oneself, concerns for friends and family, and bereavement), but also due to their finances (loss of income and inability to pay bills) but also due to challenges in meeting their basic needs (such as accessing sufficient food, medicine, and safe accommodation) [69]. Thus, the decrease in well-being can be partially explained by economic uncertainties, such as income uncertainty, financial difficulties, economic pressure, and economic worries [70]. In addition, income losses are included among the indirect effects of containment measures through wider determinants of health. Reductions in household financial security can lead to changes in stress levels, health-related behaviors, and access to health services [71].

Direct ways through which lockdowns have unequal impacts on health include unequal lockdown experiences (e.g., due to job and income loss, overcrowding, urbanity, access to green space, key worker roles), the way in which lockdowns shape the social determinants of health (e.g., reduced access to healthcare services for non-COVID-19 reasons, as the system is overwhelmed by the pandemic), and inequalities in the immediate health impacts of the lockdown (e.g., in mental health and gender-based violence) [72]. The COVID-19 pandemic entails a double burden for the most disadvantaged groups of the population; beyond the severe hit by the virus itself, they suffer most of the social and economic consequences of the confinement measures, which, in turn, have negative impacts on their physical and mental health [73]. Based on the previous points, the measures implemented to limit virus spread profoundly affected people’s quality of life [74].

In our effort to compare studies related to how the implemented confinement measures were experienced, we faced difficulties due to methodological differences, mainly concerning the scales used in such studies.

For instance, while we used a single item in our study, the scale analyzed in the study by Bernedo et al. [75] was obtained using three items based on Antonovsky’s Sense of Coherence Scale [76] as cited in [75]. Specifically, the respondents were asked the following questions: “When you think about the lockdown, to what extent do you think your family has been able: (1) to cope with the situation; (2) to accept the situation that we are all going through; and (3) to find meaning in the situation, despite the circumstances.” All three items were rated on a five-point scale, with values ranging from 1 (“Not at all”) to 5 (“Very much”). As one can observe, the items do not include health-related options, in contrast to the scale used in our study. In Bernedo’s et al. [75] study, a positive association between income and positive lockdown experience was found.

On the other hand, the study by Pérès et al. [77] approached the negative experience of the pandemic during the lockdown through emotional distress or material difficulties caused by the lockdown using the following items: (a) high anxiety symptomatology; (b) depressive symptoms (at least one out of the three); (c) at least one self-reported difficulty or worry during the lockdown; and (d) feelings of insufficient support to face the period. The experience of the pandemic was considered to be negative when at least two of the abovementioned items were present. Using logistic regression analysis, Pérès et al. [77] found that the risk of having a negative lockdown experience is approximately two-fold lower in older adults living in rural areas compared to those living in urban areas.

In addition, in the study by Gouveia et al. [78], the degree of difficulty in coping with the restrictions was approached through a binary variable with the following categories: (a) easy; (b) difficult. Based on cluster analysis, it was found that materially comfortable and subjectively relaxed individuals declared that they did not experience difficulty dealing with the lockdown restrictions, and they were confident of being able to cope with the situation.

Despite the differences in scales used, the results of our study are in line with the findings of Bernedo et al. [75], Pérès et al. [77], and Gouveia et al. [78].

An additional difficulty in the comparison between studies is that the confinement measures implemented differ by country in terms of stringency. The number of COVID-19 cases and COVID-19 deaths also differ by country. These points are of special importance since life evaluations during the COVID-19 pandemic have been found to be negatively associated with policy stringency and pandemic intensity [79].

However, the most important difference is that the scale used in our study not only captures the degree of difficulty in coping with the lockdown, but also captures, through the last answer option, the perceived threat, i.e., the combination of perceived susceptibility (beliefs regarding the probability of being affected by a disease or health condition) and perceived severity (feelings regarding the seriousness of contracting an illness or of leaving it untreated) [80]. Even if one considers that this is questionable because of the first answer option, we argue that, based on the Better Life Index, health matters the most to individuals [81]. On the other hand, health threats impact several domains of life (somatic, personal, economic, social) [82]. In addition, perceived threats are also defined as situations that are difficult or troubling to the individual [83].

At this point, it would be useful to present the theoretical background behind our findings. The COVID-19 lockdown may be considered to be a major stressor that affects the lives of all people [84]. According to the Transactional Model of Stress and Coping [85], when faced with a stressor, an individual not only evaluates the potential threats or harm (primary appraisal), but also his or her ability to change the situation and deal with negative emotional reactions (secondary appraisal). The outcomes of the coping process (e.g., psychological well-being, functional status, health behaviors, and treatment adherence) are contingent on actual coping efforts, which are aimed at problem management and emotional regulation [86]. Certain demographic, health-related, or socioeconomic characteristics, may be considered as coping antecedents, i.e., variables that influence the appraisal of a situation and the choice of coping strategies [87]. On the one hand, while the response variable used in this study captures the perceived threat, i.e., a basic appraisal [86], on the other hand, the variables that were found to be statistically significant in the analysis may be considered as coping antecedents. As such, we argue that we studied the perception of the lockdown as a threatening event.

This study contributes to the literature through making it clear as to which factors trigger mechanisms that differentiate the experience of coping with the confinement measures in a framework that is consistent with the wider consequences of the pandemic. Our findings indicate the multidimensional nature of the views on coping with confinement measures. For instance, health not only influences the view of confinement measures as an epidemiologic factor, but also as a factor reflecting the difficulty of accessing the healthcare system. Similarly, gender influences the view of the confinement measures, not only as a characteristic that is closely related to health, but also as a factor reflecting the impact of the restriction measures on family life or working life. Furthermore, the impact of household’s financial situation not only reflects the access to material resources and the ability to access healthcare, but also the exposure to health risks. In addition, the influence of community type is caused by differences in the living standards and quality of life between rural and urban areas.

5. Conclusions

In Greece, the impact of the COVID-19 pandemic on living standards and health, two of the most important domains of well-being, [88] has been severe [89].

With regard to living standards, income level and job losses were among the socioeconomic impacts of the confinement measures implemented to limit the spread of SARS-CoV-2 [90].

In terms of health impacts, in addition to the now well-described morbidity and mortality of COVID-19, the population has faced several psychosocial challenges, such as psychological and psychosomatic disorders. These have been associated with adapted living styles during the isolation period of the pandemic [91].

Thus, the dual nature of the pandemic, in terms of the disease itself and in terms of other health impacts [92], exposes people to a double health threat, physical and emotional. However, COVID-19 causes health, economic, and social losses that may lead to the perceived threat of job loss for employees [93].

On the other hand, the COVID-19 induced economic crisis put people under the threat of income loss [94]. However, income is positively associated with health. In addition, increased income is a form of protection against exogenous shocks, including health shocks such as epidemics [95].

In summary, during the early phase of the pandemic, many families in Greece experienced unexpected job losses and income insecurity [96]. In addition, a considerable percentage of individuals reported moderate to severe depressive and anxiety symptoms [97]. Thus, it is not surprising that the views of Greece’s residents on coping with confinement measures have been formed by a combination of economic and health-related mechanisms.