Who were Psychologically more Vulnerable During COVID-19? Examining the Patterns of Psychological Feelings and Risk Behaviors in Abu Dhabi
Received: 24-Dec-2021 / Manuscript No. JIDT-21-50591 / Editor assigned: 27-Dec-2021 / PreQC No. JIDT-21-50591 (PQ) / Reviewed: 07-Jan-2022 / QC No. JIDT -21-50591 / Revised: 07-Jan-2022 / Manuscript No. JIDT-21-50591 (R) / Accepted Date: 10-Jan-2022 / Published Date: 17-Jan-2022 DOI: 10.4172/2332-0877.1000484
Abstract
The present study aims to understand the impact of COVID-19 on mental health and physical health behaviors of people in Abu Dhabi. Abu Dhabi residents were approached to fill a survey about how COVID-19 had impacted their lives during May and June 2020, when they were experiencing social distancing and isolation measures for the first time. A total of 36,842 responded to the survey, representing a diverse range of demographical, ethnical, and professional backgrounds. Descriptive analysis and analysis of variance were used to capture the differences of ten categories of psychological feelings and risky health behaviors among different categories of respondents. The results indicated that females recorded significantly higher means for all ten mental and associated physical health variables, while those who are single and separated recorded the highest means for most negative psychological feelings and behaviors. Significant differences were also observed across age categories, except for fear. The illiterates and those have a below secondary school education recorded the highest mean values for those mental health variables. The same was true for the unemployed and homemakers. Emiratis and those living with elderly showed the most significant psychological concerns and challenges. The study provides some recommendations for policy-makers while elaborating on future research directions.
Keywords: COVID-19; Restrictions; Social distancing; Behavior; Abu Dhabi
Introduction
During the COVID-19 pandemic, the Abu Dhabi residents have experienced unprecedented restrictions that touched many aspects of their lives. The UAE and Abu Dhabi governments introduced many strict pandemic prevention and control regulations and measures [1-3]. These COVID-19 prevention protocols and rules affected many aspects of people’s everyday living, including social distancing, isolation, limits of family visits. In addition, certain conventional social behaviors such as shaking hands, embracing, and kissing were recommended to avoid [1,3].
As being similarly witnessed around the world, these measures presented Abu Dhabi residents with significant risks and constellations, which went over and above the health threat associated with COVID-19 to include mental or psychological health issues for them and their whole family [4]. Research elsewhere has identified various stressors faced by residents during COVID-19, including work and family well- being, unemployment and economic uncertainty, reduction in social support, reduction in access to community leisure facilities and sporting activities, homeschooling, and health crisis [5-11]. In general, most of these challenges are known for their negative impact on the well-being of residents outside the context of a pandemic and could lead to mental health problems, domestic violence, and family conflict [12-15].
As far as Abu Dhabi policymakers are concerned, given such unprecedented implications placed on lives during COVID-19, extensive exploratory work is necessary to examine the impact of COVID-19 prevention and control regulations and measures on the lives of residents and their family. Research effort like this present study allows for a better understanding of the various mental health challenges that Abu Dhabi residents have experienced during the COVID-19 pandemic and could better inform relevant policymaking in response to the current COVID pandemic. For Abu Dhabi specifically, it is essential to account for the significant efforts by various government authorities through understanding the psychological and mental challenges faced by different community categories.
Literature Study
The COVID-19 pandemic literature, in general, has revealed various concerns and challenges affecting people at the community level such as imposed restrictions, not being to go out in public, disturbance of social life, less access to regular medical services, less get together with younger children [16-19]. Apart from some physical health issues such as weight losses, eating disorders, and sleeping disorders, the literature has recorded a wide range of psychological feelings and mental health risks reported by people during the pandemic [20-25]. These include untold fear and suffering, sadness, loneliness, stress, irritability, emotional exhaustion, and depression [16,17,19,26-28]. Risky behaviors such as excessive screen use are also widely reported [29].
Fear is one of the most common mental feelings reported during the COVID-19 pandemic. Women were generally more likely to report high levels of fear of COVID-19 [30]. As showed by Koçak, et al. cross- sectional study, women and 16-25 years old youths in Turkey had higher COVID-19 related fear, anxiety, depression, and stress [26]. Bisht, et al. however, found that in India fear of COVID-19 is independent of gender as well as age group [31]. Villalba, et al. also found no age differences in the fear of COVID-19 [32]. Mohammadpour, et al. reported that marital status correlated with the degree of fear of COVID-19 [33]. In Saudi Arabia, Al-Rahimi, et al. assessed the levels of fear and anxiety during the outbreak of COVID-19 and identified gender, lower education, age, and marital status as strong predictors of fear and anxiety [34]. These predictors are generally applicable across different countries [35].
Because of the lockdowns, social isolation and the consequent feeling of loneliness has received much attention during the COVID-19 pandemic [36-39]. Victor, et al. stressed that social isolation is usually experienced as a feeling of anxiety and dissatisfaction associated with a “lack of connectedness or communality with others, and a deficit between the actual and desired quality and quantity of social engagement.” It is worth noticing that social isolation and loneliness are correlated and often used interchangeably [40]. Most studies acknowledge that social isolation and loneliness are essential and paramount due to the detrimental impact on mental and physical health [17,41]. Social isolation and loneliness increase the risk of anxiety, depression, and cognitive dysfunction [42]. Social isolation and loneliness have been treated as severe public health concerns especially among older people [43,44].
During the COVID-19 pandemic, the feelings of depression and sadness touched many individuals around the world [33,45,46]. In general, research suggests that gender, age, and socioeconomic status are all associated with how people are affected by catastrophic events and that women are less likely to have such symptoms than men, and the likelihood of symptoms decreases with age [47-50]. Having an older person at home during the pandemic has also received some attention, as significantly higher rates of depression and disturbed sleep among the caregivers were reported [51].
During the COVID-19 pandemic, stress is a critical challenge reported [52]. The research by Kharaba, et al. in the UAE revealed that the pandemic has significantly influenced daily psychological health such as stress symptoms [53]. Leila, et al. similarly investigated the impact of COVID-19 and societal lockdown measures on the mental health of adults in the UAE, where a large percentage of respondents reported increased stress and irritability. Females, younger participants, part-timers, and college graduates were more likely to have such a symptom. In Saudi Arabia, Tayyeb and Alsolami reported high levels of perceived stress during COVID-19. A study conducted in the province of Shaanxi in China showed that one of the most common psychological and behavioral disorders of children and teenagers between 3 and 18 was irritability [54]. Meanwhile, Karakose, et al. investigated the relationships between the COVID-19 phobias experienced by school administrators [55]. The results revealed that female school administrators experienced more significant levels of COVID-19 irritability than their male counterpart.
Fatigue and exhaustion have been shown to present themselves as a significant psychological symptom of COVID-19 [56-60]. For example, in a study in Turkey Morgul, et al. examined psychologically fatigue and exhaustion during the COVID-19 pandemic and significant differences between people of different age, gender, educational level, occupational status, place of residence, and the number of family members were found [61]. A related symptom is sleep disorder during the COVID-19 pandemic. In a survey that involved respondents from 39 countries, the prevalence of sleep problems was 18% among the general population [62]. Again, sleeping disturbances have been demonstrated to be associated with the type of categories of the population [63-67].
Another focus of researchers is the response of people to stress during pandemics by increasing food intake, especially of palatable, energy-dense foods [68-70]. This observation is more common among women [71,72]. Some warn that this might contribute to more obesity and related diseases [73]. This has been observed during the COVID-19 pandemic, as research findings suggest stress may lead to overeating, especially the intake of high-sugar foods and high-fat foods [74,75].
The results of the Canadian Perspective Survey indicated a significant impact of COVID-19 on screen time and mental health, as more than 60% of respondents reported increasing TV time and Internet usage [29]. Similarly, Helander, et al. reported that the COVID-19 pandemic had increased people’s screen time due to various reasons, including increased time spent on virtual education, working from home, online shopping, and electronic communication with friends and family [76]. In addition, many researchers elaborated that during the COVID-19 pandemic, the strict lock-down and quarantine that were widely imposed resulted in excessive screen and Internet use [77-79]. Most studies found that younger participants reported greater use of media screens [77]. Given the importance of social media during isolation, some analysts attempted to recommend increasing the use of such sources to tackle the feelings of social isolation and anxiety [80-82].
In summary, the table categorizes relevant research findings in the literature, centering around various reported psychological feelings and mental health issues during the COVID-19 pandemic (Table 1). It is worth noticing that while many studies explore the differences of psychological feelings between people of different age, gender, marital status, and education level, the potential differences of psychological feelings and risky health behaviors between people of different employment status and different sectors are rarely examined.
Psychological Feelings | Sources and references |
---|---|
Fear | Ahorsu et al., 2020; Alsharawy et al., 2021; Al-Rahimi et al., 2021; Ali et al., 2021; Haddad et al., 2020; Niño et al., 2021; United Nations, 2020; Villalba et al., 2020 |
Loneliness and isolation | Gerst-Emerson and Jayawardhana, 2015; Heidinger and Richter, 2020; Holt-Lunstad et al., 2010; Käll et al., 2020; Müller et al., 2021; Pierce et al., 2020; Lee et al., 2021; Vitagliano et al., 2021 |
Depressive symptoms and sadness | Holt-Lunstad et al., 2010; Mohammadpour et al., 2021; Koçak et al., 2021); Santini et al., 2020; Vitagliano et al., 2021 |
Stress and irritability | Haddad et al., 2020; Karakose et al., 2021; Klaiber et al., 2020; Kharaba et al., 2021; Leila et al., 2021; Patel, 2021; Pizarro-Ruiz and Ordóñez-Camblor, 2021; Salari et al., 2020; Taylor et al., 2020; Tayyib & Alsolami, 2020; van Tilburg et al., 2020; Waite & Creswell, 2020; Westrupp et al., 2015 |
Fatigue and exhaustion | Huang et al., 2020; Jeste et al., 2020; Morgul et al., 2021; Nicola et al., 2020; Sohrabi et al., 2020; Tian et al., 2020; Wang, Pan, et al., 2020 |
Sleeping disorder | Alimoradi et al., 2021; Kaditis et al., 2021; Lin et al., 2021; Pires et al., 2021; Qiu et al., 2020; Rodríguez-Rey et al., 2020; Wang, Song, et al., 2020; Xiong et al., 2020 |
Overeating | Altena et al., 2020; Epel et al., 2004; Dubé et al., 2005; Gibson, 2012; Haddad et al., 2020; Oliver and Wardle, 1999; Sadler et al., 2021; Touyz et al., 2020; Vitagliano et al., 2021 |
Excessive screen use | Alheneidi at al., 2021; Colley et al., 2020; Girdhar et al., 2020; King et al., 2020; Mucci et al., 2020; Sun et al., 2020 |
Table 1: Common psychological feelings reported during pandemics.
Materials and Methods
This project was part of a large survey examining the impact of the COVID-19 pandemic on Abu Dhabi residents and families. The design of the COVID-19 survey was based on an extensive review of relevant literature. Extensive international research was examined to identify the variant psychological and mental issues and challenges during the COVID-19 pandemic and previous pandemics. Therefore, this research used outputs from a rich body of international research to design a survey instrument for Abu Dhabi and to analyze differences between various community categories.
Approved by the Department of Community Development and conducted jointly with Statistics Center Abu Dhabi, the present study focused on the data specifically related to ten psychological health questions obtained from July to September, 2020, which was the second wave of data (the first wave covered early pandemic periods in late 2019 and early 2020). This was the period of time when most people were trying extensively to navigate social restrictions, isolation policies, and lockdown measures during the pandemic.
The survey questions asked respondents to rate their feelings-fear, loneliness, sadness, stress, irritability, emotional exhaustion, depressive symptoms, sleeping disorder, overeating, and excessive screen use– on a 5 point scale from “not at all” to “a great extent”. Examining the differences of these feelings across various demographics including gender, marital status, age, education, nationality, place of work, and having older people living at home is the objective of this present research.
A descriptive analysis framework was adopted to understand the experiences of respondents living in Abu Dhabi regarding their psychological feelings during the COVID-19 pandemic. In addition to the descriptive approach, SPSS-2020 (IBM Corp., 2020) was used to perform Analysis of Variance (ANOVA) to explore differences between different sample categories [82]. For each of the categories, the ANOVA F-values and their significance were recorded.
Results
Respondents were targeted mainly using online social media systems. A total of 36,842 residents participated in the survey. Table provides a general view of respondents in the survey (Table 2). More than 59.4% fall into the age category of 31 to 40 years old. About 46.1% are female and 53.9% are females. The majority (83.4%) are married. Emiratis comprise of 43.3% of the sample while the majority are non- Emiratis (56.7%). Concerning educational attainment, 45% hold a bachelor’s degree, 21% have a post-graduate degree, 9.8% have a college diploma, 15% have a secondary school diploma, and 3.5% have below secondary school education.
Gender | Percentage |
---|---|
Male | 46.10% |
Female | 53.90% |
Marital status | |
Married | 83.40% |
Single | 7.70% |
Divorced | 2.50% |
Separated | 0.80% |
Widowed | 0.80% |
Education level | |
Illiterate | 0.30% |
Below secondary school | 3.20% |
Secondary school | 15% |
Post high school training certificate | 5.70% |
College diploma | 9.80% |
Bachelor’s degree | 45% |
Master’s degree | 18.30% |
Doctorate degree | 2.70% |
Age | |
15-20 | 2.00% |
21-25 | 3.60% |
26-30 | 9.90% |
31-35 | 34.10% |
36-40 | 25.30% |
41-45 | 19% |
46-50 | 11.90% |
51-55 | 6.10% |
56-60 | 2.50% |
61+ | 1.20% |
Nationality | |
Emirati | 43.30% |
Non-Emirati | 56.70% |
Table 2: Respondent profile.
Table provides the overall means and standard deviations for each of the psychological feelings and risky physical behaviors (Table 3). Overall, the most profound concerns are excessive screen use (3.684), stress (3.050), and fear (2.866). According to the values of the standard deviations, the highest variabilities are observed concerning sleeping disorder (1.442), overeating (1.388), and fatigue and exhaustion (1.363). A significant F-value for all the psychological and behavioral variables is noted. The highest differences (F-values) are recorded for emotional exhaustion, irritability, stress, and sadness. The least significant differences are attributed to excessive screen use, fear, sleeping disorder, and loneliness. Females record higher means for all ten variables.
Variables | Overall means | Standard deviations | Male | Female | F | Sig. |
---|---|---|---|---|---|---|
Fear | 2.866 | 1.183 | 2.725 | 2.991 | 243.914 | 0.0001 |
Loneliness and isolation | 2.711 | 1.353 | 2.544 | 2.858 | 256.33 | 0.0001 |
Sadness | 2.729 | 1.276 | 2.519 | 2.916 | 465.993 | 0.0001 |
Stress | 3.05 | 1.284 | 2.831 | 3.245 | 501.543 | 0.0001 |
Irritability | 2.782 | 1.333 | 2.535 | 3 | 593.59 | 0.0001 |
Fatigue and exhaustion | 2.8 | 1.363 | 2.537 | 3.033 | 645.881 | 0.0001 |
Depressive symptoms | 2.381 | 1.358 | 2.193 | 2.546 | 323.216 | 0.0001 |
Sleeping disorder | 2.623 | 1.442 | 2.449 | 2.776 | 245.753 | 0.0001 |
Overeating | 2.564 | 1.388 | 2.356 | 2.749 | 384.5 | 0.0001 |
Excessive screen use | 3.684 | 1.342 | 3.542 | 3.808 | 185.858 | 0.0001 |
Table 3: Psychological feelings: Means and ANOVA by Gender.
Across respondents of different marital status, significant ANOVA is noted for a total of eight variables, except for fear and irritability (Table 4). The highest F-values for the significant variables are recorded for sleeping disorder (highest mean for separated) and excessive screen use (highest mean for single). The least significant differences are attributed to stress (highest mean for separated), overeating (highest mean for widower), and sadness (highest mean for separated). The married group record the lowest means for all eight variables with significant differences.
Variables | Married | Single | Divorced | Separated | Widower | F | Sig. |
---|---|---|---|---|---|---|---|
Fear | 2.861 | 2.871 | 2.886 | 3.063 | 3.007 | 1.716 | 0.143 |
Loneliness | 2.68 | 2.846 | 2.818 | 3.045 | 3.015 | 12.765 | 0.001 |
Sadness | 2.712 | 2.803 | 2.776 | 3.045 | 2.85 | 5.459 | 0.001 |
Stress | 3.035 | 3.12 | 3.069 | 3.31 | 3.304 | 5.207 | 0.001 |
Irritability | 2.781 | 2.79 | 2.724 | 2.877 | 2.9 | 0.826 | 0.508 |
Emotional exhaustion | 2.77 | 2.962 | 2.843 | 3.237 | 2.9 | 14.24 | 0.001 |
Depressive symptoms | 2.349 | 2.536 | 2.48 | 2.582 | 2.589 | 12.001 | 0.001 |
Sleeping disorder | 2.568 | 2.92 | 2.795 | 2.936 | 2.75 | 34.161 | 0.001 |
Overeating | 2.543 | 2.679 | 2.624 | 2.567 | 2.693 | 5.373 | 0.001 |
Excessive screen use | 3.647 | 3.927 | 3.729 | 3.671 | 3.688 | 21.636 | 0.001 |
Table 4: Psychological feelings: Means and ANOVA by marital status.
Table provides the ANOVA results by age group (Table 5). Significant ANOVA is recorded for all ten variables. The highest F-values for the significant variables are associated with overeating, irritability, and depressive symptoms. The least significant differences are attributed to fear and loneliness. Overall, the younger age groups (15-20, 21-25, 26- 30) tend to record higher means for most of the variables.
Variables | 15-20 | 21-25 | 26-30 | 31-35 | 36-40 | 41-45 | 46-50 | 51-55 | 56-60 | 61+ | F | Sig. |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Fear | 2.769 | 2.996 | 2.991 | 2.963 | 2.937 | 2.81 | 2.705 | 2.661 | 2.706 | 2.682 | 19.272 | 0.0001 |
Loneliness | 2.926 | 2.906 | 2.912 | 2.848 | 2.736 | 2.594 | 2.501 | 2.537 | 2.595 | 2.642 | 23.011 | 0.0001 |
Sadness | 2.847 | 2.923 | 2.939 | 2.855 | 2.776 | 2.653 | 2.529 | 2.499 | 2.434 | 2.529 | 27.384 | 0.0001 |
Stress | 3.185 | 3.193 | 3.264 | 3.198 | 3.12 | 2.979 | 2.823 | 2.8 | 2.66 | 2.645 | 35.438 | 0.0001 |
Irritability | 2.893 | 2.941 | 3.037 | 2.971 | 2.883 | 2.7 | 2.491 | 2.416 | 2.262 | 2.343 | 55.051 | 0.0001 |
Emotional exhaustion | 3.027 | 3.003 | 3.053 | 2.975 | 2.871 | 2.714 | 2.53 | 2.48 | 2.352 | 2.405 | 44.714 | 0.0001 |
Depressive symptoms | 2.717 | 2.654 | 2.634 | 2.587 | 2.456 | 2.244 | 2.088 | 2.074 | 1.923 | 1.957 | 55.116 | 0.0001 |
Sleeping disorder | 3.176 | 2.952 | 2.913 | 2.773 | 2.685 | 2.509 | 2.363 | 2.268 | 2.159 | 2.189 | 50.638 | 0.0001 |
Overeating | 2.989 | 2.861 | 2.817 | 2.793 | 2.624 | 2.43 | 2.306 | 2.183 | 2.116 | 1.967 | 59.258 | 0.0001 |
Excessive screen use | 4.091 | 3.938 | 3.927 | 3.82 | 3.73 | 3.591 | 3.516 | 3.307 | 3.32 | 3.224 | 41.146 | 0.0001 |
Table 5: Psychological feelings: Means and ANOVA by age category.
Focusing on differences by education level, we note significant ANOVA for all ten variables (Table 6). The highest F-values for the significant variables are recorded for overeating, depressive symptoms, and sleeping disorders. The least significant differences are attributed to excessive screen use, emotional exhaustion, and stress. In general, the highest means are observed with people of low educational background (the illiterates and those below high school), except for the variable of excessive screen use where the bachelor’s degree holder group and the high school group record higher means.
Variables | Illiterate | Below high school | High school | Post high school | Diploma | BS | MS | PhD | F | Sig. |
---|---|---|---|---|---|---|---|---|---|---|
Fear | 3.5 | 2.985 | 2.984 | 2.868 | 2.945 | 2.885 | 2.722 | 2.61 | 18.613 | 0.0001 |
Loneliness | 3.263 | 2.847 | 2.859 | 2.72 | 2.772 | 2.742 | 2.507 | 2.575 | 19.638 | 0.0001 |
Sadness | 3.421 | 2.829 | 2.881 | 2.785 | 2.748 | 2.762 | 2.539 | 2.54 | 21.196 | 0.0001 |
Stress | 3.6 | 3.065 | 3.095 | 3.063 | 3.075 | 3.091 | 2.936 | 2.857 | 8.411 | 0.0001 |
Irritability | 3.6 | 2.78 | 2.916 | 2.79 | 2.778 | 2.824 | 2.618 | 2.572 | 16.138 | 0.0001 |
Emotional exhaustion | 3.15 | 2.719 | 2.866 | 2.825 | 2.818 | 2.846 | 2.659 | 2.692 | 8.962 | 0.0001 |
Depressive symptoms | 3.316 | 2.499 | 2.53 | 2.436 | 2.377 | 2.431 | 2.16 | 2.166 | 24.347 | 0.0001 |
Sleeping disorder | 3.2 | 2.771 | 2.807 | 2.748 | 2.66 | 2.649 | 2.389 | 2.45 | 24.195 | 0.0001 |
Overeating | 3.15 | 2.568 | 2.723 | 2.618 | 2.605 | 2.62 | 2.341 | 2.204 | 27.115 | 0.0001 |
Excessive screen use | 3.6 | 3.502 | 3.764 | 3.646 | 3.618 | 3.72 | 3.625 | 3.58 | 5.653 | 0.0001 |
Table 6: Psychological feelings: Means and ANOVA by education level.
Examining the differences by employment status and place of work, the differences of all psychological feelings are again significant (Table 7). The highest significances are observed on irritability, emotional exhaustion, and depressive symptoms. The unemployed and homemakers record the highest means for seven variables. School students and university students record the highest means for sleeping disorder and excessive screen use. Between public sector and private sector employees, people working in the private sector report higher means for emotional exhaustion, depressive symptoms, stress, irritability, sadness, loneliness, and sleeping disorders, while public sector employees have a higher mean for fear, overeating, and excessive screen use.
Variables | Public | Private | Employer | Un-employed | Home-maker | School student | Retired | University student | F | Sig. |
---|---|---|---|---|---|---|---|---|---|---|
Fear | 2.848 | 2.785 | 2.84 | 2.968 | 3.043 | 2.721 | 2.789 | 2.875 | 13.341 | 0.0001 |
Loneliness | 2.611 | 2.64 | 2.759 | 2.924 | 2.988 | 2.797 | 2.613 | 2.868 | 27.572 | 0.0001 |
Sadness | 2.64 | 2.679 | 2.718 | 2.919 | 2.974 | 2.801 | 2.556 | 2.952 | 25.768 | 0.0001 |
Stress | 2.92 | 3.077 | 3.12 | 3.277 | 3.28 | 3.069 | 2.762 | 3.181 | 30.588 | 0.0001 |
Irritability | 2.648 | 2.749 | 2.835 | 2.992 | 3.137 | 2.793 | 2.549 | 2.923 | 43.978 | 0.0001 |
Emotional exhaustion | 2.671 | 2.787 | 2.824 | 2.986 | 3.096 | 2.966 | 2.526 | 2.963 | 33.109 | 0.0001 |
Depressive symptoms | 2.26 | 2.34 | 2.429 | 2.684 | 2.633 | 2.662 | 2.217 | 2.594 | 31.384 | 0.0001 |
Sleeping disorder | 2.527 | 2.582 | 2.654 | 2.973 | 2.765 | 3.097 | 2.375 | 3.018 | 25.113 | 0.0001 |
Overeating | 2.508 | 2.5 | 2.505 | 2.591 | 2.786 | 2.669 | 2.373 | 2.987 | 20.934 | 0.0001 |
Excessive screen use | 3.67 | 3.663 | 3.578 | 3.759 | 3.733 | 4.16 | 3.339 | 4.013 | 12.418 | 0.0001 |
Table 7: Psychological feelings: Means and ANOVA by employment and place of work.
Focusing on the nationality of respondents, we note significant ANOVA for eight variables (Table 8). The highest F-values were recorded for fear, overeating, stress, and excessive screen use. The least significant differences were attributed to emotional exhaustion, sadness, and depressive symptoms. Emiratis record higher means for six variables.
Variables | Emirati | Non-Emirati | F | Sig. |
---|---|---|---|---|
Fear | 2.966 | 2.791 | 102.59 | 0 |
Loneliness | 2.717 | 2.706 | 0.288 | 0.592 |
Sadness | 2.759 | 2.706 | 8.002 | 0.005 |
Stress | 2.999 | 3.089 | 22.66 | 0 |
Irritability | 2.78 | 2.783 | 0.018 | 0.892 |
Emotional exhaustion | 2.772 | 2.822 | 6.178 | 0.013 |
Depressive symptoms | 2.414 | 2.354 | 8.984 | 0.003 |
Sleeping disorder | 2.676 | 2.582 | 19.743 | 0 |
Overeating | 2.638 | 2.508 | 40.691 | 0 |
Excessive screen use | 3.736 | 3.645 | 21.238 | 0 |
Table 8: Psychological feelings: Means and ANOVA by nationality.
The final ANOVA looks at differences between two groups categorized by whether respondent lives with an elderly or not. Table shows significant ANOVA for five variables-fear, depressive symptoms, sleeping disorder, overeating, and excessive screen use (Table 9).
Variables | Yes | No | F | Sig. |
---|---|---|---|---|
Fear | 2.935 | 2.844 | 20.476 | 0 |
Loneliness | 2.679 | 2.721 | 3.207 | 0.073 |
Sadness | 2.761 | 2.719 | 3.619 | 0.057 |
Stress | 3.033 | 3.056 | 1.063 | 0.303 |
Irritability | 2.792 | 2.778 | 0.387 | 0.534 |
Emotional exhaustion | 2.817 | 2.795 | 0.869 | 0.351 |
Depressive symptoms | 2.44 | 2.361 | 11.866 | 0.001 |
Sleeping disorder | 2.717 | 2.593 | 25.97 | 0 |
Overeating | 2.66 | 2.533 | 29.108 | 0 |
Excessive screen use | 3.741 | 3.665 | 11.2 | 0.001 |
Table 9: Psychological feelings: Means and ANOVA by elderly at home or not.
No significance is seen for loneliness, sadness, stress, irritability, and emotional exhaustion. The highest F-values were recorded for overeating, sleeping disorder, and fear. Those with an elderly at home record higher means on all significant variables.
Discussion
During the COVID-19 pandemic, many restrictions and curfews imposed by government have overwhelmingly disrupted and affected the ordinary daily lives of individuals. In this research, we analyzed the impact of COVID-19 on the psychological status, mental health, and associated risky health behaviors witnessed among the residents of Abu Dhabi. This is one of the first attempts in Abu Dhabi to assess COVID-19’s impact on the mental and psychological health of the public. Assessing the public’s mental and physical challenges during a pandemic is of immense importance for policymakers to intervene and tackle adverse outcomes in a timely fashion [16,83-85].
Overall, the most significant psychological and behavioral challenges in Abu Dhabi are associated with excessive screen use, stress, and fear. As far as excessive screen use is concerned, studies in other countries also identified it as one primary outcome in the COVID-19 era [29,76]. In Abu Dhabi and elsewhere in the world, many factors and reasons during the COVID-19 lockdown and quarantine period, more specifically working from home, virtual education, online shopping, and electronic communication with friends and family contributed to that [77-79]. In addition, some creative ways of supporting the general population during the pandemic including new online applications and platforms also contributed to excessive screen use [16,83]. Overall, the psychological symptom of stress and fear is consistent with research findings reported in many other international replications [31,32,54].
Other prevalent mental health concerns in Abu Dhabi include feelings of fatigue and exhaustion, sadness, and loneliness. The symptom of fatigue and exhaustion may be attributed to the emergence of related symptoms such as sadness and loneliness [36-39,44]. The results from Huang, et al., Nicola, et al. and Sohrabi, et al. also reported higher feelings of fatigue and exhaustion shown by females [48,57,58].
Gender differences were evident for all the psychological feelings and physical health variables examined by this research. Compared to males, females in Abu Dhabi reported a higher level of mental issues and concerns. These results are in line with most of the extant international research, including the ones conducted in the UAE [26,53].
The current study highlights that the younger population reported significantly higher levels of negative psychological feelings and risky physical health behaviors. Consistent with other research, excessive screen use is most common among school children and younger youth [77]. Such results give significant importance to the use of social media during isolation [80,81]. Younger cohorts in Abu Dhabi also showed much higher level of feelings stressful, same as reported by other studies [53,54]. It is also important to note that the Abu Dhabi results showed that younger respondents (15-30 years) reported the highest level of feeling lonely, which is contrary to some studies that identified older people as having more serious concerns over loneliness [37,44].
Some vulnerable or disadvantaged groups were hit hardest by mental challenges during the pandemic. In general, the divorced, the separated, and single people showed much more severe psychological health symptoms. These groups of people did not have the companion of partners and family, and thus were more vulnerable when experiencing a pandemic and its associated implications. These results are consistent with those reported by others tackling the issue of loneliness and isolation during the COVID-19 pandemic [33,34,53,79]. Other vulnerable groups when facing the COVID-19 pandemic are those of lower levels of education, who reported a higher level of psychological health issues and feelings, especially stress, loneliness, sadness, and irritability. This result is largely consistent with that of Al-Rahimi, et al., Karakose, et al., and Kharaba, et al. [34,53,55]. This suggests that education, knowledge and cognitive capacity seem to be able to build a buffer for protection against adverse mental challenges. This Abu Dhabi study also supports the findings of Lee, et al., Pierce, et al., and Tymoszuk, et al. that the unemployed and homemakers are likely to experience higher level of fear, loneliness, sadness, and stress [36,38,39].
Screen use was higher for Emiratis and for those who lived with older people. However, for both categories the availability of more spare time might be the reason for engaging in longer online activities and practices. Our results underscore the challenges for those families that have older adults during COVID-19. Members of those families might experience overwhelming duties and burdens that result in some adverse psychological reactions and feelings [86-88]. It should be emphasized that family caregivers or members taking care of older people should receive sufficient professional guidance and support during pandemics such as COVID-19.
One of the strengths of the current study is the relatively large sample size and the cross-sectional design, which allows the generalization of the observations and conclusions for all Abu Dhabi residents and households. In addition, the survey data collection took place during the peak of the COVID-19 pandemic, when all residents in Abu Dhabi felt lockdowns. Thus, the results of the current study are an immediate reflection of real experiences, based on which conclusions are drawn. Furthermore, the study examined a wide range of mental, physical and behavioral issues, while most other studies considered only a few psychological symptoms or feelings. A limitation of the study, however, is that respondents might have interpreted the meanings of some of the ten psychological feeling variables differently from each other.
Conclusion
The Abu Dhabi COVID-19 survey results provide important insights into the different level of mental and physical challenges that various Abu Dhabi residents and community groups experienced during the COVID-19 pandemic lockdown. The results show that females recorded significantly higher means for all psychological feelings. Those who are single and separated recorded the highest means for most feelings. Significant differences in mental health and feelings were observed for all age categories (except fear). The illiterates and those holding degrees below secondary schools recorded the highest mean values for most mental health variables. The same is true for the unemployed, homemakers, Emiratis, and those living with elderly.
These findings can inform public health and social policymakers to focus awareness, intervention and community engagement programs on the most vulnerable community groups during emerging pandemics. The results of this study call for responsible social sector authorities and service providers to implement appropriate interventions to assist those vulnerable groups in Abu Dhabi’s population who show more severe psychological symptoms. The lack of connectedness with others due to social isolation during the pandemic was much severe for the separated, divorced, unemployed, and illiterates, who usually experienced higher levels of feeling of anxiety, stress, and fear. The deficit in social connection has to be addressed through more active social engagement or consultation and services.
Future research should examine the nature of psychological feelings and risky health behaviors throughout the pandemic and post-pandemic periods from a longitudinal perspective. It is advised to carry longitudinal studies using a larger sample base to validate the results of this present study. Such an attempt could provide a more solid and thorough understanding of the mental health issues. It should be stressed that many psychological feelings or mental health variables are significantly correlated with each other. Better psychological scales should be developed, which could better aid in analysis and policy-making. It is also recommended that qualitative interviews be conducted with the different segments of the community with a view to validating the findings of this research and exploring factors and contexts that this survey research failed to capture.
Source of Funding
This research did not receive any grant from funding agencies in the public, commercial, or not-for-profit sectors.
Conflicts of Interest
The authors have no conflict of interest to declare.
Ethical Approval
Ethical consent regarding the protocol of the study was granted by the Department of Community Development (DCD) and the Statistic Center Abu Dhabi (SCAD).
References
- UAE model in confronting coronavirus pandemic, Emirates Policy Center, 2020.
- The UAE government’s initiatives to combat the covid-19 crisis, Federal Competitiveness and Statistics Authority, 2020.
- COVID-19: Abu Dhabi health authority provides guidelines to keep the elderly safe, UAE Health, 2021.
- Evans S, Mikocka-Walus A, Klas A, Olive L, Sciberras E, et al. (2020) From “It has stopped our lives” to “spending more time together has strengthened bonds”: The varied experiences of Australian families during COVID-19. Front Psychol 11: 588667.
[Crossref] [Google Scholar] [PubMed]
- Creswell C, Waite P, Hudson J (2020) Practitioner review: Anxiety disorders in children and young people-assessment and treatment. J Child Psychol Psychiatry 61: 628-643.
[Crossref] [Google Scholar] [PubMed]
- Antipova A, Momeni E (2021) Unemployment in socially disadvantaged communities in Tennessee, US, during the COVID-19. Front Sustain Cities 3: 84.
[Crossref]
- Yang X, Yang X, Kumar P, Cao B, Ma X, et al. (2020) Social support and clinical improvement in COVID-19 positive patients in China. Nurs Outlook 68: 830-837.
[Crossref] [Google Scholar] [PubMed]
- Luo A, Zhong S, Sun C, Wang J, White A (2021) Multiple linear regression analysis of rural-urban COVID-19 risk disparities in Texas. medRxiv 8: 1-13.
- Petts R, Carlson D, Pepin J (2020) A gendered pandemic: Childcare, homeschooling, and parents’ employment during COVID-19. Gender Work Organ 28: 515-534.
- Subhadra E, Antonina M, Anna K, Lisa O, Emma S, et al. (2020) It Has Stopped Our Lives” to “Spending More Time Together Has Strengthened Bonds”: The Varied Experiences of Australian Families During COVID-19. Front Psychol 11: 2906.
[Crossref] [Google Scholar] [PubMed]
- Cui J, Lu J, Weng Y, Yi GY, He W (2021) Impact of COVID-19 on mental health: A longitudinal study using penalized logistic regression. medRxiv 7: 1-16.
- Bakusic J, Schaufeli W, Claes S, Godderis L (2017) Stress, burnout and depression: A systematic review on DNA methylation mechanisms. J Psychosom Res 92: 34-44.
[Crossref] [Google Scholar] [PubMed]
- Leigh-Hunt N, Bagguley D, Bash K, Turner V, Turnbull S, et al. (2017) An overview of systematic reviews on the public health consequences of social isolation and loneliness. Public Health 152: 157-171.
[Crossref] [Google Scholar] [PubMed]
- Reifels L, Mishara BL, Dargis L, Vijayakumar L, Phillips MR, et al (2018) Outcomes of community-based suicide prevention approaches that involve reducing access to pesticides: A systematic literature review. Suicide Life Threat Behav 49: 1019-1031.
[Crossref] [Google Scholar] [PubMed]
- Vahedi Z, Zannella L, Want SC (2019) Students’ use of information and communication technologies in the classroom: Uses, restriction, and integration. Active Learn High Educ 22: 215-228.
- Käll A, Bäck M, Welin C, Åman H, Bjerkander R, et al. (2021) Therapist-guided internet-based treatments for loneliness: A randomized controlled three-arm trial comparing cognitive behavioral therapy and interpersonal psychotherapy. Psychother Psychosom 90: 351-358.
[Crossref] [Google Scholar] [PubMed]
- Santini ZI, Jose PE, York Cornwell E, Koyanagi A, Nielsen L, et al. (2020) Social disconnectedness, perceived isolation, and symptoms of depression and anxiety among older Americans (NSHAP): A longitudinal mediation analysis. Lancet Public Health 5: e62-e70.
[Crossref] [Google Scholar] [PubMed]
- Takashima R, Onishi R, Saeki K, Hirano M (2020). Perception of COVID-19 restrictions on daily life among Japanese older adults: A qualitative focus group study. Healthcare 8: 450.
[Crossref] [Google Scholar] [PubMed]
- Klaiber P, Wen J H, DeLongis A, Sin N L (2021) The ups and downs of daily life during COVID-19: Age differences in affect, stress, and positive events. J Gerontol B Psychol Sci Soc Sci 76: e30-e37.
[Crossref] [Google Scholar] [PubMed]
- Constandt B, Thibaut E, De Bosscher V, Scheerder J, Ricour M, et al. (2020) Exercising in times of lockdown: An analysis of the impact of COVID-19 on levels and patterns of exercise among adults in Belgium. Int J Environ Res Public Health 17: 4144.
[Crossreff] [Google Scholar] [PubMed]
- Owen AJ, Tran T, Hammarberg K, Kirkman M, Fisher J (2021) Poor appetite and overeating reported by adults in Australia during the coronavirus-19 disease pandemic: A population-based study. Public Health Nutr 24: 275-281.
[Crossref] [Google Scholar] [PubMed]
- Altena E, Baglioni C, Espie CA, Ellis J, Gavriloff D, et al. (2020) Dealing with sleep problems during home confinement due to the COVID-19 outbreak: Practical recommendations from a task force of the European CBT-I academy. J Sleep Res 29: e13052.
[Crossref] [Google Scholar] [PubMed]
- Touyz S, Lacey H, Hay P (2020) Eating disorders in the time of COVID-19. J Eat Disord 8: 19.
[Crossref] [Google Scholar] [PubMed]
- Vitagliano JA, Jhe G, Milliren CE, Lin JA, Spigel R, et al. (2021) COVID-19 and eating disorder and mental health concerns in patients with eating disorders. J Eat Disord 9: 80.
[Crossref] [Google Scholar] [PubMed]
- Pires L, De Carvalho L, Rawet E (2021) Multi-dimensional inequality and covid-19 in Brazil. Inv Econ 80: 33-58.
- Koçak O, Koçak ÖE, Younis MZ (2021) The psychological consequences of COVID-19 fear and the moderator effects of individuals’ underlying illness and witnessing infected friends and family. Int J Environ Res Public Health 18: 1836.
[Crossref] [Google Scholar] [PubMed]
- Policy briefs: The impact of COVID-19 on older persons, United Nations, 2020.
- van Tilburg, Theo G, Steinmetz S, Stolte E, van der Roest H, et al. (2020) Loneliness and mental health during the COVID-19 pandemic: A study among Dutch older adults. J Gerontol B Psychol Sci Soc Sci. 76: e249-e255.
[Crossref] [Google Scholar] [PubMed]
- Colley RC, Bushnik T, Langlois K (2020) Exercise and screen time during the COVID-19 pandemic. Health Rep 31: 3-11.
[Crossref] [Google Scholar] [PubMed]
- Niño M, Harris C, Drawve G, Fitzpatrick K (2021) Race and ethnicity, gender, and age on perceived threats and fear of COVID-19: Evidence from two national data sources. SSM Popul Health 13: 100717.
[Crossref] [Google Scholar] [PubMed]
- Bisht IP, Bisht RK, Sagar P (2021) Effect of gender and age in fear and stress due to COVID-19. J Hum Behav Soc Environ 31: 70-76.
[Crossref]
- Villalba AA, Stanley JT, Turner JR, Vale MT, Houston ML (2020) Age differences in preferences for fear-enhancing vs. fear-reducing news in a disease outbreak. Front Psychol 11: 589390.
[Crossref] [Google Scholar] [PubMed]
- Mohammadpour M, Ghorbani V, Khoramnia S, Ahmadi SM, Ghvami M, et al. (2020) Anxiety, self-compassion, gender differences and COVID-19: Predicting self-care behaviors and fear of COVID-19 based on anxiety and self-compassion with an Emphasis on gender differences. Iran J Psychiatry 15: 213-219.
[Crossref] [Google Scholar] [PubMed]
- Al-Rahimi JS, Nass NM, Hassoubah SA, Wazqar DY, Alamoudi SA (2021) Levels and predictors of fear and health anxiety during the current outbreak of COVID-19 in immunocompromised and chronic disease patients in Saudi Arabia: A cross-sectional correlational study. PLoS One 16: e0250554.
[Crossref] [Google Scholar] [PubMed]
- Ali M, Uddin Z, Banik PC, Hegazy FA, Zaman S, et al. (2021) Knowledge, attitude, practice, and fear of COVID-19: An online-based cross-cultural study. Int J Ment Health Addict 30: 1-16.
[Crossref] [Google Scholar] [PubMed]
- Lee SL, Pearce E, Ajnakina O, Johnson S, Lewis G, et al. (2021) The association between loneliness and depressive symptoms among adults aged 50 years and older: A 12-year population-based cohort study. Lancet Psychiatry 8: 48-57.
[Crossref] [Google Scholar] [PubMed]
- Müller F, Röhr S, Reininghaus U, Riedel-Heller SG (2021) Social isolation and loneliness during COVID-19 lockdown: Associations with depressive symptoms in the German old-age population. Int J of Environ Res Public Health 18: 3615.
[Crossref] [Google Scholar] [PubMed]
- Pierce M, Hope H, Ford T, Hatch S, Hotopf M, et al. (2020) Mental health before and during the COVID-19 pandemic: A longitudinal probability sample survey of the UK population. Lancet Psychiatry 7: 883-892.
[Crossref] [Google Scholar] [PubMed]
- Tymoszuk U, Perkins R, Fancourt D, Williamon A (2020) Cross-sectional and longitudinal associations between receptive arts engagement and loneliness among older adults. Soc Psychiatry Psychiatr Epidemiol 55: 891-900.
[Crossref] [Google Scholar] [PubMed]
- Steptoe A, Shankar A, Demakakos P, Wardle J (2013) Social isolation, loneliness, and all-cause mortality in older men and women. Pro Natl Acad of Sci USA 110: 5797-5801.
[Crossref] [Google Scholar] [PubMed]
- Barth J, Schneider S, Von Känel R (2010) Lack of social support in the etiology and the prognosis of coronary heart disease: A systematic review and meta-analysis. Psychosom Med 72: 229-238.
[Crossref] [Google Scholar] [PubMed]
- Holt-Lunstad J, Smith TB, Layton JB (2010) Social relationships and mortality risk: A meta-analytic review. Plos One 2: 5-15.
[Crossref] [Google Scholar] [PubMed]
- Gerst-Emerson K, Jayawardhana J (2015) Loneliness as a public health issue: The impact of loneliness on health care utilization among older adults. Am J Public Health 105: 1013-1019.
[Crossref] [Google Scholar] [PubMed]
- Heidinger T, Richter L (2020) The effect of COVID-19 on loneliness in the elderly: An empirical comparison of pre- and peri-pandemic loneliness in community-dwelling elderly. Front Psychol 11: 585308.
[Crossref] [Google Scholar] [PubMed]
- Bueno-Notivol J, Gracia-García P, Olaya B, Lasheras I, López-Antón R, et al. (2021) Prevalence of depression during the COVID-19 outbreak: A meta-analysis of community-based studies. Int J Clin Health Psychol 21: 100196.
[Crossref] [Google Scholar] [PubMed]
- Perlis RH, Ognyanova K, Santillana M, Baum MA, Lazer D, et al. (2021) Association of acute symptoms of COVID-19 and symptoms of depression in adults. JAMA Netw Open 4: e213223.
[Crossref] [Google Scholar] [PubMed]
- Callen M, Isaqzadeh M, Long JD, Sprenger C (2014) Violence and risk preference: Experimental evidence from Afghanistan. Am Econ Rev 104: 123-148.
- Huang L, Zhou Y, Han Y, Hammitt JK, Bi J (2013) Effect of the Fukushima nuclear accident on the risk perception of residents near a nuclear power plant in China. Proc Natl Acad Sci U S A 110: 19742-19747.
[Crossref] [Google Scholar] [PubMed]
- Ibuka Y, Chapman GB, Meyers LA, Li M, Galvani AP, et al. (2010) The dynamics of risk perceptions and precautionary behavior in response to 2009 (H1N1) pandemic influenza. BMC Infect Dis 10: 296.
[Crossref] [Google Scholar] [PubMed]
- Jang WM, Kim UN, Jang DH, Jung H, Cho S, et al. (2020) Influence of trust on two different risk perceptions as an affective and cognitive dimension during Middle East respiratory Syndrome Coronavirus (MERS-CoV) outbreak in South Korea: Serial cross-sectional surveys. BMJ Open 10: e033026.
[Crossref] [Google Scholar] [PubMed]
- Scott SR, Rivera KM, Rushing E, Manczak EM, Rozek CS, et al. (2021). “I Hate This”: A Qualitative Analysis of Adolescents' Self-Reported Challenges during the COVID-19 Pandemic. J Adolesc Health 68(2): 262-269.
- Fegert JM, Vitiello B, Plener PL, Clemens V (2020) Challenges and burden of the coronavirus 2019 (COVID-19) pandemic for child and adolescent mental health: A narrative review to highlight clinical and research needs in the acute phase and the long return to normality. Child Adolesc Psychiatry Ment Health 14: 20.
[Crossref] [Google Scholar] [PubMed]
- Kharaba Z, Al-Azzam S, Alhusban A, Nuseir K (2021) A look behind the scenes: COVID-19 impact on depression and perceived stress of UAE population. Middle East Curr Psychiatry 28: 35.
[Crossref] [Google Scholar] [PubMed]
- Jiao WY, Wang LN, Liu J, Fang SF, Jiao FY, et al. (2020) Behavioral and Emotional Disorders in Children during the COVID-19 Epidemic. J Pediatr 221: 264-266.
[Crossref] [Google Scholar] [PubMed]
- Karakose T, Yirci R, Papadakis S (2021) Exploring the interrelationship between COVID-19 phobia, work-family conflict, family-work conflict, and life satisfaction among school administrators for advancing sustainable management. Sustainability 13: 8654.
- Huang C, Wang Y, Li X, Ren L, Zhao J, et al. (2020) Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 395: 497-506.
[Crossref] [Google Scholar] [PubMed]
- Nicola M, Alsafi Z, Sohrabi C, Kerwan A, Al-Jabir A, et al. (2020) The socio-economic implications of the coronavirus and COVID-19 pandemic: A review. Int J Surg 78: 185-193.
- Sohrabi C, Alsafi Z, O’Neill N, Khan M, Kerwan A, et al. (2020) World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19). Int J Surg 6: 71-76.
[Crossref] [Google Scholar] [PubMed]
- Tian S, Hu N, Lou J, Chen K, Kang X, et al. (2020) Characteristics of COVID-19 infection in Beijing. J Infect 80: 401-406.
[Crossref] [Google Scholar] [PubMed]
- Wang C, Pan R, Wan X, Tan Y, Xu L, et al. (2020) Immediate psychological responses and associated factors during the initial stage of the 2019 corona virus disease (COVID-19) epidemic among the general population in China. Int J Environ Res Public Health 17: 1729.
[Crossref] [Google Scholar] [PubMed]
- Morgul E, Bener A, Atak M, Akyel S, Aktaş S, et al. (2021) COVID-19 pandemic and psychological fatigue in Turkey. Int J Soc Psychiatry 67: 128-135.
[Crossref] [Google Scholar] [PubMed]
- Alimoradi Z, Broström A, Tsang HWH, Griffiths MD, Haghayegh S, et al. (2021) Sleep problems during COVID-19 pandemic and its' association to psychological distress: A systematic review and meta-analysis. EClinicalMedicine 36: 100916.
[Crossref] [Google Scholar] [PubMed]
- Lin LY, Wang J, Miao Q, Chen R, Liang FX, et al. (2021) The immediate impact of the 2019 novel coronavirus (COVID-19) outbreak on subjective sleep status. Sleep Med 77: 348-354.
[Crossref] [Google Scholar] [PubMed]
- Qiu D, Yu Y, Li RQ, Li YL, Xiao SY (2020) Prevalence of sleep disturbances in Chinese healthcare professionals: A systematic review and meta-analysis. Sleep Med 67: 258-266.
[Crossref] [Google Scholar] [PubMed]
- Rodríguez-Rey R, Garrido-Hernansaiz H, Collado S (2020) Psychological impact and associated factors during the initial stage of the coronavirus (COVID-19) pandemic among the general population in Spain. Front Psychol 11: 1540.
[Crossref] [Google Scholar] [PubMed]
- Xiong J, Lipsitz O, Nasri F, Lui L, Gill H, et al. (2020) Impact of COVID-19 pandemic on mental health in the general population: A systematic review. J Affect Disord. 277: 55-64.
[Crossref] [Google Scholar] [PubMed]
- Wang W, Song W, Xia Z, He Y, Tang L, et al. (2020) Sleep disturbance and psychological profiles of medical staff and non-medical staff during the early outbreak of COVID-19 in Hubei province, China. Front Psychiatry 11: 733.
[Crossref] [Google Scholar] [PubMed]
- Epel E, Jimenez S, Brownell K, Stroud L, Stoney C, et al. (2004) Are stress eaters at risk for the metabolic syndrome?. Ann N Y Acad Sci 1032: 208-210.
- Oliver G, Wardle J (1999) Perceived effects of stress on food choice. Physiol Behav 66: 511-515.
[Crossref] [Google Scholar] [PubMed]
- Tryon MS, Carter CS, Decant R, Laugero KD (2013) Chronic stress exposure may affect the brain’s response to high calorie food cues and predispose to obesogenic eating habits. Physiol Behav 120: 233-242.
[Crossref] [Google Scholar] [PubMed]
- From “It has stopped our lives” to “spending more time together has strengthened bonds”: The varied experiences of Australian families during COVID-19
- Gibson EL (2012) The psychobiology of comfort eating: Implications for neuropharmacological interventions. Behav Pharmacol 23: 442-460.
[Crossref] [Google Scholar] [PubMed]
- Hackett RA, Steptoe A (2017) Type 2 diabetes mellitus and psychological stress - A modifiable risk factor. 13: 547-560.
[Crossref] [Google Scholar] [PubMed]
- Haddad C, Zakhour M, Bou Kheir M, Haddad R, Al Hachach M, et al. (2020) Association between eating behavior and quarantine/confinement stressors during the coronavirus disease 2019 outbreak. J Eat Disord 8: 40.
[Crossref] [Google Scholar] [PubMed]
- Sadler JR, Thapaliya G, Jansen E, Aghababian AH, Smith KR, et al. (2021) COVID-19 stress and food intake: Protective and risk factors for stress-related palatable food intake in U.S. adults. Nutrients 13: 901.
[Crossref] [Google Scholar] [PubMed]
- Helander M, Cushman S, Monnat S, A public health side effect of the coronavirus pandemic: Screen timerelated eye strain and eye fatigue, Population Health Research Brief Series, Syracuse University, 2021.
- Alheneidi H, AlSumait L, AlSumait D, Smith AP (2021) Loneliness and problematic internet use during COVID-19 lock-down. Behav Sci (Basel) 11: 5.
[Crossref] [Google Scholar] [PubMed]
- King DL, Delfabbro PH, Billieux J, Potenza MN (2020) Problematic online gaming and the COVID-19 pandemic. J Behav Addict 9: 184-186.
[Crossref] [Google Scholar] [PubMed]
- Sun Y, Li Y, Bao Y, Meng S, Sun Y, et al. (2020) Brief report: Increased addictive internet and substance use behavior during the COVID-19 pandemic in China. Am J Addict 29: 268-270.
[Crossref] [Google Scholar] [PubMed]
- Girdhar, R, Srivastava V, Sethi S (2020) Managing mental health issues among elderly during COVID-pandemic. Journal of Geriatric Care and Research 7: 32-35.
- Mucci F, Mucci N, Diolaiuti F (2020) Lock-down and isolation: Psychological aspects of COVID-19 pandemic in the general population. Clinical Neuropsychiatry, 17: 63-64.
[Crossref] [Google Scholar] [PubMed]
- IBM SPSS statistics for windows, version 27.0. Armonk, NY: IBM Corp, IBM Corp, 2020.
- Berg-Weger M, Morley JE (2020) Loneliness and social isolation in older adults during the covid-19 pandemic: Implications for gerontological social work. J Nutr Health Aging 14: 1-3.
[Crossref] [Google Scholar] [PubMed]
- The impact of COVID-19 on older adults, Johns Hopkins University, 2020.
- Newman M, Zainal N (2020) The value of maintaining social connections for mental health in older people. Lancet Public Health 5: e12-13.
[Crossref] [Google Scholar] [PubMed]
- Beach S, Schulz R, Donovan H, Rosland A (2021) Family caregiving during the covid-19 pandemic. Drug Gerontologist 61: 650-660.
[Crossref] [Google Scholar] [PubMed]
- Ettman CK, Abdalla SM, Cohen GH, Sampson L, Vivier PM, et al. (2020) Prevalence of depression symptoms in US adults before and during the COVID-19 pandemic. JAMA Netw Open 3: e2019686.
[Crossref] [Google Scholar] [PubMed]
- Schulz R, Beach SR, Czaja SJ, Martire LM, Monin JK (2020) Family caregiving for older adults. Annu Rev Psychol 71: 635-659.
[Crossref] [Google Scholar] [PubMed]
Citation: Badri M, Alkhaili M, Aldhaheri H, Yang G, Albahar M, et al. (2022) Who were Psychologically more Vulnerable During Covid-19? Examining the Patterns of Psychological Feelings and Risk Behaviors in Abu Dhabi. J Infect Dis Ther 10: 484. DOI: 10.4172/2332-0877.1000484
Copyright: © 2022 Badri M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Share This Article
Recommended Journals
Open Access Journals
Article Tools
Article Usage
- Total views: 3267
- [From(publication date): 0-2022 - Nov 21, 2024]
- Breakdown by view type
- HTML page views: 2857
- PDF downloads: 410