The coronavirus, designated as COVID-19, is an infectious disease which emerged initially in the city of Wuhan in China in late December 2019 before spreading rapidly into a global pandemic. In response to this global health crisis, quarantine and lock down measures were implemented by Malaysian government to contain the rapid spread of the virus. The lockdown included stringent measures such as suspension of flights, avoidance of large gatherings, mandatory use of face mask in many countries, social distancing, teleworking, home-schooling of children, and health orders to stay at home. After 2 years of battle with the virus, Malaysia is gradually shifting into the endemic phase. Living with COVID-19 requires several amendments such as lifestyle modifications and the way we live or interact with people as well as our surroundings. Although Malaysia is entering an endemic phase, fear of COVID-19 lingers. Some even develop mental illness such as anxiety, depression and obsessive-compulsive disorder as a repercussion. In other words, shifting into a new norm is challenging for many. Coping skill on the other hand is a valuable resource which aids an individual in face of an adversity. The World Health Organization has identified three main coping mechanisms which are generally employed by people to overcome their troubles namely; avoidance, emotional and problem solving coping mechanism.
Thus, this recent study was conducted with aims to examine the impact of the COVID-19 outbreak on quality of life (QOL), the overall fear of COVID-19 among Malaysians as well as the type of coping mechanisms which are most frequently used. Other possible factors such as sociodemographic background which may play an important role are taken into consideration as well. We hypothesize that problem based coping mechanism may be beneficial to help overcome COVID-19-related problems. Conversely, negative coping mechanisms such as avoidance may be correlated with higher levels of fear toward COVID-19 and negatively correlated with QOL. We will also evaluate important sociodemographic factors such as age, gender, marital status, education, employment, and history of contact with COVID-19.
Study design and participants
This web-based survey was conducted in a cross-sectional approach. The sample was drawn from all states across Malaysia. Data collection from each state was conducted from a tertiary psychiatric hospital with a minimum of one psychiatrist acting as a coordinator in site. Inclusion criteria requires participants to be consenting Malaysian adults aging 18 years and above. Non Malaysians or people aged <18 years of age were excluded from the study. Participants were recruited electronically using targeted advertising methods in order to generate large-scale distribution. Scan able QR codes were put up at several strategic locations such as vaccination centers and city squares to aid with distribution process. There was no restriction on the total number of participants; however, a minimum target of 1400 participants were desired based on an initial pilot study of similar design. Responses are then uploaded into Google-Form for further analysis. A total of 4904 participants completed the survey and their data were included in the analysis. The questionnaires were prepared using Google Document Forms in the English and Bahasa Malaysia languages which are two of the most widely used languages in Malaysia. Participants are given the chance to choose the language of preference as well as filling up an online consent form before proceeding to answer the respective questionnaires. They were also able to freely withdraw at any time without giving explanations and no personal identification were requested to retain participant’s confidentiality. Participants were given no incentives for participating in this survey. The system of Google Forms only provides responses for questionnaires with 100% completion rate. The responses were then processed with IBM Statistical Package for the Social Sciences (SPSS). The present study followed the ethical code for web-based research and conforms to the principles embodied in the Declaration of Helsinki. The study protocol was approved by the Malaysian Research Ethics Committee and registered with National Malaysian Research Registry.
Demographic information includes characteristics of the respondents was collected including age, gender, state of residence, education level, employment status, marital status, employment status, financial status (designated as T20, M40 and B40) and history of being in contact with COVID-19.
Quality of life (WHOQOL-BREF)
The WHOQOL-BREF is a 26-item QOL assessment tool. There are 4 domains assessed: physical health, psychological, social relationship, and environment. Each item is rated on a 5-point Likert scale, scored from 1 to 5. The Malay validated version has a Cronbach’s alpha estimate of 0.64–0.80 for the domains.
Fear of COVID-19 scale
The Fear of COVID-19 Scale will assess stressor. It is unidimensional with 7 items but appears to be robust in measuring the stressor of COVID-19 upon an individual. It has good internal consistency, reliability and validity. The Malay version of this scale is ready for use under public domain and has equivalent properties as the original.
Brief Coping Orientation to Problems Experienced scale
The Brief Coping Orientation to Problems Experienced (COPE) scale is a 28-item multidimensional measure of strategies used for coping or regulating cognition in response to stressors. It is comprised of items that assess the frequency with which a person uses different coping strategies rated on a scale from 1 to 4. There are 14 2-item subscales within the Brief COPE and each coping strategy is analyzed separately: (1) self-distraction, (2) active coping, (3) denial, (4) substance use, (5) use of emotional support, (6) use of instrumental support, (7) behavioral disengagement, (8) venting, (9) positive reframing, (10) planning, (11) humor, (12) acceptance, (13) religion, and (14) self-blame. The Malay version is now available for use. The reliability analysis suggested that the Malay version of Brief COPE has Cronbach’s alpha value of more than 0.79.
Data distribution was tested with the use of Kolmogorov–Smirnov test of normality. Descriptive statistics for the sociodemographic characteristics were reported as frequencies and percentages. Fear of COVID-19, Brief COPE and WHOQOL-BREF scores were presented as means and standard deviations. Pearson correlation factor was used to analyze correlation between domains. A hierarchical linear model was utilized to assess the effect of sociodemographic factors on continuous total score. Variables included in the final model were selected using multivariate hierarchical linear regression analysis and only factors with a cut-off value of P < 0.2 was selected.
The sociodemographic characteristics of the study population are presented in Table 1. The female to male ratio was almost 4:1, with 83.7% being females. The majority of surveyed individuals have a mean age of 32, (ranging between 18 and 76), 54% were married, 40% had a master’s degree, 68.0% were employed, 82% were not working from home, hails from the bottom strata B40 (67.0%), no medical comorbid 77% and (41%) had at least one encounter with COVID-19. Table 2 shows that 59.1% of Malaysians perceive low quality of life whilst 47.3% report high lvels of fear towards COVID-19. Emotion based coping mechanism is the most frequentl usedcoping mechanism with a mean score of 30 (6.0).
In Table 3, means, standard deviations, and correlations for QOL are reported. Pearson product–moment correlation was used to test bivariate associations between variables in the study. Examination of the correlation matrix indicated significant and small to strong correlations between all variables with QOL, but none of these variables indicated significant multicollinearity (r > 0.90) Psychological factors including fear of COVID-19, emotional coping, avoidance coping, were inversely correlated with QOL, while problem focused coping had positive correlation with QOL. Emotional coping strategy showed weak correlation but significant correlation with QOL (r = −0.14, P < 0.001).
Predicting quality of life
In model 1, we run a linear regression analysis to predict QOL [Table 4] without controlling the demographic factors, medical comorbidities, and COVID-19-related experiences. The inclusion of psychological predictors made significant contributions to the regression equation, explaining 65.0% of the variance in QOL (F = 765.86, df = 4, 4767, P = 0.001). Fear of COVID-19, emotional, problem solving and avoidance coping, emerged as significant predictors. The sign of the beta weight indicates that problem solving coping mechanism emerged as the strongest predictor (β = 0.50, P < 0.001). Thus, higher fear of COVID-19, greater use of emotional and avoidance coping, significantly predicted lower QOL. On the other hand, problem based coping mechanism appears to be positively correlated with higher scores in QOL.
In model 2, demographic factors, medical comorbidities, and COVID-19-related experiences were controlled in multiple regression analysis to determine whether psychological related variables, namely, fear of COVID-19 and coping strategies contributed significant variance beyond that accounted for by previously identified known (i.e., demographic factors) correlates of QOL. The multiple regression analyses was performed using hierarchical regression to rule out alternative explanations and to reduce error variance (Becker, 2005).
Table 5 shows results from hierarchical multiple regression models predicting QOL adjusted by selected control variables. Demographic variables were entered first and accounted for adjusted R2 = 2% Fear of COVID-19 (F = 86.10, df = 7, 4874, P = 0.001). Gender, age, education status, working from home, B40 income, and marital status were significant predictors at this stage. QOL increased with age and decreased with lower education level and lower social economic status. Being married also appears to be positively correlated with QOL.
Entered in the second step, medical comorbidities and COVID-19-related experience variables, accounted for an additional 5.3% of the variance (F = 51.18, df = 6, 4869, P = 0.001). All predictors were significant except history of being infected. This suggests lower levels of QOL were reported among people with medical comorbidities (M = 79.11; standard deviation [SD] = 17.44) than those without comorbidities (M = 85.97; SD = 16.23). People with histories of family (M = 82.63, SD = 16.59) and acquaintance (M = 83.01; 17.45) being affected and histories of family (M = 81.27; SD = 17.09) and acquaintances (M = 83.34; SD = 16.33) death due to COVID-19 had lower QOL compared to those with no such histories (M = 85.11; SD = 16.78; M = 85.74; SD = 15.96; M = 84.71; SD = 16.70; M = 84.59; SD = 16.84, respectively).
In the final step, psychological predictors; fear of COVID-19 and three types coping strategies were included, controlling for the other variables. This added an increment of 28.0% of variance explaining QOL (F = 1699.63, df = 5, 4864, P = 0.001). The results revealed that QOL negatively associated with Fear of COVID-19, emotional and avoidance coping, but positively related with problem focused coping strategy. Age, education status and income remained significant at all steps, suggesting the fact that these variables were predictors of QOL despite having beta weight ranging from 0.01 to 0.11. Overall, the entire model explains 43% of the total variance in QOL, with coping mechanism and fear-related predictors contributing to the largest amount of variance in QOL.
Predicting fear of COVID-19
In Table 6, means, standard deviations, and correlations for fear of COVID-19 are reported. Pearson product–moment correlation was used to test bivariate associations between variables. The correlation matrix indicated significant correlation between all variables with Fear of COVID-19. Problem focused coping, emotional and avoidance coping were positively correlated with Fear of COVID-19, whereas QOL correlated negatively with Fear of COVID-19.
Predicting fear of COVID-19
Table 7 shows a linear regression analysis to predict Fear of COVID-19 without controlling the demographic factors, medical comorbidities and COVID-19-related experiences (Model 1). The inclusion of psychological predictors; three types of coping strategies, and QOL made significant contributions to the regression equation, explaining 10.7% of the variance in Fear of COVID-19 (F = 1126.53, df = 5, 4879, P = 0.001). Problem focused coping, emotional coping, avoidance coping and QOL were all significant predictors. The sign of the beta weight indicates that QOL had the strongest beta (β = −0.21, P < 0.001). Thus, greater use of problem focused coping, emotional and avoidance coping significantly predicted higher fear of COVID-19. General QOL had significant negative beta weight, suggesting that higher Fear of COVID-19 was reported among those with lower QOL.
In model 2, demographic factors, medical comorbidities, and COVID-19-related experiences were controlled in multiple regression analysis. Table 8 shows results from hierarchical multiple regression models predicting fear of COVID-19 adjusted by selected control variables. Demographic variables entered first step, accounted for adjusted R2 = 2% of Fear of COVID-19 (F = 20.60, df = 7, 4875, P = 0.001). Gender, marital status, working from home, income, and educational status were significant predictors at this stage. The reported Fear of COVID-19 was significantly higher females (M = 21.47; SD = 5.22) than males (M = 20.39; SD = 5.75), among married people (M = 21.53; SD = 5.22) than single (M = 20.95; SD = 5.45), among those with lower education (M = 21.74; SD = 5.19) than higher education background (M = 20.62; SD = 5.45), among those from lower family income group (M = 21.63; SD = 5.38) than higher income group (M = 21.15, SD = 5.26), and among those who work from home (M = 21.92, SD = 5.55) than those who were not working from home (M = 84.75; SD = 16.83).
Medical comorbidities and COVID-19-related experience variables were entered at second step, accounted for an additional 1% of the variance (F = 12.58, df = 6, 4869, P = 0.001). Medical comorbidities, history of death among family members and acquaintances due to COVID-19 were significant predictors. This suggests higher Fear of COVID-19 were reported among people with medical comorbidities (M = 22.04; SD = 5.63) than those without comorbidities (M = 21.07; SD = 5.21). People with histories of family (M = 22.70; SD = 5.75) and acquaintances (M = 22.24; SD = 5.56) death due to COVID-19 had higher fear compared to those with no such death of family (M = 21.15; SD = 5.26) and acquaintances (M = 21.12; SD = 5.26) histories.
The psychological predictors, namely, three types coping strategies, and QOL were included, controlling for the other variables in the final step. This added an increase of 10% of variance explaining fear of COVID-19 (F = 105.19, df = 5, 4864, P = 0.001). The results revealed that higher fear of COVID-19 was predicted by higher use of problem focused coping, emotional and avoidance coping. On the other hand, reported of lower QOL predicted higher fear of COVID-19. Gender, working from home, income, marital status, education status, history of death among family and acquaintances remained significant at all steps, suggesting the fact that these variables were relevant predictors of Fear of COVID-19. The model explains 13% of the total variance in explaining Fear of COVID-19.
This study aimed to investigate the impact of the COVID-19 outbreak on mental health, QOL, coping skills, and fear of COVID-19 among Malaysians. The survey was conducted on 2021, approximately 1 year after the outbreak. A total of 4904 respondents completed the survey, with a ratio of male to female being 1:4. Majority of Malaysians surveyed have a mean age of 32, (ranging between 18 and 76), 54% were married, 40% had a master’s degree, 68.0% were employed, 82% were not working from home, hails from the bottom strata B40 (67.0%), no medical comorbid (77%), and (41%) had at least one encounter with COVID-19. Sociodemographic data trend is similar to other large-scale studies conducted earlier in Malaysia utilizing similar design which revealed an approximate ratio of male to female participant from (1:3 to 1:4)[14,15] There is an increase in the number of B40 from 53% in 2020 to 67% in 2021, possibly due to the increase in unemployment rates; 8% in 2020 compared to 31.8% in 2021. This result appears to be a global phenomenon with several countries reporting increase in unemployment rates during the pandemic[16,17] Fear of COVID-19 scores show that 47.3% of Malaysians have high levels of fear toward COVID-19 with scores ranging from 22 to 35. Most respondents fear the virus itself with mean score of 3.69 (0.94) while fear of losing their life ranks as the second highest cause of fear with mean score of 3.56 (1.1). Fear of an unknown disease and death is a common yet disturbing psychological issue harkening back to the era of SARS and MERS-COV outbreak several years ago. Similar psychological studies show elevated fear of death among victims and survivors of viral outbreaks, some developing anxiety and posttraumatic symptoms even after recovery. Fear of COVID-19 is negatively correlated to overall perceived QOL, with a correlation coefficient of − 0.27. However, this negative corelationship is rather weak. Another local study with similar design showed that Fear of COVID-19 is only significant among people who were infected with the virus, implying that direct exposure had a greater impact on levels of fear as compared to people who only had relatives, families or friends who were infected. Coping mechanisms on the other hand may prove to be a valuable resource to help victims overcome the adversity of a viral outbreak. A similar local study by Perveen etal. also proved that positive coping mechanisms is related to lower psychological distress. Brief Cope-28 scale gives us some insight regarding coping styles of Malaysians during the COVID-19 pandemic. From the study we find that emotional coping skills scores the highest while avoidant coping scores lowest with mean scores of 30 (6.0) and 15 (4.1) respectively. According to the author of Brief Cope-28, high scores on emotional coping domain indicates a high level of effort to regulate emotional distress during a particular crisis. This is consistent with the scores of Fear of COVID-19 which demonstrates an elevated level of fear throughout during the pandemic. However, avoidant coping scores are low which proves that most Malaysians are still adaptively coping.
Regression analysis revealed that problem based coping mechanism is beneficial to improve overall perceived QOL while avoidance based coping mechanism exerts a negative effect. As written by Carver, avoidance coping mechanism is a detrimental coping mechanism where an individual copes by avoiding the problem rather than tackling it. This is in contrast to a more adaptive problem-based solving. Therefore, it is interesting to note that avoidance coping mechanism scores are positively correlated with elevated levels of fear. The avoidance based coping mechanism has also been shown in effect by a local study which reveals that detrimental coping skills such as alcohol has been associated with greater fear of COVID-19 and heightened psychological distress. While emotional coping mechanism has not been labelled as good or bad[10,22] regression analysis shows that it is associated with increased Fear of COVID-19 and decreased QOL.
With regards to sociodemographic factors, hierarchical linear regression model shows that overall perceived QOL may be positively affected by factors such as gender, age, income levels and education while working from home has a negative correlation. Some studies show that working from the confines of home and being forced to adapt to a new way of work may prove to be stressful for some, hence the perceived reduction in overall quality in life. In addition, some authors noted that familial tension is increased among people who work from home, which may offer some merit to the observed phenomenon. On the other hand, factors that contribute to mature forms of coping mechanisms, such as age, marital status and education may foster resilience and improve QOL. Authors on coping mechanisms such as Gupta and Algorani noted that mature forms of coping skills are usually more systematic and problem based. Such skills are also affected by age and education levels which is a consistent finding in this study.
Although this study has recruited a considerable number of participants we acknowledge that it has several notable weaknesses. First, we are unable to establish cause and effect due to its cross-sectional design. As this study also relies heavily on online survey mechanisms, we may not be able to gather information from the socioeconomically deprived. Movement restriction and social distancing also hampered efforts of research assistants to conduct a throughout face to face survey. In addition, response bias may not be eliminated entirely. Owing to the lack of randomization, it is also difficult to conclude if the respondents sampled were representative of the Malaysian population.
This study focuses on psychological aspects of COVID-19; of how coping skills affects QOL and fear of COVID-19. We find that QOL is greatly affected by a variety of factors, especially type of coping skills and psychological fear of the virus itself. Other socioeconomic factors such as gender, employment status, income, age and levels of education also play an important role. It is therefore imperative to take mental health factors especially pertaining to coping mechanisms and psychological distress into consideration during public health planning. Policy makers may also consider various short-term measures to combat poverty and other long-term plans such as improving education levels in the society as well as amending other sociodemographic factors highlighted in this study in the endeavor to improve QOL and resilience toward COVID-19.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
This study was funded by the National Institute of Health Malaysia.
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