A Perception Based Study on Mental Health Response During COVID-19 Outbreak in Bangladesh
Sharmin Yousuf Rikta1*, Md. Ashik-Ur-Rahman2, Shafi Mohammad Tareq3
1Assistant Professor, Department of Environmental Sciences, Jahangirnagar University, Dhaka-1342, Bangladesh
2Lecturer, Environmental Science Discipline, Khulna University, Khulna-9208, Bangladesh
3Professor, Department of Environmental Sciences, Jahangirnagar University, Dhaka-1342, Bangladesh (Received: 27 February 2021, Revised: 24 May 2021, Accepted: 5 June 2021, Online: 30 June 2021)
Abstract
The recent study was carried out to shape the mental health status of the general population, maintaining social distancing during the COVID-19 pandemic situation. Questionnaire surveys were conducted, revealing that out of the 504 respondents, female respondents had an overall higher mean mental illness level than males. Students reported more mental anxiety than employed respondents or homemakers. Social media acted as a main source to get the news on COVID-19, and a significant effect of media coverage on mental illness was found. The mental illness of the respondents who is not engaged in any physical exercise or household works was found significantly higher than those who responded affirmatively during this social distancing period. The mean of greenery access categories (never, sometimes, and always) inferred that, as the scope of greenery access increases, the mental illness level decreases. A significant difference (p<0.001) was found among various occupational categories regarding future uncertainty due to the COVID-19 outbreak. This work has been designed to visualize the mental health crisis among the people of Bangladesh during the COVID-19 pandemic, which may provoke the thinking of top authorities to focus on mental health and any other required steps before imposing further lockdown during similar crisis management.
Keywords:Depression, Social distancing, Social media, Coronavirus.
Introduction
The recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing COVID-19 disease is a global public health concern. The World Health Organization (WHO) declared the COVID-19 outbreak as a global health emergency and pandemic on 30 January 2020 and 11 March 2020, respectively (Rahman and Bahar, 2020) . Along with the climate crisis, natural habitat destruction and improved transport system, it has crossed all the borders and boundaries putting tremendous pressure on global health service, trades and economy (The Guardian, 2020).
Originating from Hubei Province of China, coronavirus has a death surge throughout 207 countries and territories. Globally, 153,954,491confirmed cases and 3,221,052 deaths were reported by WHO (2021) by 5 May, 2021.
The dead pool is coming down to South Asian countries after Europe and different states of the USA. In South and East Asian region 23,837,189 confirmed cases and 291,762 deaths were reported by WHO (2021) by 5 May 2021. In Bangladesh, the COVID-19 incidence is creeping gradually though the government has taken many preventive measures including social distancing/quarantine/ lockdown to control COVID-19 spread. The first COVID-19 case in
Bangladesh was identified on 8th March 2020 and already 767,338 confirmed cases and 11,755 deaths were reported officially as of 5 May, 2021 (DGHS, 2021) though there were many other deaths having COVID-19 symptoms. To tackle the situation, the government had declared general holidays from 26 March 2020 to 31 May 2020 to maintain social distancing, though many areas/families were lockdown since before for the presence of COVID-19 patients/ symptoms. Like other countries, this lockdown/ social distancing had created huge pressure on society and economy.
After a few months of low wave the Covid-19 wave has started to rise again in March 2021 with greater intensity and deaths. The Government has declared further lockdown from 5 April 2021 to 16 May 2021.
Along with physical health, the COVID-19 pandemic situation can affect the mental health of an individual. The population maintaining social distancing are going through continuous fear, anxiety and depression. Stress level is increasing day by day throughout the country. This condition might have adverse impacts on quality of life as cognitive deficits which are poorly controlled are prominent and severely affect the quality of life (Millan et al., 2012). Cullen et al. (2020) has anticipated a significant upsurge of depressive symptoms and anxiety among people who did not experience those mental health conditions earlier, with some experiencing post-traumatic stress disorder in due course. A study conducted among1210 respondents of 194 cities in China by Wang et al. (2020) found moderate or severe psychological impact of the Covid-19 outbreak in 54% of respondents; moderate to severe anxiety symptoms in 29%; moderate to severe depressive symptoms in 17% respondents. Significant level of psychological burden was also observed in Jordanians, especially among females (Khatatbeh et al., 2021). Yeasmin et al. (2020) conducted a study on the impact of Covid-19 pandemic on the mental health of children in Bangladesh. The study found that 43% of children encountered subthreshold mental disturbances, 30.5% had mild, 19.3% suffered moderately and 7.2% of children suffered from severe disturbances. Another study conducted among the home-quarantined Bangladeshi students (college and university level) revealed that 46.92%, 33.3% and 28.5% respondents suffered from mid to extremely severe levels of depression, anxiety and stress respectively (Khan et al., 2020). New research and technologies are constantly finding ways to handle the pandemic situation; like preventive measures from coronavirus infection, discovery of vaccines etc. At a time, it is also important to know and concentrate on public mental health in this situation because it can have a prolonged effect even when we will overcome this pandemic. Hence, this research work is designed to investigate how the social distancing/ quarantine/ lockdown can affect the mental health of the general population.
Methodology
Data Collection
A questionnaire survey was designed using Google Form and sent to the respondents randomly in Dhaka city of Bangladesh. The survey was conducted from March, 2020 to April, 2020. Total 526 responses were received, among which 484 respondents were young adults (18-35 years old), 17 were middle aged adults (36-50), and 03 were older adults (aged older than 50 years). Most of the respondents were educated urbanites as they have used Google Forms for their feedback and the focused study area was Dhaka city. From the dataset, data of 22 respondents were deleted as outliers for statistical analysis.
Questionnaire development and data processing
The questionnaire was developed to identify the mental health status of people maintaining social distancing/ quarantine in COVID-19 outbreak situations. For conducting this study, mental illness/discomfort was identified by six symptoms. For statistical analysis scores for the symptoms were given as, anxiety=5, depression=4, insomnia=3, hypertension=2, fatigue and tiredness=1 and none of the above=0. Based on these scores, respondents with lowest mental illness recorded as 0 and highest mental illness recorded as 15. So the mental illness score range is 0-15. This scoring reflects the present mental illness situation amidst the COVID-19 pandemic declared by WHO.
Five factors; influence of social media, physical inactivity/lack of physical exercise, attachment with greenery, attachment with family and friends, and future uncertainty were considered which can affect the mental health/ illness of people during quarantine/ social distancing period.
Three questions were considered to identify the social media influence; do you use electronic/ social media to know COVID-19 update, which media do you mostly use to get COVID-19 update and do you think media news increases your mental anxiety regarding COVID-19. To identify the influence of physical inactivity/lack of physical exercise following questions were considered; do you perform physical exercise regularly/frequently during this social distancing period, how long you have been staying idle at home (hour per day) and how long you have been taking physical exercise (or doing household works) at home (hour per day). To identify the influence of green attachment on mental health, do you have access to visit greenery (garden/rooftop garden/park etc.) during this social distancing period, and when did you last visit greenery (in days) were taken as the questions.
Family and friends attachment was another factor whose influence was measured through four specific questions; how long you have been maintaining social distancing, how many family members do you have, how many calls do you attend per day (in average) from friends/family members, do you think the presence of your friends/ family members could reduce your mental anxiety. Mental health status was tried to identify through correlating with future uncertainty (do you think COVID-19 can affect you socially and economically, are you worried about your future like; job security, education etc. due to COVID-19 outbreak) of the respondents. Additionally, people’s perception on mental health education or counselling were also included in this study .
Statistical analysis
Descriptive statistics with mean and Standard Deviation (SD) were carried out on continuous variables, and percentages were utilized for dichotomous variables. Multiple Response Dichotomy Analysis was utilized for multiple response items and correlations (Pearson product-moment correlation coefficient, r) for relationships or dependency. To compare means among different categories of response, a one-way ANOVA or F-test (Analysis of variance) was used. Besides, Mann-Whitney U non-parametric test was applied to reveal the significant difference among the demographic characteristics of the respondents.
Research Ethics
Information/data for this research were collected following the basic principles of the Declaration of Helsinki guideline. Participants documented only their perception of mental states, not any formal medical data. Informed consents were obtained from all participants.
Results and discussion
Demographic characteristics of respondents
The demographic characteristics of respondents are shown in Table 1. Out of the 504 respondents, 285 (56.5%) were males. Female respondents had an overall higher mean mental illness level than males (Mean ± SD were 5.38 ± 4.451 and 4.79 ± 4.194 respectively), and the difference found was non-significant in a Mann-Whitney U non-parametric test (U = 29071.5, P = 0.184). Student respondents (62%) reported more mental illness than employed respondents or homemakers.
However, the difference was non-significant between the groups.
Table 1: Demographic characteristics and mental illness of respondents
Characteristics Number of respondents = 504 Mental Illness ± SD
Male: N (%) 285 (56.5%) 4.79 ± 4.194
Female: N (%) 219 (43.5%) 5.38 ± 4.451
Student: N (%) 313 (62.1%) 5.23 ± 4.203
Employed: N (%) 159 (31.5%) 4.96 ± 4.625
Unemployed: N (%) 13 (1.8%) 4.38 ± 3.453
Homemaker: N (%) 9 (1.8%) 2.00 ± 1.732
Others: N (%) 10 (2%) 4.20 ± 4.638
Table 2 shows the descriptive statistics of the variables associated with mental illness during social distancing period. The mean days of last visiting greeneries and social distancing periods are almost similar (12.48 and 11.34 respectively). Respondents receive about four calls (4.57 ± 4.901) per day during the social distancing period.
Table 2: Descriptive statistics of surveyed variables among respondents (N= 504)
Minimum Maximum Mean ± Std.
Deviation
Mental illness score 0 15 5.05 ± 4.314
Duration of social distancing (days) 0 25 11.34 ± 4.246
Number of calls per day from family members (no.) 0 50 4.57 ± 4.901
Number of family members (no.) 1 20 4.69 ± 1.923
Last visit in greenery (days) 0 90 12.48 ± 12.875
Passing idle hours during a day (hours) 0 24 12.20 ± 7.344
Taking exercise/doing household works at home (hours) 0 14 1.997 ± 2.1553
Mental illness levels of respondents and associated factors
Social media influence
The influence of social media was considered as one of the vital factors of mental illness during the social distancing period. COVID-19 updates covered by social media and conversation as well as sharing the negative news can aggravate mental anxiety among isolated people. Several studies were done (Liu and Kim, 2011; Dobrean and Costina, 2016) on the social media influence in pandemic situations. This study shows that around 95% respondents use electronic/social media to know the updates of coronavirus (Figure 1a) and about 61% respondents mostly use social media like Facebook, Twitter, Instagram etc. for that purpose (Figure 1b).
Figure 1: Electronic/social media usage (a) and their types (b) to know COVID-19 Update.
A one-way ANOVA is conducted to compare the effect of media news observation on the mental illness during the social distancing situation of the COVID-19 pandemic. An analysis of variance shows that the effect of media news observation on mental illness was significant, F (2, 501) = 5.091. p = .006 (Table 3).
Table 3: One-way ANOVA result for the difference in mental illness by media news Variable Media News Observation Affects
Never (Mean)
Sometimes (Mean)
Always (Mean)
ANOVA (F)
Sig.
(2-tailed)
Mental Illness 3.52 5.05 5.47 5.091* .006
*Significant at the 0.05 level (2-tailed).
There was also a significant effect of COVID-19 media coverage on mental illness at the p < .05 level for the three media types, such as: television, newspaper, and social media (Facebook, Twitter, Instagram etc.) [F (2,501) = 5.091, p = .009] (Table 4). A study conducted by Dobrean and Costina (2016) revealed mixed results of the relationship between social media use and anxiety though most of the studies showed a positive relationship. Conversations are made on social media which is both offering a chance to our collective response to the coronavirus outbreak, as well as shaping our mental illness in the first place. Besides, the lockdown situation ignites the younger group to use social media excessively than before.
Table 4: One-way ANOVA result for difference in mental illness by different media types
Variable Media Types
Television (Mean)
Newspaper (Mean)
Social Media (Mean)
ANOVA (F)
Sig.
(2-tailed)
Mental Illness 4.22 5.13 5.49 4.729* .009
*Significant at the 0.05 level (2-tailed).
Influence of Physical inactivity
The Centers for Disease Control and Prevention and the American College of Sports Medicine recommended moderate-intensity physical activity for a minimum of 30 minutes on five days each week for healthy adults aged 18 to 65 years (Haskell et al., 2007). This is necessary to maintain and promote good health. Studies (Taylor et al., 1985; Craft and Perna, 2004; Moraes et al., 2007;
Deslandes et al., 2009) suggested that physical activity and exercise have a great influence on human mental health and can reduce mild to moderate depression and anxiety. Thus, physical inactivity/lack of exercise was considered as another factor to correlate with mental health status of people maintaining social distancing.
Results show that the respondents who always do exercise or household work experience less mental illness during social distancing periods (M= 4.10) than the respondents who never engage in any physical exercise (M= 5.71). Table 5 shows that the difference was statistically significant, F (2,501) = 5.505, p = .004. A Pearson product-moment correlation coefficient was computed to assess the relationship between the hour spent for physical exercise (or doing household works) at home per day and mental illness of the respondents. Results of the recent study support the previous study conducted by Frazer et al (2005). Table 9 shows a negative correlation between exercise hours and mental illness of the respondents. Though the correlation is weak (r = .199), it is highly significant (p< .01).
Table 5: One-way ANOVA result for difference in mental illness by performing physical exercise during social distancing
Variable Physical Exercise
Never (Mean)
Sometimes (Mean)
Always (Mean)
ANOVA (F)
Sig.
(2-tailed)
Mental Illness 5.71 4.79 4.10 5.505* .004
*Significant at the 0.05 level (2-tailed).
Influence of green attachment
Many researchers (Kaplan and Kaplan, 1989; Kaplan, 1995; Hartig et al., 2011; Bell and Thompson, 2014) suggested that natural environment can restore from fatigue, effectively reduce stress and improve mental health. Pretty et al (2007) implied, green space and nature can enhance mental health and affect psychological well-being positively. Thus, attachment to the green environment (garden/rooftop garden/park etc.) was selected as another factor to assess the mental health condition of people during quarantine period. The result in table 6 indicates a statistically significant difference between mental anxiety score and access to visit greenery during social distancing period (p = .005). The mean of greenery access categories infers that, as the scope of greenery access increases, the mental anxiety level decreases.
Due to lockdown, most of the people cannot visit greeneries frequently, except those who have rooftop gardens or gardens adjacent to living places. Last visit to greeneries (in days) is found to be very weakl (r = .102) and positively correlated with the mental illness status of respondents with a high significant level (p = 0.05). This result supports the previous study conducted by Pretty et al (2007). Duration of social distancing and last greenery visits is also found positively correlated, r (504) = .143, p < .01 (Table 9).
Table 6: One-way ANOVA result for difference in mental illness by greenery access
Variable Greenery Access
Never (Mean)
Sometimes (Mean)
Always (Mean)
ANOVA (F)
Sig.
(2-tailed)
Mental Illness 5.60 4.56 4.34 5.309* .005
*Significant at the 0.05 level (2-tailed).
Family and friends’ influence
“When people are asked to indicate who they turn to in times of crisis and emotional distress, they typically cite key family members and friends who they consider natural helpers” (Barrera et al., 1981). The absence of family members and friends was taken as another influencing factor of mental health status. The recent study shows that there is a significant effect of family and friends’
presence on mental illness condition (F2,501 = 5.911, p = .003) (Table 7). When people go through social or mental crises, they seek assistance from family members, friends, neighbors and this group of networks have a significant impact on psychological reformation (Barrera et al., 1981). On the other hand, there is no correlation between mental illness and the phone calls attended by the respondents from friends and families (Table 9). Most of the respondents are already residing with family members at home and during phone conversation with friends and family they could have mostly discussed the pandemic situation of COVID-19 during lockdown period. These could be the reasons behind no correlation between mental illness and the phone calls attended by the respondents from friends and families.
Table 7: One-way ANOVA result for difference in mental illness by the presence of friends and family
Variable Presence of Friends and family Never
(Mean)
Sometimes (Mean)
Always (Mean)
ANOVA (F)
Sig.
(2-tailed)
Mental Illness 5.28 3.72 3.03 5.911* .003
*Significant at the 0.05 level (2-tailed).
Future uncertainty
Feeling uncertainty during any disaster or pandemic situation is a central feature of human behavior.
During social distancing, students or employed person remain worried about their studies or job.
This further affects the socio-economic condition. Session jam in Universities or delay in salary bring anxiety among the lockdown people. Results show that, among 285 male respondents more than 63% is worried about future uncertainty due to the COVID-19 outbreak, whereas more than 67% female respondents (out of 219 respondents) are worried. Percentage of male respondents who are sometimes worried about future uncertainty is slightly higher than female respondents in the same category, and respondents who are not worried of future uncertainty are almost the same in both categories (Figure 2).
Figure 2: Response of respondents to future uncertainty based on gender.
While comparing the means of worriedness categories among the respondents, it is found that, the group with extremely worriedness of socioeconomic effects have higher mental anxiety (M=6.06) than those who are not worried at all (M=2.92). Difference among these categories are found statistically significant F (2,501) = 10.785, p <.001 (Table 8).
Table 8: One-way ANOVA result for difference in mental anxiety by the worriedness of socio- economic effects
Variable Worriedness of Socio-economic Effects Extremely
Worried (Mean)
Worried (Mean)
Somehow Worried
(Mean)
Not Worried
(Mean)
ANOVA (F)
Sig.
(2-tailed)
Mental Illness
6.06 4.56 3.07 2.92 10.785* .000
*Significant at the 0.001 level (2-tailed).
Table 9: Correlation between mental illness and taking exercise or doing household works at home Score of
illness
Last visit in greenery
Passing idle hours per day
Taking exercise/
HH works
Duration of social distancing
Number of calls from family members per day
Family member Numbers Score of illness
Last visit in greenery
.102* Passing idle
hours per day
.149** .078 Taking
exercise/HH works
-.119** -.074 -.111*
Duration of social distancing
.124** .143** -.057 .033
Number of calls from family members per day
.062 .023 .053 .039 -.091*
Family member Numbers
-.010 .022 -.038 .017 -.049 -.007
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
N=504
Online mental health education/counseling service recommendation
People all over the world are worried about the pandemic outbreak of Coronavirus. People of Bangladesh are worried about COVID-19 because of various influencing factors including death, uncertain future, health care system and financial security. A study was conducted to identify the fear of general respondents to COVID-19 and most of the respondents were extremely worried and worried (44.43% and 39.68%, respectively) (Figure 3). This result implies a possibility of great mental anxiety/illness among the general population.
Figure 3: Public response to fear of COVID-19 outbreak.
The survey was conducted to identify the way to overcome/cope with that fright in this quarantine situation. In isolation/social distancing periods people are mostly unable to access mental health care as it is one of the neglected health care issues of the country and the service is not widely accessible. Even in developed countries, between 44% and 70% of patients can access treatment for mental illness whereas in developing countries the scenario is more devastating, treatment/service gap is close to 90% (WHO, 2003).
Counseling is a widely accepted way to deal with mental illness (Broglia el al., 2018; Greidanus et al., 2019). Hence, the survey question was designed to evaluate the public acceptance of online mental health education/counseling service. More than 27% and 34% respondents highly recommended and recommended online service (Figure 4). Although 28.57% respondents said that service may be required and 9.72% responded as not necessary which further imply the lack of awareness about mental health care among the general population.
Figure 4: Public response to the necessity of online mental health education/counseling service.
Conclusion
The study reveals that the absence of friends and family members, physical inactivity, unavailability of visiting natural space/greenery and social media have played vital roles in triggering mental illness among the people during the lockdown period. This study finds out more than 50% of respondents (both male and female) are anxious due to the future uncertainties regarding their job security and education. Overall, this work reflects how the lockdown/ quarantine period arises the mental health crisis among general people. To tackle the situation and for better management, along with other health services, mental health awareness and treatment services are highly recommended to avoid chronic mental illness even after this pandemic situation. Otherwise, a hidden health crisis will persist, which will cost a lot in the near future.
Acknowledgement
This research study was funded by the Jahangirnagar University, Dhaka, Bangladesh. Authors declare no competing interest.
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