Trust in Government, Awareness and Attitude, and Influence of Social Media in the Context of Risk Perception During the COVID-19 Pandemic in Bangladesh

Trust in Government, Awareness and Attitude, and Influence of Social Media in the Context of Risk Perception During the COVID-19 Pandemic in Bangladesh

Md. Khaled Saifullah *¹, Md. Yousuf Harun ², Emadul Islam ³

¹Department of Economics, School of Business and Entrepreneurship, Independent University, Bangladesh; Dhaka, Bangladesh

²Department of Finance and Banking, Jahangirnagar University; Dhaka, Bangladesh

³Ocean Policy Research Institute (OPRI), The Sasakawa Peace Foundation, Tokyo, Japan

³College of Social Sciences and Humanities, Northeastern University; Boston, USA

DOI: https://doi.org/10.47772/IJRISS.2023.70595

Received: 09 May 2023; Accepted: 19 May 2023; Published: 15 June 2023

ABSTRACT

The novel coronavirus (COVID-19) remains a global public health emergency as declared by the World Health Organization (WHO), and its spread is associated with the adaptation to public health behaviors and risk perception. This study assesses the trust in government, awareness and attitude, and the influence of social media in the context of risk perception during the COVID-19 pandemic in Bangladesh. To fulfill the objective of the study, data were obtained from 447 respondents living in Bangladesh and the Structural Equation Modeling (SEM) was adopted as a quantitative technique to verify the objectives. The study revealed that awareness and attitude, and the influence of social media have significant effects on people’s risk perception of COVID-19, while people’s trust in the government has a significantly negative effect. The study suggests that authorities in Bangladesh should strive to acquire the citizen’s trust, as COVID-19–related health guidelines and disseminated information are essential and capable of minimizing the spread of the virus. Authorities should also effectively utilize social media for the dissemination of COVID-19 related information.

Keywords: COVID-19, Risk perception, Trust in government, Awareness and attitude, Social media

INTRODUCTION

The devastating novel COVID-19 pandemic of the 21^st century has sent a clear message to world leaders, researchers, and policymakers on the persistent failure of existing technology to tackle natural calamities (Islam, 2020). The first case of the virus was recorded on December 8, 2019, in the Wuhan province of China. The virus eventually spread all over the world, and as of June 30, 2021, a total of 182,201,911 confirmed cases including 3,947,011 deaths and 167,547,026 recovery cases have been recorded worldwide (WHO, 2021). Even with a mere mortality rate of 2.17 percent, the virus has turned out to be a conundrum for doctors, researchers, and scientists all over the world. On August 11, 2020, Russia became the first country to approve a vaccine named Sputnik V, which it believed was going to be effective in the cure of the virus. However, minimal human tests were conducted, and as a result, its use remained controversial among world leaders, doctors, and scientists (Al Jazeera, 2020). After Russia, other countries such as the USA, UK, and China have also launched and administered their own COVID-19 vaccines, bringing the total administered dosage worldwide to 2,950,104,812 doses as of June 30, 2021 (WHO, 2021).

The United Nations (UN) and World Bank forecast a shrink in the world economy due to COVID-19 by over 5% in the year 2020 and a huge social and economic loss, should the pandemic linger (UN, 2020; World Bank, 2020).

In Bangladesh, the first case of COVID-19 occurred on March 8, 2020, and as of June 30, 2021, a total of 913,123 confirmed cases and 14,508 deaths have been recorded (WHO, 2021). The COVID-19 outbreak emphasized the importance of the government’s attention to public health and social protection. However, public health issues in developing countries were observed to be worse than in the developed regions. According to the UN ESCAP (2020) report, around 1.6 billion people lack access to basic sanitation, 260 million are without clean and potable water in the home, 40 percent of the global population have no access to healthcare, and more than 60 percent lack access to social protection. Being a densely populated country, Bangladesh has only eight hospital beds for every 10,000 patients and 0.5 doctors per 1,000 patients. To make matters worse, 87 percent of its workers are employed in the informal sector and are directly affected by the COVID-19 lockdown.

Social distancing has been identified as a key preventive measure against the pandemic, while the lockdown of suspected areas and shutdown of economic activities are being implemented worldwide to further limit the spread of the virus. Research relating to crisis management and the present COVID-19 pandemic identifies risk perception as being crucial to sustainable responses against hazards. The spread of diseases like the COVID-19 is influenced by people’s willingness to adopt preventative public health behaviors, which are often associated with public risk perception (Dryhurst et al., 2020). The level of awareness and people’s understanding of the risk at the community level goes a long way in enhancing its prevention (Chatterjee et al., 2020). However, the death toll of COVID-19 is on the rise worldwide, necessitating the increased attention towards an understanding of public risk perception (Van Bavel et al., 2020). Chatterjee et al. (2020), Dryhurst et al. (2020) and Van Bavel et al. (2020) argued that precise public risk perceptions are crucial to the management of public health risks like the COVID-19.

Dryhurst et al. (2020) also argued that risk perception and communication are largely influenced by cognitive, emotional, social, cultural, and individual variations where social media provides opportunities for experts to rapidly convey accurate information about hazards (Hassan et al., 2021). Luu and Huynh (2020) found the positive impact of social media on the risk perception of the COVID-19 pandemic in Vietnam. Hassan et al. (2021) also identified the influence of risk perception and the awareness gained from using social media during the pandemic on people’s trust in the government in the context of Malaysia. Many international agencies and governments are also adopting and using social media as the main channel for the dissemination of public information during the COVID-19 pandemic (Mejia et al., 2020). Previous studies indicated that social media played a vital role in the propagation of information during the outbreak. Hence, the objective of this study is to assess the trust in government, awareness and attitude, and the influence of social media (mainly Facebook) in the context of risk perception during the COVID-19 pandemic in Bangladesh.

LITERATURE REVIEW

This study considers three broad concepts: risk perception, social media, and the citizens’ trust in the government. The concept of risk perception has been widely explored in earlier studies compared to the other two concepts. Darker (2013) defined risk perception as the subjective judgment of people towards potential risks. Paek and Hove (2017) also described risk perception as a subjective judgment under two broad dimensions: cognitive, which relates to the level of people’s awareness towards risks; and emotional, which relates to how they feel about them. From the 20^th century, pandemics like the severe acute respiratory syndrome (SARS), swine flu, Ebola, and Spanish flu that were successfully controlled via the enactment of policies have been observed to greatly rely on the public’s accuracy of risk perceptions (Dryhurst et al., 2020). Therefore, risk perceptions are important determinants of health and risk-related decisions (Paek & Hove, 2017).

The most cited risk perception theory—the protection motivation theory (PMT)—possess key features as highlighted: “people are more likely to protect themselves when they anticipate negative consequences, have the desire to avoid them and feel they have the ability to take preventive measures” (Inouye, 2014, pp. 5). Overall, the PMT postulates the existence of a relationship between risk perception and protective actions and highlights that people tend to indulge in protective actions when they are motivated and have the agency to do so (Inouye, 2014). To corroborate this, Sheeran, Harris and Epton (2014) discovered that enhancing the elements of risk perception has a combined positive effect on the changing intentions of people and their behavior towards safety. The WHO declared core preventive measures to tackle the COVID-19 pandemic by enforcing social distancing and personal hygiene practices. In this regard, risk communication and perceptions are critical to the creation of awareness that ensures the participation of people in suggested preventive and protective measures geared at effectively managing these public health risks (Chatterjee et al., 2020). However, in the context of the COVID-19 pandemic, risk perception influenced people’s adoption of preventive measures, which may result in the trivialization and politicization of established interventions. As an instance, despite the clear evidence of reduction in COVID-19 transmission through wearing masks, its adoption in the US was low as it was politicized (Malecki, Keating & Safdar, 2020).

The second concept in the study is social media, which comprises of Web 2.0 internet-based set of applications, including online social network platforms such as Facebook, Twitter, Instagram, Pinterest, and others. Several studies have highlighted the important role of social media, particularly Facebook and Twitter, in the communication of COVID-19 risks (Chatterjee et al., 2020; Malecki et al., 2020), risk perception (Hassan et al., 2021; Luu & Huynh, 2020; Karasneh et al., 2020), crisis information dissemination (Xie et al., 2020), student-teacher connection during periods of crisis (Greenhow & Chapman, 2020), and crisis intervention and management (Cheng et al., 2020). However, the authenticity of the disseminated information in risk communication and perception is being questioned, owing to the lack of credibility of the sources and websites through which information are obtained, thereby resulting in the propagation of false information and difficulties in distinguishing rumors from the reality (Karasneh et al., 2020). Despite authenticity issues, social media was observed to have a positive impact on the risk perception of the COVID-19 pandemic in Vietnam (Luu & Huynh, 2020).

Vai et al. (2020) conducted a study on 2,223 participants in Italy and discovered the COVID-19 threat perception to be dependent on efficacy belief. Participants declared that the WHO’s website is more trusted, whilst social media, although frequently used, is unreliable. Rahmanti et al. (2021) studied public perception employing sentiment analysis and identified predominant tweets using emotion analysis. In response to the COVID-19 pandemic, the Government of Indonesia utilized Twitter for speedy decision-making and policy evaluation during uncertain times. In addition, social media platforms tend to be more convenient compared to conventional media, as a large mass of people can obtain health crisis-related information at any time from any location (Lin et al., 2016).

OECD (2013, pp. 21) defined trust as “holding a positive perception about the actions of an individual or an organization”. Easton (1965) proceeded to define trust in government as citizens’ reliance on the acts of a ‘government to do what is right and fair’.  Likewise, Bouckaert and Van de Walle (2003) described trust as the uniformity between citizens’ perceptions and elucidation of the right, fair and unfair, and the actual functioning of a government. Research shows that in any crisis or pandemic, citizen participation in state policies depends on their level of trust in the government. Amid the COVID-19 pandemic, the WHO prescribed several protective and preventive measures such as the enforcement of lockdown, social distancing, the wearing of face masks, and the promotion of personal hygiene. Nonetheless, in many cases, citizen participation in state policies was minimal. This holds for developed countries like the USA where the government delayed the declaration of a clear direction, thereby confusing the citizens about risk perception. It is also evident that citizens’ perception of government-issued information about the COVID-19 was mostly criticized due to the falsified figures of actual suspected cases. Hassan et al. (2021) and Sibley et al. (2020) observed that citizens’ trust in the government had a significant effect on risk perception during the COVID-19 pandemic. Barrafrem, Tinghög and Västfjäll (2021) revealed that the trust in the government’s ability to deal with financial issues posed by the COVID-19 pandemic had a considerable impact on the overall well-being via financial security. Furthermore, citizens’ confidence in the government’s ability to deal with the healthcare issues posed by the COVID-19 pandemic had a significant impact on their overall well-being (Barrafrem, Tinghög & Västfjäll, 2021).

Franke and Elliott (2021) conducted a study among US citizens which revealed that relational characteristics such as alienation and trust influence people’s level of optimism or pessimism of surviving a public health crisis. Additionally, Diotaiuti et al. (2021) observed that risk perception, individual self-efficacy perception, social responsibility value, interpersonal trust and trust in health authorities have all changed significantly overtime during the COVID-19 crisis. Furthermore, Seale et al. (2020) highlighted the importance of understanding how people assert their risk perceptions during the pandemic in light of dominant factors, such as trust in government direction, awareness and attitudes, and social media.

The situation of the COVID-19 pandemic in Bangladesh

Almost one year and eight months after the first case of the novel coronavirus, the world is still struggling. Bangladesh is one of the most densely populated countries and as such, has become one of the countries most affected by the COVID-19 pandemic. According to Rahman et al. (2021), three in every five of the nation’s residents are exposed to health and economic disposition threats. The daily data from March 8, 2020, to August 31, 2020, depicts this in a line graph.

Figure 1. COVID-19 daily trends in Bangladesh. Source: WHO (2021)

Figure 1 shows that the number of tests increased over time but significantly dropped at the end of August, and as the number of cases rose, Bangladesh started to fall short of testing supplies (Anwar, Nasrullah & Hosen, 2020). In a country with a population of about 166.5 million people (UNSD, 2020), only 6.64 million tests were conducted, and 10.17 million vaccine doses were administered as of June 30, 2021 (DGHS, 2021). Initially, there were only a few confirmed cases, but the situation gradually worsened. Consequently, Bangladesh responded by reducing the number of international flights, imposing thermal screening, and shutting down educational institutions. The delay and poor timing in enforcing these measures are the major reasons for the sudden surge in the number of cases. Moreover, the Government declared a general holiday from the 26^th of March to the 30^th of May 2020 without imposing any effective travel restrictions, and this encouraged many citizens to travel to rural areas rather than staying back in urban areas. As a consequence, there was an upsurge in the number of confirmed cases of the COVID-19. Ever since the lockdown commenced on the 26^th of March 2020, Bangladesh had witnessed a drastic increase in the total COVID-19 cases, starting from just 39 and increasing to a staggering 529,687 cases, of which 7,950 deaths (1.50% mortality rate) were recorded. The mortality rate looks negligible, but with prudent planning and foresight, the situation could have been more favorable (Anwar, Nasrullah & Hosen, 2020). Figure 1 also shows an upward trend in recovered cases from the 15^th of June 2020, as the Government resorted to documenting patients who recovered while staying at home. Bangladesh currently faces a third wave of the virus from mid-May due to a new Indian variant mostly originating from the border districts. However, as of 30^th of June 2021, 89.39 percent of the infected cases have recovered.

The literature highlights risk communication and perception, which are being questioned owing to the several sources of information (Karasneh et al., 2020). During public health crises, credible and timely information is critical to creating awareness, as this ensures the participation of the public in preventive and protective measures (Chatterjee et al., 2020). Additionally, Seale et al. (2020) highlighted the importance of asserting public risk perception, especially in relation to trust in government direction, awareness and attitudes, and social media during the COVID-19 pandemic.

RESEARCH METHOD

Sample size and questionnaire design

A quantitative online survey methodology employing a self-administered questionnaire was adopted by using Google Forms to obtain data pertaining to the underlying constructs proposed in the theoretical model. These constructs were operationalized by multi-item measures employing a 6-points Likert scale. The online survey commenced on the 28^th of July 2020 and ended on the 13^th of August 2020. A total of 447 respondents from all administrative divisions in Bangladesh participated in the online survey. The questionnaire was divided into five sections. The first section dealt with the demographic or background information of respondents and families, while the remaining four were regarding risk perception (RP), trust in government (TG), influence of social media (SM), and awareness and attitude (AA).

Data analysis technique

This study adopted the confirmatory factor analysis (CFA) to assess the robustness of the latent variables and the structural equation modeling (SEM) to analyze the influence of social media in the context of risk perception on trust in government, and awareness and attitude during the COVID-19 pandemic. Craighead et al. (2011) argued that the CFA is a robust assessment that contrasts between the one-factor models compared to the multifactorial models, which can be assessed through the Cronbach’s alpha value. Moreover, according to Hair et al. (2010), the CFA is used to assess the measurement model for all latent variables and explain how the measured latent variables logically and systematically represent constructs in the model. The factor loading of the CFA should have a minimum value of 0.50 and an ideal value of 0.70 or higher. Hence, any item with a low CFA loading is to be dropped.

The SEM is a multivariate technique that acts as a combinational aspect of multi-regressions and can simultaneously appraise a progression between related reliance connections (Hair et al., 2010; Byrne, 2013). This technique can harmonize both unobserved and observed variables in measurement and structural models. In structural modeling, the SEM gives the capacity to gauge the auxiliary connections between the arrangements of unobserved variables while clarifying the measure of sudden fluctuations (Byrne, 2013). The advantage of the SEM lies in its seamless application to different shapes of data, and as an example, it is appropriate for non-normality data sets (Hair et al., 2012; Ringle et al., 2009). Moreover, according to Chin and Newsted (1999), the SEM is able to attain robust results. Other advantages of the SEM include its applicability to formative modes and its easy identification of the key driving constructs (Hair et al., 2012; Ringle et al., 2009). An SEM model has two parts: measurement and structural. The measurement part demonstrates the relationship between the latent variables and their indicators, while the structural part reveals the relationship between the latent variables Vinzi et al. (2010).

The sample size adequacy remains a prime concern in the application of the SEM. According to Hoe (2008), a sample size of 200 offers sufficient statistical strength for data analysis. Also, Hair et al. (2010) highlighted the vital role of sample sizes in the formation of steady and significant approximations and explanations of outcomes. While no precise guidelines regarding sample size are required, this postulation suggests that models having a larger number of parameters necessitate a greater sample size (Kline, 2010). Therefore, a sample size of about 447 is considered adequate. In line with the recommended guidelines, the target sample size of 447 was adopted in this study.

Conceptual framework and hypothesis

To have a clear understanding and develop a clear representation of this study’s objective, i.e., to define the relationship between trust in government (TG), awareness and attitude (AA), influence of social media (SM) and risk perception (RP), the following model and hypotheses were taken into account (Figure 2).

Figure 2 Proposed research model

H1: TG has a positive relationship with SM.

H2: AA has a positive relationship with SM.

H3: TG has a negative relationship with RP.

H4: AA has a positive relationship with RP.

H5: SM has a positive relationship with RP, and if H1 and H2 are significant, then SM is significant as a mediator factor.

Figure 2 shows that the study uses TG and AA to examine the direct effect of these two factors on SM and RP. Moreover, this study used SM (mainly Facebook) as a mediator factor having a direct and positive relationship with RP, and that TG and AA may have an indirect positive relationship with RP.

RESULTS AND DISCUSSION

A total of 447 respondents participated in the online survey. Table 1 shows the socio-demographic profiles of the respondents. The sample in the study comprised 54.1 and 45.9 percent male and female respondents, respectively. A larger fraction of the respondents (68.7 percent) were aged between 17 to 25 years, followed by the 26–35 age range (25.7 percent). Table 1 also depicts that 78.7 percent of the respondents are from urban areas, 54.1 percent have undergraduate, 40.7 percent have masters, 2.7 percent have high school certificates (HSC) and 2.5 percent have doctorate academic qualifications.

Table 1 Socio-demographic characteristics of the respondents

Table 1 also shows that a majority (68 percent) of the respondents are students; 15 percent, private jobholders; and 4.9 percent, job seekers. Moreover, 85.5 percent of the respondents were non-smokers. Figure 3 highlights that 40 percent of the respondents’ households earned a monthly income between BDT 20,001 and BDT 60,000; 15 percent, less than BDT 20,001; and 6 percent, above BDT 200,000.

Figure 3 Monthly household income (BDT) group of the respondents

Figure 4 shows that participants from all eight administrative divisions of Bangladesh took part in the online survey. The majority of the respondents (337) lived in the capital city of Dhaka, followed by Chittagong (27), Rajshahi (22), Khulna (20), Mymensingh (15), Barishal (10), Rangpur (9) and Sylhet (7).

Figure 4 Geographical distribution of the respondents

Confirmatory factor analysis (CFA)

The CFA shows that all the factor loadings range between 0.522 and 0.846. It also indicates that all item loadings exceed the threshold value of 0.50 as shown in Table 2. According to Hair et al. (2010), the factor loading of the CFA should have a minimum value of 0.50, an ideal value of 0.70 or higher, and that any item with low CFA loading should be dropped. Reliability analysis was also conducted for all variables to determine the adequacy of the internal consistency of the variables. Table 2 also presents the values of the Cronbach’s alpha (reliability analysis) as 0.478, 0.899, 0.826 and 0.746 for RP, TG, SM and AA, respectively. A Cronbach’s alpha value of 0.50 or higher indicates the reliability of the item scales (Dall’Oglio et al., 2010). However, according to Taber (2018), a Cronbach’s alpha value of 0.45 or higher is acceptable.

Table 2 Construct validity of confirmatory factor analysis

Test for structural equation modeling (SEM)

The SEM is used to assess the association among the constructs of a hypothesized model (Kline, 2010). In this study, a structural model was tested to examine the relationship between trust in government (TG), awareness and attitude (AA), influence of social media (SM) and risk perception (RP) (Figure 5). As indicated by the overall goodness-of-fit indices, the SEM (Figure 5) confirms a very good fit of the measurement model. The value of the Chi-square is 2.580, which lies below the threshold value of 3.00; the values of the CFI and GFI are 0.923 and 0.903, respectively, exceeding the threshold value of 0.900; the RMSE value is 0.060, which is less than the threshold value of 0.080 (Byrne, 2013; Hair et al., 2010; Kline, 2010).

Figure 5 The structural equation modeling of risk perception (RP)

Figure 5 shows that in the SEM, the RP has 2 items. Table 2 on the other hand shows otherwise, with the RP having 6 items. The items RP2, RP3, RP4 and RP6 were not included in the SEM, as they had factor loadings lower than 0.40. This is in accordance with the study conducted by Wülferth (2013) and Avkiran and Ringle (2018) where it was stated that the factor loading of SEM items should exceed 0.40, less of which should be deleted from the model. Figure 5 presents the factor loadings of TG, AA, SM and RP as lying between 0.45 and 0.87.

Table 3 Hypothesis and path coefficients

  *** Significant at less than 1% level; ** Significant at 5% level

The SEM results (Table 3) show that trust in government (TG), and awareness and attitude (AA) have positive relationships with the influence of social media (SM). However, these relationships are not statistically significant at the 5 percent level; hence, H1 and H2 are not supported. Also, TG and AA do not have any effect on SM. However, Hassan et al. (2021) observed that social media have an influence on trust in government and self-awareness during the COVID-19 pandemic. The results also indicate that TG has a negative relationship with RP, which is statistically significant at the 1 percent level, thereby validating H3. Therefore, if respondents trust the government regarding COVID-19 information and preparation, they will take their vulnerability to the COVID-19 more seriously. Although, Quinn et al. (2013), Hassan et al. (2021) and Sibley et al. (2020) observed that trust in government has a strong positive relationship with the adherence to health guidelines, which has a vital role in risk perception during pandemics. Additionally, AA and SM have significant positive relationships with RP at the 1 percent and 5 percent levels, respectively; hence, the H4 and H5 are validated. However, TG and AA have no indirect relationships with RP, as the H1 and H2 are statistically unsupported, indicating the insignificance of SM as a mediator factor. However, SM has a direct relationship with RP. Luu and Huynh (2020) and Hassan et al. (2021) also observed a similar relationship between SM and RP in Vietnam and Malaysia.

Discussion

This study examined the crucial role of social media (mainly Facebook) in the dissemination of information during the COVID-19 pandemic in Bangladesh. Particularly, it investigated the influence of trust in government, and awareness and attitude on risk perception during the pandemic. According to Vos and Buckner (2016), during public health crises such as the COVID-19 pandemic, people essentially depend on every information they can find about the crisis. This study is consistent with the literature, as it observed that trust in government and awareness and attitude are influenced by social media despite the insignificant relationship (Luu & Huynh, 2020). Hence, the government can employ social media in the dissemination of accurate COVID-19-related information. Several governments around the world have adopted social media as one of the main sources to distribute timely information to the public (Mejia et al., 2020). By providing accurate and timely information, governments can create awareness about preventive measures against the spread of COVID-19 (Chatterjee et al., 2020; Malecki, Keating & Safdar, 2020). This can be an effective way for the government to minimize the risk perception of COVID-19, increase awareness, and change peoples’ behaviors towards the pandemic (Hassan et al., 2021; Sibley et al., 2020). These will also help the government in earning the trust of the public.

CONCLUSION

This study assessed the trust in government, awareness and attitude, and the influence of social media in relation to risk perception during the COVID-19 pandemic in Bangladesh. Following the first case of COVID-19 on December 8, 2019, in Wuhan province of China, many researchers have begun studying the importance of social media, trust in government, and awareness and attitude in the context of risk perception (Hassan et al., 2021; Mejia et al., 2020; Seale et al., 2020; Sibley et al., 2020). The study discovered that trust in government and awareness and attitude do not have a direct influence on social media but have a positive relationship with the influence of social media (Hassan et al., 2021). Moreover, awareness and attitude, and the influence of social media were discovered to have direct positive relationships with risk perception. Therefore, people use social media to receive COVID-19 related information, which helps to better prepare themselves in terms of risk perception (Mejia et al., 2020). Thus, authorities should effectively utilize social media in the dissemination of information about COVID-19. Furthermore, trust in government has a direct negative effect on risk perception. Hence, people do not have trust in authorities and the information they provide to the public. As observed in previous studies on the COVID-19 pandemic, people’s trust in the government can help in the minimization of COVID-19 related risks (Hassan et al., 2021, Sibley et al., 2020). Therefore, the authorities of Bangladesh should strive to earn the trust of its citizens since health guidelines and information on the COVID-19 are very essential and will help in containing the outbreak. Future research can focus on the influence of social media on awareness and attitude—in view of the new normal and social norm—for a sustainable economic and social recovery from the COVID-19 pandemic. Furthermore, face-to-face interviews with wider participants can also be considered in the future study.

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