Misinformation as a Determinant of Response to COVID 19

Abstract

Most of the micro and macro effects of the COVID-19 pandemic on the global economy have been investigated in the past two years. Few studies have examined COVID disinformation in non-Western countries. India produced the most social media disinformation, probably due to its high internet penetration, increased social media consumption, and low internet literacy (Al-Zaman, 2022a). To quantify the influence of disinformation on pandemic response, this study used mixed methods. The variables were examined through in-depth interviews. As they use digital media more than others, participants under 40 provided quantifiable data (The Future of India Foundation. (2022). Politics of disinformation: Why the current approaches are geared to fail and possible path forward. Retrieved from https://futureofindia.in/reports). It is mainly collected from metro cities of India. Moderation analysis using PLS-SEM examined whether self-perceived media literacy moderates the link between fake social media news and COVID-19 anxiety. The study findings have been linked to the theoretical foundation, the availability heuristic. This study holds significance as its implications will be beneficial in tackling the challenges associated with misinformation and its influence on response to pandemics that might be experienced in the future.

The spread of COVID-19 has influenced lives in several ways, viz. economic instability, adverse effects on physical and mental health, changed consumer behavior, and re-skilling, to name a few. According to the World Health Organization (WHO), a pandemic is an infectious disease that widely spreads in a community or worldwide. For the past centuries, there have been several disease outbreaks, including cholera, malaria, yellow fever, dengue fever, severe acute respiratory syndrome (SARS), Ebola, mumps, and the Zika virus, to name a few. The swine flu was one of the worst pandemics in the past 20 years (Shorey & Chan, 2020). The COVID-19 pandemic differed from past pandemics, especially concerning access to information.

During past epidemics and pandemics, information has been accessed through traditional sources like newspapers, radio, television, and magazines, to name a few. Since the 1990s, digital media sources have emerged, resulting in access to more real-time information. Access to information is certainly beneficial to take better decisions. However, in this age of information overload, it is sometimes challenging to verify the authenticity of the received information. Hence, the chances of the spread of misinformation cannot be ruled out. Misinformation is the unintentional dissemination of false and misleading information (CSI Library, n.d.). In addition, misinformation during the spread of pandemics may intensify the severity of adversities that people might face. Instead, Tedros Adhanom Ghebreyesus, director-general of WHO, referred to the COVID-19 pandemic as an “infodemic” (World Health Organization, 2021). It relates to information overload that could be right or wrong, making it difficult to know what to believe. Since the start of the COVID-19 epidemic, the prevalence of fake news, false information, and conspiracy theories has increased substantially. It is alarming as it threatens public confidence in healthcare programs and organizations (The Lancet Infectious Diseases, 2020). Misinformation can have a detrimental impact on the mental health of individuals and can result in chaos and economic loss (Kanozia, Kaur, & Arya, 2021). Making the wrong decision, based on false information, can result in death. Misinformation about the coronavirus is to blame for the hospitalization of close to 6,000 people in the first 3 months of 2020 worldwide. At least 800 people might have passed away due to COVID-19 misinformation. The infodemics can foster a climate of uncertainty. Uncertainty breeds skepticism and mistrust, creating the ideal conditions for despair, anxiety, blame game, stigma, violent behavior, and the rejection of effective public health policies, all of which can result in fatalities (Fighting Misinformation in the Time of COVID-19, One Click at a Time, 2021).

Further, past studies relating to people’s response to the pandemic in other countries have been related to other theoretical frameworks like The Theory of Planned Behavior, Uses and Gratification Framework, Social Cognitive Theory, Theory of Prosocial Behavior, Cognitive Load Theory, Dependency Theory & Nudge Theory (Apuke & Omar, 2021; Dou, Yang, Wang, & Li, 2022; Ferreira & Borges, 2020; Hossain et al., 2021; Islam, Laato, Talukder, & Sutinen, 2020; Malik, Islam, & Mahmood, 2022; Pennycook, McPhetres, Zhang, Lu, & Rand, 2020; Yahaghi et al., 2021). The spread of COVID misinformation has been highest in India (Al-Zaman, 2022a). Therefore, in addition to the past studies discussed in the literature, mixed research studies must be undertaken to understand the perceptions of people regarding misinformation. It is essential, as it will enable policymakers to figure out how to control the spread of misinformation in the future.

If economies face such pandemics in the future, this study will act as a guideline to sensitize people about the worsening impact that misinformation can have in such challenging times. Hence, it will be pertinent to estimate the impact of misinformation in changing the response to the pandemic and its connection with the availability heuristic can be instrumental in devising effective policies to control the spread of misinformation and the pandemic. The study attempts to answer the following research questions:

• (1) Did misinformation in the form of social media fake news influence our anxiety during COVID-19?

• (2) What were the reasons for the spread of misinformation?

• (3) Is the availability heuristic theory contributing to understanding people’s belief in misinformation and its impact on COVID-19 anxiety levels during the pandemic?

Review of Literature

Availability Heuristic as a Theoretical Framework

This study is grounded in the theoretical framework established by Tversky and Kahneman (1973) in their pioneering publication “Availability: A heuristic for judging frequency and probability.” Behavioral economics enables one to acknowledge that people may act irrationally and understand their atypical conduct. Behavioral economics uses economics, sociology, psychology, anthropology, neurology, and biology to understand and predict economic decisions. Furthermore, it scrutinizes theories by conducting experiments and analyzing real evidence, rather than relying solely on assumptions. This field has helped explain illogical conduct and why people often act against their interests (Goodwin et al., 2018). People often overvalue conveniently accessible or vivid information. The availability heuristic is used to estimate frequency or probability by how quickly instances or associations spring to mind. Thus, overusing the availability heuristic produces systemic biases (Tversky & Kahneman, 1973).

COVID-19 and Misinformation

Declining growth, global supply chain disruption, diminishing demand, increased inequality, and vulnerability destroyed economies during the COVID-19 pandemic (Dhar, 2020; Dev & Sengupta, 2020; Bagchi, Chatterjee, Ghosh, & Dandapat, 2020; Maital & Barzani, 2020; The World Bank, 2022). Shrestha et al. (2020) calculated the Pandemic Vulnerability Index to examine COVID-19’s influence on globalization and proposed solutions for vulnerable countries. Few qualitative studies have examined the impact of disinformation in India for certain sectors and locations (Akbar, Panda, Kukreti, Meena, & Pal, 2021; Al-Zaman, 2022a, b; Datta, Yadav, Singh, Datta, & Bansal, 2020; Husain, Shahnawaz, Khan, Parveen, & Savani, 2021). As many have investigated the impact of COVID-19 on tourism and other heavily damaged service sectors, Beckman & Countryman (2021) emphasize the fall in food away from home spending and its impact on agricultural commodity production and trade. Due to domestic violence and home obligations, women have suffered more since the pandemics (Wenham et al., 2020). Pandemics also cause stress, dread, despair, and social and hazardous behavioral abnormalities in children and adolescents (Meherali et al., 2021). Though many studies have estimated the pandemic’s macro impact, few comprehend its reaction factors (Sharma, Borah, & Moses, 2021). COVID-19 reaction may be affected by misinformation. Researchers estimate misinformation’s macro impact on economies. Although some disinformation may be minor, others may be serious by convincing the public to trust unjustified and/or unsupported claims of protection over scientifically tested advice (Ahinkorah, Ameyaw, Hagan, Seidu, & Schack, 2020). The desire for cognition, liberals, and disinformation were adversely connected with COVID-19 myths (Borah, Su, Xiao, & Lai Lee, 2022; Su, Borah, & Xiao, 2022a; Su, Lee, & Xiao, 2022b).

Social Media Fake News, COVID-19 Anxiety, and Self Perceived Media Literacy

Social media increased self-efficacy and perceived knowledge, boosting third-person perception. Social media may also create an echo chamber where people think they are immune to fake news (Yang & Tian, 2021). COVID-19 misinformation is positively connected with social media news. Social media fake news is incorrect information that gets circulated easily in the age of information overload with the help of online platforms (Rocha et al., 2021). Homogeneous online discourse also mediated the link between social media news use and COVID-19 misperceptions. Self-perceived media literacy influenced the main and indirect associations between social media news and COVID-19 misconceptions (Borah, Su, Xiao, & Lai Lee, 2022; Su, Borah, & Xiao, 2022a; Su, Lee, & Xiao, 2022b). Self-perceived media literacy is the belief of individuals that they are media literate and are capable of accessing, analyzing, and evaluating media content (Vraga, Tully, Kotcher, Smithson, & Broeckelman-Post, 2015). According to Borah, Su, Xiao, & Lai Lee (2022), general misunderstandings mediated the correlation between incidental news exposure and COVID-19 misperceptions, while self-perceived media literacy reduced this association. People who received news over social media were more judgmental and prejudiced (Ahmed, Chen, & Chib, 2021). Damstra & Hameleers (2021) stated that exposure to the news did not increase accuracy; rather, a negative relationship was discovered. Eventually, digital news lost its effect as people learned more. One of the main reasons why people share misinformation is that they find it difficult to understand whether the received information is correct or not and if they are nudged to think about authenticity before sharing, the spread of misinformation can be curtailed significantly (Pennycook, McPhetres, Zhang, Lu, & Rand, 2020). Kanozia (2019) emphasizes the importance of digital literacy and fact-checking with AI and machine learning to disprove fake news. Twitter and Facebook had the most fake news in India, and much of it was political. Cross-checking official sources is the most prevalent fake news debunking method (Kanozia, Kaur, & Arya, 2021).

Zhang et al. (2022) leverage data, psychology, and communication theories to examine social media misinformation correction efficacy. Due to inaccurate information, self-reported compliance with COVID-19 public health recommendations, readiness to get immunized, and promotion of vaccination to susceptible populations decrease (Roozenbeek et al., 2020). Further, misinformation has disseminated myths that have caused people to skip vaccines, refuse face masks, and seek unproven treatments, increasing morbidity (Caceres et al., 2022). Dubé et al. (2022) explored how web-based misinformation and disinformation influence vaccine acceptability and offered solutions. Internet access makes it easier to spread anti-vaccination misinformation, especially among those who are skeptical of science and doctors. Some wealthy people ignore the hazards of vaccine-preventable diseases since direct exposure is rare (Trujillo & Motta, 2021). Fighting misinformation can lessen vaccine aversion (Kanozia & Arya, 2021). Conspiracy theories are more popular than health misinformation (Enders, Uscinski, Klofstad, & Stoler, 2020). Akbar, Panda, Kukreti, Meena, & Pal (2021) found sectarian bias influences Indian disinformation. In India, Al-Zaman (2022b) highlights a paradigm shift in communication infrastructure, a lack of digital literacy, insufficient anti-disinformation activities, and a political climate to understand the epidemic’s misinformation situation. Yıldırım, Akgül, & Geçer (2022) define COVID-19 anxiety as fear and unease generated by pandemics. Studying anxiety can change public attitudes about infection prevention and decrease (Apisarnthanarak et al., 2020; Jones-Jang, 2021). COVID-19 anxiety greatly affects patients’ health and coping (Yıldırım, Akgül, & Geçer, 2022). Recent research demonstrates that social media fake news induces anxiety, fatigue, psychic pain, despair, dread, and panic (Rocha et al., 2021). Spanish non-health professionals’ COVID-19 suffering was assessed by Ruiz-Frutos et al. (2020). Another study by Sallam et al. (2020) indicated that misinformation regarding the pandemic’s cause (conspiracy, biological warfare, and 5G networks) increased Jordanian concern. Secosan, Virga, Crainiceanu, Bratu, & Bratu (2020) found that Romanian frontline healthcare workers during the COVID-19 epidemic reported stress, concern, and insomnia. Radwan, Radwan, & Radwan (2020) found that social media scared Palestinian students about COVID-19. In Italy, excessive social media use increased anxiety during the COVID-19 epidemic (Boursier, Gioia, Musetti, & Schimmenti, 2020). Based on the above justification, we formulated the hypotheses that (Figure 1):

  

Research Methodology

The dissemination of misinformation motivated by shame, blame, and fear was one of the risks to India’s COVID-19 response. There were some initiatives taken to reduce the spread of misinformation, like more than 400 diverse Indian scientists voluntarily created Indian Scientists’ Response to COVID-19 to challenge false information about the disease (The Lancet, 2020). However, the spread of misinformation still has a vital role to play in determining the response. Hence, the present study aims to estimate the impact of misinformation in determining the response to the pandemic. The mixed research method, for example, both qualitative and quantitative methods of data collection and analysis, has been utilized to better gain insights and answer the research questions. It gives policy analysts the ability to both qualitatively comprehend and quantitatively and graphically explain complicated problems. A multi-method approach to policy research, in contrast to a single method, uses diverse methodologies that better respond to the various stakeholders of policy issues and has the potential to better explain the complex phenomena of the social world (Creswell, 1999).

The purposive sampling technique has been used to identify the participants of the study. A random selection of sampling units within the population segment that contains the most information regarding the attributes of interest is referred to as purposive sampling (Guarte & Barrios, 2006). Social media has boosted public participation and democratized access to information, but misinformation on these platforms has polarized users more than ever. In India, 70% of internet users are under the age of 35. They make up 65% of the country’s population. The current content moderation practices used by social media platforms are more “geared toward public relations” than “geared to combat the spread of disinformation.” The broader issue is that the platforms themselves contribute to the dissemination of false information and hate speech through their “value-neutral” approach of amplifying posts that generate more interaction (likes, shares, and comments) rather than postings that have been reviewed for validity and quality (The Future of India Foundation, 2022). Therefore, people younger than 40 were decided to be the sampling frame. Depending on the diversity of the problem, a mixed–research method was adopted. Ten in-depth semi-structured interviews were conducted, and an online survey was conducted from December 2022 to January 2023 to collect quantitative data. Since urban areas have better access to connectivity, primary data was decided to be collected from the metro cities in India. A pilot study was conducted to check the consistency. Then, the questionnaire was purposively sent through email to people belonging to less than 40 years of age. It was sent to 400 people and there were 227 complete responses that were received. Therefore, the response rate was 56.75%.

Instrument Development

A 5-point Likert scale was used to obtain data regarding social media fake news, COVID-19 anxiety, and self-perceived media literacy (see Table 1). COVID-19 anxiety was measured with five items which are from the coronavirus anxiety scale (CAS) (Lee, 2020). The scale was also used in the study of Mohanty et al. (2021) to assess the COVID-19 anxiety of Indians. Similarly, six items were used to measure self-perceived media literacy adapted from two previous studies (Borah, Su, Xiao, & Lai Lee, 2022; Tully, Vraga, & Bode, 2020; Su, Borah, & Xiao, 2022a; Su, Lee, & Xiao, 2022b). The social media fake news was assessed with three items proposed by (Apuke & Omar, 2021). Along with the Likert scale-based questions, more questions were incorporated into the questionnaire to answer the other research questions. It consisted of questions regarding the demographic profile, source of information for COVID-related news, the source that was trusted the most, state of mind after reading COVID-related information, kind of precautionary measures followed, misinformation—its nature and source, verification of misinformation before forwarding it, reasons for the spread of misinformation, and impact of misinformation on the spread of COVID. Purposefully, more open-ended questions were incorporated to better understand people’s perspectives regarding misinformation and its impact.

Common Method Bias

Common method variance from self-reported biases can inflate variable relationships. According to Harman’s single-factor test (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003), if the total variance extracted by one factor exceeds 50%, common method bias is present in the study. The total variance extracted by one factor is 34.932% and it is less than the recommended threshold of 50%. Thus, this dataset lacks common method bias (Kock, 2015).

Analysis and Interpretation

The hypotheses were tested using a mixed method approach. Qualitative data was collected in the form of 10 in depth interviews and an online survey was conducted to collect quantitative data from metro cities in India. Measurement model and moderation analysis using PLS-SEM have been utilized to analyze the quantitative data and answer the research questions.

The COVID-19 pandemic has been called an “infodemic” and most of the spread of misinformation was experienced in India (The Lancet Infectious Diseases, 2020; Al-Zaman, 2022a). Out of the 10 in-depth interviewees, Mr. MS¹ was unable to make a differentiation between correct and misleading information and was skeptical of even believing the fact-checking websites for accuracy, when asked about the verification of the authenticity of the information. Six participants seemed to be aware of the spread of misinformation and shared about few pieces that they came across like:

……… (name of the country is not disclosed) had played a vital role in the spread of COVID; It spreads through surface/newspapers/air; It does not sustain in the hot climate; Rains will kill the virus; Helpline numbers shared on news channels; Usefulness of Remdesivir in increasing the platelet count; Consuming cumin and saltwater/lemon water/tobacco/ hot water and cardamom can save us from infection; Covishield is more effective than Covaxin; Once vaccinated, we cannot be infected with the virus; & COVID infection results into memory loss and reduced lung capacity.

When asked about instances of misinformation, Mr. AC (see Footnote 1) shared that due to this misinformation about the virus lasting long in the cold climate, people around him were making more use of heaters, drinking alcohol, eating non-vegetarian food, and keeping lights on to generate heat. So, it resulted in following certain precautions which were just not required. Also, few people had no clarity on whether to utilize reusable or use and throw masks and so ended up using contaminated masks.

The interviewees were also asked about the reasons for the spread of misinformation. Seven participants shared that some businesses could flourish due to misinformation and rather it promoted the requirement of computed tomography (CT) scans, bulk purchasing, and exacerbated the black marketing of oxygen cylinders, sanitizers, remdesivir, and vaccines for earning profits. Three of them also shared that though the home kits showed negative results, lab tests were manipulated to show positive results. Eight participants agreed upon receiving misinformation through social media and verifying the source of information was considered essential for ensuring its accuracy. Further, receiving different information from different sources caused more confusion. Misinformation resulted in a casual approach being followed by people in dealing with COVID-19 and two participants also shared that they came across people who were using fake vaccination certificates. Four of the participants verified information by talking to their family doctors or with people working in government offices. Altruism, racing to share information, and gaining popularity was mainly resulted in the sharing of information promptly with family and friends without verifying it.

A participant shared that though it is difficult to change people’s mindset in a populous nation, they can be nudged to trust the few authorized sources of information.

Ms. SK (see Footnote 1) shared that it was certainly good to check the positive news as it gave confidence that the spread of the pandemic can be curtailed by following the guidelines. She further shared it was difficult to know the status of the availability of beds, medicines, and oxygen cylinders due to manipulation. Also, she highlighted the instances of people being injected with water instead of vaccines at a few vaccination centers.

Mr. PP (see Footnote 1) and Ms. BT (see Footnote 1) emphasized that it is always the richer sections that get initial access to information and resources and so are better positioned to take timely and effective steps to save their lives. Due to the negative experiences of COVID-infected people, Mr. PP shared:

“We were following social distancing but not ‘untouchability’.”

He further shared that there was a change in cultural practices due to the pandemic and some participants also talked about the dire need for regulating media so that it will behave more responsibly and in a mature manner. They emphasized that the motive of media should be to share correct information instead of chasing money.

A 19-year-old participant Mr. RT (see Footnote 1) was interestingly part of a non-profitable organization which was verifying information from actual sources, like hospitals in case of the number of beds, and sharing real-time information with needy people. He started working for the good cause after coming across the rampant increase in black marketing and feeling that “Humanity is dead now.” He shared how the trusted websites were also showing false information regarding the availability of beds and patients were dying due to the lack of timely support. He honestly shared how their organization was also sharing misinformation in the initial few days and could have a verification team in place as more supporters joined in. He quoted an instance of misinformation:

“One early morning, around 400 people were crowded outside a gas station as they were misinformed about the availability of oxygen cylinders.”

He believed such acts itself may increase the spread of the pandemic.

Followed by the in-depth interviews, a questionnaire was designed, and primary data was collected from metro cities in India by circulating the Google form. The responses were collected from 227 respondents staying in Pune, Mumbai, Bangalore, Hyderabad, Ahmedabad, and Chennai. Out of the total respondents, 67.7% were male and 31.6% female. Further, 42.2% belonged to the <20 age group and 57.8% were from the 20 to 39 age group. The majority of the participants (83.2%) belonged to the Hindu religion and 87.7% had completed education up to post-graduation. Out of the 57.3% employed respondents, 36.7% worked in the private sector, 3.2% were employed in the government sector, and 17.4% were self-employed.

The source of information can play a vital role in avoiding access to misinformation. Hence, respondents were questioned regarding the source of information that they accessed. Most of them got COVID-related information from newspapers (69%), news channels (66.5%), word of mouth (47.7%), WhatsApp (37.4%), Instagram (33.5%), Facebook (12.3%), and LinkedIn (4.5%). Further, an attempt was made to find out which source the respondents trusted the most. Most of them trusted newspapers (67.7%) and news channels (46.5%). However, word of mouth (10%) and social media (<10%) were also the sources trusted by a few participants. The information about the spread of the pandemic can result in mixed reactions. Therefore, there were few respondents who believed in spreading awareness and reading less of the negative information. However, many others experienced anxiety, fear, sadness, stress, irritation, frustration, confusion, and helplessness. Datta et al. (2020) highlighted that COVID-19 updates made respondents uncomfortable and distracted their decision-making. The COVID-related information also made the participants more cautious and most of them followed guidelines like social distancing (78.1%), using masks (94.8%), and sanitizers (89%). The COVID pandemic was rightly called the infodemic, it gets reflected through the primary responses as well. When the respondents were asked whether they had come across misinformation, 81.3% agreed to it. They admitted receiving it through social media, news channels, and word of mouth and stated that most of it was negative. Most of the misinformation had spread through social media and word of mouth (Datta et al., 2020). Out of the total respondents who came across misinformation, 76.8% verified its authenticity by checking facts online, in newspapers, and with the help of networks, consulting doctors, and government officials. The remaining participants did not feel the need to verify as they believed the information and interestingly one of the respondents stated that “we were busy trying to secure ourselves” so could not think of cross-checking. If the received information is forwarded to acquaintances without checking its authenticity, it may increase the spread of misinformation and change our response to COVID. It was found that 28.4% of the participants had forwarded the information without verifying it. Further, though the ideal approach is to verify the information before sharing it, it is easier said than done. Most of the respondents (81.3%) found it difficult to verify the received information for its accuracy. Some of the reasons cited by participants for the spread of misinformation are fear, social media usage, word of mouth, politics, excessive access to information, profit-making, gaining popularity, digital illiteracy, ignorance, lack of awareness, and verification of information. Socialization, entertainment, altruism, pass time, self-promotion, and information-seeking were the main predictors of sharing fake news (Apuke & Omar, 2021; Islam, Laato, Talukder, & Sutinen, 2020).

Interestingly, two of the respondents stated:

There was widespread panic and fear amongst the public. So, whenever some new type of information was released, they would blindly forward it everywhere. They thought they were doing the right thing, but little did they know that they were acting as an agent of misinformation.

In this age of information overload, it might become difficult for information seekers to understand which information can be trusted and act accordingly. Therefore, 80% of the participants agreed that access to too much information changed their response to the pandemic.

Furthermore, 76.1% of the respondents felt that having access to misinformation increased the spread of COVID in India as people became more careless and did not follow the necessary precautionary measures. Spreading misinformation for black marketing and profit making was another important reason stated by many that actually resulted in more spread of the virus. A few of the interesting responses that were shared by the respondents are:

Incorrect information increased the spread of COVID in India because a lot of the areas were reported as hot spots when they weren’t and a lot of the deaths and infections in particular cities and even states were underreported purposefully.

People used to roam around more during the second wave considering that there wouldn’t be any problem after the first wave had hit. But unfortunately, that belief, which was because of incorrect information, spread the virus more.

The respondents were also suggested to share their perspectives on the ways in which the spread of misinformation can be reduced in the future. Most of them shared that making information available through a few trusted sources by the government, verification of it, regulating media through a central regulatory authority, and creating awareness can curtail the spread of misinformation. One of the participants interestingly shared:

“Misinformation cannot be stopped completely but it can be countered by maximizing the spread of correct information.”

One of the main purposes of this study has been to assess a moderating effect of Self-Perceived Media Literacy on the relationship between social media fake news and COVID-19 anxiety. Fundamentally, this study has successfully tested a moderation effect by establishing two hypotheses. First, social media fake news influences COVID-19 Anxiety during the pandemic and second self-perceived media literacy moderates the effect of social media fake news on COVID-19 Anxiety during the COVID-19 pandemic. To operationalize the research objectives and to test the hypotheses in the research model, we used PLS-SEM as it is suitable for complex models (Sarstedt & Cheah, 2019). There are two specific reasons for using PLS-SEM for the study. Firstly, PLS is popular among researchers because it can handle complex model analysis with small sample sizes under non-normality conditions (Chin, 1998), which suits the sample size and constructs of this study. Secondly, PLS-SEM is supposed to be more favorable for studies with moderating and mediating effects (Becker, Cheah, Gholamzade, Ringle, & Sarstedt, 2023).

Quantitative Analysis

Assessment of the Measurement Model

The measurement model is assessed by following the recommendations of Roldán & Sánchez-Franco (2012). Since all the constructs are reflective in nature, our first step was to analyze the values of factorial loads, reliability, and validity of the constructs. The reliability is the internal consistency which is assessed through composite reliability and Cronbach’s alpha (see Table 2). The reliability of each variable using Cronbach’s alpha should be more than 0.70 (Hair, Sarstedt, Matthews, & Ringle 2016; Sarstedt & Cheah, 2019). Whereas the convergent validity is assessed by average variance extracted (AVE) (see Table 2), and discriminate validity (see Table 3) is measured by the Fornell–Larcker criterion. The factor loadings of the remaining items as indicated in Figure 2 and Table 2 range from 0.752 to 0.897 which outstripped the cut-off point of 0.60 as suggested by Hair et al. (2011). As shown in Table 2, all the variables AVE range from 0.643 to 0.768 which are all above the acceptable value of 0.50 as suggested by Hair et al. (2012). According to the study by Cho, Hwang, Sarstedt, & Ringle (2020), the value of inner and outer VIFs should be <5, indicating that there is no issue of collinearity in the model. The result of inner VIF is also <5 (between 1.619 and 3.493), indicating that there is no issue of collinearity in the model (see Table 2).

The discriminant validity (DV) was tested by analyzing the AVE’s square root as suggested by (Hair, Ringle, & Sarstedt, 2011). To assess the DV, Fornell & Larcker (1981) approach was utilized, and it is fulfilled or achieved if the exogenous variance is greater than the common value with other variables (Hair, Ringle, & Sarstedt, 2011). The diagonal values in Table 3 reflect the square root of the AVE’s whereas the off diagonals reflect the correlations of the study variables. The Fornell–Larcker criterion results revealed that the square root of the AVE of the constructs is above the correlations of all other constructs. Therefore, all conditions were met that fulfill the measurement model Discriminant Validity. Hence, Tables 2 and 3 have established the convergent and DV of this research.

Evaluation of structural model

In Figure 2, the outcome revealed that the R² value of COVID-19 Anxiety was 0.250 which provides moderate explanatory strength (Chin, 1998). After the blindfolding protocol has been performed, the Q² value for COVID-19 anxiety was 0.218, which is higher than 0, and proves that the structural model has adequate predictive significance (Hair, Ringle, & Sarstedt, 2013). After determining the R² and Q², the hypotheses are tested.

For the hypothesized relationships the path estimates and t-statistics were examined using a bootstrapping approach with a re-sampling of 5,000. Figure 2 and Table 4 reveal the analysis of the structural model. The results in Figure 2 and Table 4 showed that social media fake news has a substantial effect on COVID-19 anxiety (β = 0.321, t = 5.600, p < .000). Thus, hypothesis 1 is supported.

The primary goal of this section is to experimentally examine the H2 research hypothesis, which concerns the investigation of the moderating effect of self-perceived media literacy on the relationship between social media fake news and COVID-19 anxiety (Figure 2). Here, a moderator in a sample can change the intensity and frequency of a correlation between two constructs (Hair, HultRingle, & Sarstedt, 2021). Specifically, the interaction effect results in Table 4 indicated that the relationship between social media fake news and COVID-19 anxiety was statistically significant through the moderator Self-perceived media literacy (β= −0.252, t = 4.531, p < .000), thus hypothesis 2 is supported. Since we have a negative beta coefficient for this moderating effect, it can be inferred that self-perceived media literacy negatively moderates the positive relationship between social media fake news and COVID-19 anxiety. In other words, the impact of social media fake news on COVID-19 anxiety tends to decrease for individuals who perceived that they have a high level of media literacy. Therefore, Hypothesis H2 is also supported. To aid the interpretation of the moderating effects, the researcher conducted a simple slope test and plotted the test results in Figure 3. In other words, the relationship between social media fake news and COVID-19 anxiety was found to be lesser with a high self-perceived media literacy than that with low self-perceived media literacy as shown in Figure 3.

The belief in COVID-19 misconceptions and misleading information was less for those with higher education and confidence in government information. The infodemic was made worse by having trust in news from social media, interpersonal communication, and clerics followed by the increasing confidence in COVID-19 myths and false information, which in turn led to less critical social media posting habits (Melki et al., 2021). Wei, Gong, Xu, Eeza Zainal Abidin, & Destiny Apuke (2023) emphasized that the sharing of fake news was more influenced by social media trust and people with poor social media literacy are more likely to spread false information. The possibility of recognizing misinformation substantially increases due to information literacy but not because of other forms of literacy (Jones-Jang, Mortensen, & Liu, 2021). Instead, even if media literacy has become very important to curtail the spread of misinformation, the lack of trust makes us reconsider it (Pérez-Escoda, Pedrero-Esteban, Rubio-Romero, & Jiménez-Narros, 2021). Further, with growing digitalization, we must accept the problem of spreading misinformation (Lee, Lee, & Lee, 2022). Bas-Sarmiento, Lamas-Toranzo, Fernández-Gutiérrez, & Poza-Méndez (2022) suggested that strengthening health literacy and curtailing the spread of misinformation can enable us to better deal with COVID. In addition, science media literacy skills support the adoption of healthy behaviors by enhancing knowledge (Austin, Austin, Willoughby, Amram, & Domgaard, 2021).

Availability Heuristic and Misinformation

During the spread of the COVID-19 pandemic, the misinformation might have acted as a cognitive tax thereby influencing human beings to behave differently. Nisbet & Kamenchuk (2021) argue that, in addition to the impact of information sources and cognitive biases, the abundance of competing claims and information intrinsic to infodemics makes it more difficult for people to distinguish between accurate and false information, increasing the cognitive and emotional costs associated with doing so. This is what the authors referred to as “informational learned helplessness.” (Figure 4).

The cognitive burden could have resulted in giving undue importance to negative information even if it is just one of the many types of feedback. Instead, most of the misinformation (63.2%) about the pandemic was negative (Al-Zaman, 2020). In addition, misinformation was one of the factors that exacerbated vaccine hesitancy (Roozenbeek et al., 2020). Through the open-ended questions, an attempt was made to figure out the reasons for the spread of misinformation and whether it has altered our responses to the pandemic. Most of the participants highlighted that the easy accessibility of information from social media and news channels and its lack of verification fiercely increased the spread of misinformation and changed our response to COVID. Therefore, the availability heuristic theory is enabling us to comprehend why people believed misinformation and acted in an unusual manner.

Conclusion and Recommendations

Misinformation has been creating havoc in this information-overload age. Further, the spread of such misleading information during pandemics can worsen its impact by changing our responses. The spread of misinformation was highest in India (Al-Zaman, 2022a). Therefore, through this study, the authors tried to identify whether misinformation influenced people’s response to the pandemic in metro cities of India. Through in-depth interviews and online surveys, it was realized that people had been resorting to home remedies and had many misperceptions regarding vaccines and the spread of the virus. The key reasons for the spread of misleading information were found to be altruism, ignorance, gaining popularity, lack of digital literacy, black marketing, and profit making. Further, a conceptual model was developed to test the relationship between social media fake news and COVID-19 anxiety and also to find out whether self-perceived media literacy moderated this association. The findings revealed that with a high self-perceived media literacy, the association between social media fake news and COVID-19 anxiety was weaker than with a low self-perceived media literacy. Therefore, both the stated hypotheses can be accepted. The availability heuristic theory further enabled us to better understand that the quick availability of social media information made people believe it easily. It also helped us to interpret why COVID-19 anxiety increased with more spread of social media fake news. Since pandemics may be experienced even in the future, it is vital to take steps to reduce the spread of misinformation.

A few policy implications that follow from this study are the timely sharing of both positive and negative information regarding the spread of such pandemics by the government authorities, regulation of media, awareness campaigns for nudging people to act more rationally, and bringing in more media literacy. Verification and sharing of correct information by the government authorities from time to time can sensitize and caution people against the use of unreliable sources and can enable them to prepare better and handle such crises. Since the participants in the present study believed that misinformation aggravated the crisis, controlling its spread can minimize the severity and hazards associated with such pandemics in the future. Nudging people to not spread misinformation for self-interests (e.g., black marketing and profit making) and also to avoid unintentional sharing of misinformation which may harm public safety, can go a long way in ensuring improved economic welfare.

Limitations and Future Research Directions

Though the authors have attempted to address a vital problem of the impact of misinformation on the response to COVID in India, where the spread has been the highest, there is certainly scope for improvement. The study did not cover responses from rural areas of the country. Further, it would be interesting to undertake a comparative analysis of the impact of misinformation in metro cities. Since it is a cross-sectional study, the opportunity to better understand the influence of misinformation in altering responses with the help of panel data is missed. In future studies, along with in-depth interviews and surveys, focus group discussions will also be conducted, to have access to more rich data. It would be of interest to examine with experimentation whether the nudge theory plays a positive role in changing our response to pandemics due to misleading information. To get a comprehensive understanding of the influence of misinformation in India, further studies will cover the rural counterpart as well.

Footnotes

References

Author note

Dr. Shilpa Deo is currently working as an Assistant Professor at the School of Humanities & Social Sciences, DES Pune University, India. She also serves as a Research Fellow at the Centre for International Trade and Business in Asia, James Cook University, Australia. Her research interests include consumer behavior, poverty, vulnerability, inequality, and post-COVID dynamism to name a few.

Dr. Abhijit Mohanty is currently working as an Assistant Professor at the School of Management, Centurion University of Technology & Management, Bhubaneswar, Odisha. His research interests include branding, service marketing, service quality, and consumer behavior.

Dr. Deependra Sharma is working as Dean of the School of Business at Dr. Vishwanath Karad MIT World Peace University, Pune, India. He is an Indian Institute of Management-Ahmedabad (IIM-A) alumnus and has 22 years of experience in academic administration, teaching, and research blended with experience in industrial marketing.

Dr. Sushil Sharma is currently an Associate Provost at Texas A&M University. He has the unique distinction of earning two doctoral degrees. He has over 20 years of administrative leadership experience and more than 25 years of experience in higher education. His research has appeared in several highly ranked journals in the MIS field, including Decision Support Systems, Communications of the Association for Information Systems, European Journal of Information Systems, Information Systems Frontiers, Journal of Information Privacy & Security (JIPS), Electronic Commerce Research Journal, and Information Management and Computer Security. His primary research interests are in computer information systems security, e-Learning, e-Government, computer-mediated communications, human–computer interaction (HCI), and community and social informatics.

Prof Dinesh Khisti holds a doctoral degree from Symbiosis International University, Pune. He completed his M.B.A. in Finance from Y.C.M.O. University, Nashik. He is a Six Sigma Black Belt Certified practitioner. He is a mechanical engineer with PG qualifications in Production Management. He is an Associate Professor in Operations Management at MIT WPU, Pune, India. Before joining MIT WPU, he worked with many multinational manufacturing industries as a Management Coach and Corporate Consultant for Operations Excellence. He has over 41 years of experience in teaching and industrial projects.