Using structural equation modeling to predict Indian people's attitudes and intentions towards COVID-19 vaccination

Mir, Hilal Hamid; Parveen, Subeena; Mullick, N. H.; Nabi, Shazia

doi:10.1016/j.dsx.2021.05.006

Cited by 47 publications

(106 citation statements)

References 33 publications

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“…Studies show that those who believe they are at greater risk or risk of infection are more likely to receive vaccines [55][56][57][58]. A survey of India's intention to vaccinate COVID-19 found that risk disclosure was not significantly associated with India's intention to become vaccinated [59], where non-vaccination risks are higher than the side effects of the vaccine itself, resulting in inconsistent results with our findings.…”

Section: Effect Of Risk Disclosure On Vaccination Intentioncontrasting

confidence: 89%

Information Framing Effect on Public’s Intention to Receive the COVID-19 Vaccination in China

Peng

Guo

2021

Vaccines

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The aims of the study were (1) to explore information framing effect on the public’s intention to receive the COVID-19 vaccination and (2) to understand the key factors influencing the intention of COVID-19 vaccinations in China. An online questionnaire survey was conducted to explore the influence of demographic characteristics, individual awareness, social relationship, risk disclosure, perceived vaccine efficacy, and protection duration under the assumptions of information framing. The results showed that (1) the persuasion effect under loss frame was higher than that under gain frame (B = 0.616 vs. 0.552); (2) there was no significant difference between sex, age, income, occupation, educational background and residence for the participants’ intention to be vaccinated; whether family members/friends were vaccinated had a strong correlation with their vaccination intention under the gain frame; (3) the higher the understanding of COVID-19 and the compliance with government COVID-19 prevention and control measures were, the higher the vaccination intention was; (4) risk disclosure had the greatest impact on people‘s COVID-19 vaccination intention; (5) perceived vaccine effectiveness and duration of protection had little effect on people’s intention to receive vaccination. The influence of information framing on the intention of COVID-19 vaccination is different. The publicity of relevant health information should pay attention to the influence of information framing and contents on the behavior of public vaccination, so as to enhance public health awareness and promote the vaccination of the whole population.

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Section: Effect Of Risk Disclosure On Vaccination Intentioncontrasting

confidence: 89%

Information Framing Effect on Public’s Intention to Receive the COVID-19 Vaccination in China

Peng

Guo

2021

Vaccines

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“…Impact: A person’s awareness and knowledge about the benefits of the action to undertake can ensure a successful launch of any new initiative. If people feel that their actions would contribute to the general welfare of the society, they are more likely to adopt a change in behavior [14] , [25] .…”

Section: Literature Reviewmentioning

confidence: 99%

“…Knowledge: Knowledge about a new initiative or goal increases a person’s confidence and self-esteem, which further increases their trust in the initiative and benefits the organization. Accordingly, when people have more knowledge about the vaccine, the different types of vaccines available, and their benefits and their side-effects, they are more likely to make an informed choice [14] , [27] .…”

Section: Literature Reviewmentioning

confidence: 99%

“…Country like Israel have successfully inoculated a significant percentage of citizens using incentives and motivation [13] . Unfortunately, in India, misinformation, and misplaced beliefs have led to fears about the potentially harmful effects of vaccines [14] . In light of this situation, this study aims to use the “BeSD” vaccination model ( figure 1 ) as a theoretical stance to map the relationship between vaccination confidence, motivation, behaviour and the practical issues that affect vaccine uptake among rural Indians.…”

Section: Introductionmentioning

confidence: 99%

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Explaining the intention to uptake COVID-19 vaccination using the behavioral and social drivers of vaccination (BeSD) model

et al. 2022

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Background The World Health Organization (WHO) has proposed a tool to measure behavioral and social drivers (BeSD) of vaccination uptake intentions of people across all countries. This study tests BeSD model to predict people’s intentions to uptake COVID-19 vaccination in rural India. Methods An online cross-sectional survey was developed for the purpose based on the components of the BeSD model, i.e., confidence, motivation, and behavioral intention. A convenient sampling technique was used to collect samples, amounting to a total of 625, from rural Bengaluru, in the Karnataka state of India. Structural equation modelling (SEM) was applied to examine the proposed model. All respondents for the survey were in the age category of 18-68 years with a mean age of 35 years. Findings The results showed that 85% of COVID-19 vaccine uptake intentions can directly or indirectly be attributed to the government’s vaccine communication strategy, perceived threats about the vaccine, and their trust in the healthcare sector. The dimensions of the vaccine acceptance scale (motivation factors) act as a mediator between these factors and COVID-19 vaccination uptake (the behavioral factor). Conclusion The study demonstrates that the BeSD framework is an efficient model for predicting the COVID-19 vaccination uptake in India.

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“…Adopting protective behaviors in response to infectious respiratory illnesses such as hand cleanliness, social distance, and mask-wearing can significantly influence the course of a pandemic. PMT [30,31] and TPB [32,33] provide valuable frameworks for analyzing behavioral choices during such outbreaks. Individuals are primarily motivated to engage in protected activity when confronted with a frightening situation.…”

Section: Theoretical Foundationmentioning

confidence: 99%

A Hybrid Model with Spherical Fuzzy-AHP, PLS-SEM and ANN to Predict Vaccination Intention against COVID-19

et al. 2021

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This study aims to identify the key factors affecting individuals’ behavioral vaccination intention against COVID-19 in Vietnam through an online questionnaire survey. Differing from previous studies, a novel three-staged approach combining Spherical Fuzzy Analytic Hierarchy Process (SF-AHP), Partial Least Squares-Structural Equation Model (PLS-SEM), and Artificial Neural Network (ANN) is proposed. Five factors associated with individuals’ behavioral vaccination intention (INT) based on 15 experts’ opinions are considered in SF-AHP analysis, including Perceived Severity of COVID-19 (PSC), Perceived COVID-19 vaccines (PVC), Trust in government intervention strategies (TRS), Social Influence (SOI), and Social media (SOM). First, the results of SF-AHP indicated that all proposed factors correlate with INT. Second, the data of 474 valid respondents were collected and analyzed using PLS-SEM. The PLS-SEM results reported that INT was directly influenced by PVC and TRS. In contrast, SOI had no direct effect on INT. Further, PSC and SOM moderated the relationship between PVC, TRS and INT, respectively. The ANN was deployed to validate the previous stages and found that the best predictors of COVID-19 vaccination intention were PVC, TRS, and SOM. These results were consistent with the SF-AHP and PLS-SEM models. This research provides an innovative new approach employing quantitative and qualitative techniques to understand individuals’ vaccination intention during the global pandemic. Furthermore, the proposed method can be used and expanded to assess the perceived efficacy of COVID-19 measures in other nations currently battling the COVID-19 outbreak.

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Using structural equation modeling to predict Indian people's attitudes and intentions towards COVID-19 vaccination

Cited by 47 publications

References 33 publications

Information Framing Effect on Public’s Intention to Receive the COVID-19 Vaccination in China

Information Framing Effect on Public’s Intention to Receive the COVID-19 Vaccination in China

Explaining the intention to uptake COVID-19 vaccination using the behavioral and social drivers of vaccination (BeSD) model

A Hybrid Model with Spherical Fuzzy-AHP, PLS-SEM and ANN to Predict Vaccination Intention against COVID-19

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