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Using structural equation modeling to predict Indian people's attitudes and intentions towards COVID-19 vaccination.
Diabetes Metab Syndr. 2021 May-Jun; 15(3):1017-1022.DM

Abstract

BACKGROUND AND AIM

Understanding people's attitudes towards Covid-19 vaccination is crucial to the successful implementation of a vaccination program. Hence this research study seeks to identify critical factors influencing Indian people's attitudes and intentions to take up Covid-19 vaccinations.

METHODS

An online questionnaire was administered to a sample (n = 254) drawn from Indian population, to assess the impact of perceived benefits, risk perceptions, social media exposure, social norms, and trust associated with Covid-19 vaccines on people's attitudes towards Covid-19 vaccines and their intentions to take up the Covid-19 vaccinations.

RESULTS

The findings showed that the perceived benefits, social norms, and trust correlated significantly with people's attitudes towards Covid-19 vaccinations. In contrast, risk perceptions and social media exposure showed an insignificant influence on people's attitudes towards Covid-19 vaccinations. Social norms, trust, and people's attitudes towards the Covid-19 vaccinations are significantly correlated with their intentions to take up Covid-19 vaccinations. On the contrary, social media exposure was found to have an insignificant influence on people's intentions to take up Covid-19 vaccinations.

CONCLUSION

Participants' intentions to take up Covid-19 vaccinations was influenced mainly by their attitudes and perceptions of Covid-19 vaccines in general, which strongly confirms the importance of various dimensions (perceived benefits, trust, social norms) of Covid-19 vaccines in cultivating Covid-19 vaccination acceptance among participants'.

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Authors+Show Affiliations

Mir HH
Center for Management Studies Jamia Millia Islamia Central University, New-Delhi, 110025, India. Electronic address: mirhilal410@gmail.com.
Parveen S
Department of Commerce and Business Studies Jamia Millia Islamia Central University, New-Delhi, 110025, India.
Mullick NH
Center for Management Studies Jamia Millia Islamia Central University, New-Delhi, 110025, India.
Nabi S
Department of Commerce and Business Studies Jamia Millia Islamia Central University, New-Delhi, 110025, India.

MeSH

AdolescentAdultAgedAged, 80 and overAttitude to HealthCOVID-19COVID-19 VaccinesFemaleHealth Knowledge, Attitudes, PracticeHealth LiteracyHumansIndiaIntentionInternetLatent Class AnalysisMaleMiddle AgedModels, TheoreticalPatient Acceptance of Health CareSARS-CoV-2Surveys and QuestionnairesVaccinationYoung Adult

Pub Type(s)

Journal Article

Language

eng

PubMed ID

34000711

Citation

Mir, Hilal Hamid, et al. "Using Structural Equation Modeling to Predict Indian People's Attitudes and Intentions Towards COVID-19 Vaccination." Diabetes & Metabolic Syndrome, vol. 15, no. 3, 2021, pp. 1017-1022.
Mir HH, Parveen S, Mullick NH, et al. Using structural equation modeling to predict Indian people's attitudes and intentions towards COVID-19 vaccination. Diabetes Metab Syndr. 2021;15(3):1017-1022.
Mir, H. H., Parveen, S., Mullick, N. H., & Nabi, S. (2021). Using structural equation modeling to predict Indian people's attitudes and intentions towards COVID-19 vaccination. Diabetes & Metabolic Syndrome, 15(3), 1017-1022. https://doi.org/10.1016/j.dsx.2021.05.006
Mir HH, et al. Using Structural Equation Modeling to Predict Indian People's Attitudes and Intentions Towards COVID-19 Vaccination. Diabetes Metab Syndr. 2021 May-Jun;15(3):1017-1022. PubMed PMID: 34000711.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Using structural equation modeling to predict Indian people's attitudes and intentions towards COVID-19 vaccination. AU - Mir,Hilal Hamid, AU - Parveen,Subeena, AU - Mullick,Naushadul Haque, AU - Nabi,Shazia, Y1 - 2021/05/08/ PY - 2021/04/13/received PY - 2021/04/30/revised PY - 2021/05/02/accepted PY - 2021/5/18/pubmed PY - 2021/6/25/medline PY - 2021/5/17/entrez KW - Covid-19 vaccination KW - Health belief model (HBM) KW - Statistical analysis KW - Structural equation modeling KW - Theory of planned behavior (TPB) SP - 1017 EP - 1022 JF - Diabetes & metabolic syndrome JO - Diabetes Metab Syndr VL - 15 IS - 3 N2 - BACKGROUND AND AIM: Understanding people's attitudes towards Covid-19 vaccination is crucial to the successful implementation of a vaccination program. Hence this research study seeks to identify critical factors influencing Indian people's attitudes and intentions to take up Covid-19 vaccinations. METHODS: An online questionnaire was administered to a sample (n = 254) drawn from Indian population, to assess the impact of perceived benefits, risk perceptions, social media exposure, social norms, and trust associated with Covid-19 vaccines on people's attitudes towards Covid-19 vaccines and their intentions to take up the Covid-19 vaccinations. RESULTS: The findings showed that the perceived benefits, social norms, and trust correlated significantly with people's attitudes towards Covid-19 vaccinations. In contrast, risk perceptions and social media exposure showed an insignificant influence on people's attitudes towards Covid-19 vaccinations. Social norms, trust, and people's attitudes towards the Covid-19 vaccinations are significantly correlated with their intentions to take up Covid-19 vaccinations. On the contrary, social media exposure was found to have an insignificant influence on people's intentions to take up Covid-19 vaccinations. CONCLUSION: Participants' intentions to take up Covid-19 vaccinations was influenced mainly by their attitudes and perceptions of Covid-19 vaccines in general, which strongly confirms the importance of various dimensions (perceived benefits, trust, social norms) of Covid-19 vaccines in cultivating Covid-19 vaccination acceptance among participants'. SN - 1878-0334 UR - https://www.unboundmedicine.com/medline/citation/34000711/Using_structural_equation_modeling_to_predict_Indian_people's_attitudes_and_intentions_towards_COVID_19_vaccination_ DB - PRIME DP - Unbound Medicine ER -