Evidence map›Paper›PMID 34140015›Full record

ArticleBMC public health2021

The protection motivation theory for predict intention of COVID-19 vaccination in Iran: a structural equation modeling approach.

Alireza Ansari-Moghaddam, Maryam Seraji, Zahra Sharafi, Mahdi Mohammadi, Hassan Okati-Aliabad

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Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 2 pooled it
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

39 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Implications for COVID-19 vaccine uptake: A systematic review.Journal of infection and public health · 2023
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Alireza Ansari-MoghaddamHealth Promotion Research Center, Zahedan University of Medical Sciences, Zahedan, Iran.
Maryam SerajiHealth Promotion Research Center, Zahedan University of Medical Sciences, Zahedan, Iran.
Zahra SharafiHealth Promotion Research Center, Zahedan University of Medical Sciences, Zahedan, Iran.
Mahdi MohammadiHealth Promotion Research Center, Zahedan University of Medical Sciences, Zahedan, Iran.
Hassan Okati-AliabadHealth Promotion Research Center, Zahedan University of Medical Sciences, Zahedan, Iran. dr.okati@zaums.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany efforts are being made around the world to discover the vaccine against COVID-19. After discovering the vaccine, its acceptance by individuals is a fundamental issue for disease control. This study aimed to examine COVID-19 vaccination intention determinants based on the protection motivation theory (PMT).

methodsWe conducted a cross-sectional study in the Iranian adult population and surveyed 256 study participants from the first to the 30th of June 2020 with a web-based self-administered questionnaire. We used Structural Equation Modeling (SEM) to investigate the interrelationship between COVID-19 vaccination intention and perceived susceptibility, perceived severity, perceived self-efficacy, and perceived response efficacy.

resultsSEM showed that perceived severity to COVID-19 (β = .17, p < .001), perceived self-efficacy about receiving the COVID-19 vaccine (β = .26, p < .001), and the perceived response efficacy of the COVID-19 vaccine (β = .70, p < .001) were significant predictors of vaccination intention. PMT accounted for 61.5% of the variance in intention to COVID-19 vaccination, and perceived response efficacy was the strongest predictor of COVID-19 vaccination intention.

conclusionsThis study found the PMT constructs are useful in predicting COVID-19 vaccination intention. Programs designed to increase the vaccination rate after discovering the COVID-19 vaccine can include interventions on the severity of the COVID-19, the self-efficacy of individuals receiving the vaccine, and the effectiveness of the vaccine in preventing infection.

Indexed as

COVID-19COVID-19 VaccinesAdultCross-Sectional StudiesHumansIntentionIranLatent Class AnalysisMotivationSARS-CoV-2Surveys and QuestionnairesVaccinationCOVID-19 VaccinesCOVID-19IntentionIranStructural equation modelingVaccination

Identifiers

PMID34140015
PMCPMC8209774

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.