Dataset Information

Psychological characteristics and the mediating role of the 5C Model in explaining students' COVID-19 vaccination intention.

ABSTRACT: To achieve herd immunity against COVID-19, it is crucial to know the drivers of vaccination intention and, thereby, vaccination. As the determinants of vaccination differ across vaccines, target groups and contexts, we investigate COVID-19 vaccination intention using data from university students from three countries, the Netherlands, Belgium and Portugal. We investigate the psychological drivers of vaccination intention using the 5C model as mediator. This model includes five antecedents of vaccination: Confidence, Complacency, Constraints, Calculation and Collective Responsibility. First, we show that the majority of students have a positive propensity toward getting vaccinated against COVID-19, though only 41% of students are completely acceptant. Second, using the 5C model, we show that 'Confidence' (β = 0.33, SE = 03, p < .001) and 'Collective Responsibility' (β = 0.35, SE = 04, p < .001) are most strongly related to students' COVID-19 vaccination intention. Using mediation analyses, we show that the perceived risk and effectiveness of the vaccine as well as trust in the government and health authorities indirectly relate to vaccination intention through 'Confidence'. The perceived risk of COVID-19 for one's social circle and altruism, the need to belong and psychopathy traits indirectly relate to vaccination intention through 'Collective Responsibility'. Hence, targeting the psychological characteristics associated with 'Confidence' and 'Collective Responsibility' can improve the effectiveness of vaccination campaigns among students.

SUBMITTER: Wismans A

PROVIDER: S-EPMC8357093 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Psychological characteristics and the mediating role of the 5C Model in explaining students' COVID-19 vaccination intention.

Wismans Annelot A Thurik Roy R Baptista Rui R Dejardin Marcus M Janssen Frank F Franken Ingmar I

PloS one 20210811 8

To achieve herd immunity against COVID-19, it is crucial to know the drivers of vaccination intention and, thereby, vaccination. As the determinants of vaccination differ across vaccines, target groups and contexts, we investigate COVID-19 vaccination intention using data from university students from three countries, the Netherlands, Belgium and Portugal. We investigate the psychological drivers of vaccination intention using the 5C model as mediator. This model includes five antecedents of vac ...[more]

PMID: 34379648

Similar Datasets

Project description:BackgroundMonitoring the reasons why a considerable number of people do not receive recommended vaccinations allows identification of important trends over time, and designing and evaluating strategies to address vaccine hesitancy and increase vaccine uptake. Existing validated measures assessing vaccine hesitancy focus primarily on confidence in vaccines and the system that delivers them. However, empirical and theoretical work has stated that complacency (not perceiving diseases as high risk), constraints (structural and psychological barriers), calculation (engagement in extensive information searching), and aspects pertaining to collective responsibility (willingness to protect others) also play a role in explaining vaccination behavior. The objective was therefore to develop a validated measure of these 5C psychological antecedents of vaccination.Methods and findingsThree cross-sectional studies were conducted. Study 1 uses factor analysis to develop an initial scale and assesses the sub-scales' convergent, discriminant, and concurrent validity (N = 1,445, two German convenience-samples). In Study 2, a sample representative regarding age and gender for the German population (N = 1,003) completed the measure for vaccination in general and for specific vaccinations to assess the potential need for a vaccine-specific wording of items. Study 3 compared the novel scale's performance with six existing measures of vaccine hesitancy (N = 350, US convenience-sample). As an outcome, a long (15-item) and short (5-item) 5C scale were developed as reliable and valid indicators of confidence, complacency, constraints, calculation, and collective responsibility. The 5C sub-scales correlated with relevant psychological concepts, such as attitude (confidence), perceived personal health status and invulnerability (complacency), self-control (constraints), preference for deliberation (calculation), and communal orientation (collective responsibility), among others. The new scale provided similar results when formulated in a general vs. vaccine-specific way (Study 2). In a comparison of seven measures the 5C scale was constantly among the scales that explained the highest amounts of variance in analyses predicting single vaccinations (between 20% and 40%; Study 3). The present studies are limited to the concurrent validity of the scales.ConclusionsThe 5C scale provides a novel tool to monitor psychological antecedents of vaccination and facilitates diagnosis, intervention design and evaluation. Its short version is suitable for field settings and regular global monitoring of relevant antecedents of vaccination.

Project description:BackgroundThe availability of various types of COVID-19 vaccines and diverse characteristics of the vaccines present a dilemma in vaccination choices, which may result in individuals refusing a particular COVID-19 vaccine offered, hence presenting a threat to immunisation coverage and reaching herd immunity. The study aimed to assess global COVID-19 vaccination intention, vaccine characteristics influencing vaccination acceptance and desirable vaccine characteristics influencing the choice of vaccines.MethodsAn anonymous cross-sectional survey was conducted between 4 January and 5 March 2021 in 17 countries worldwide. Proportions and the corresponding 95% confidence intervals (CI) of COVID-19 vaccine acceptance and vaccine characteristics influencing vaccination acceptance were generated and compared across countries and regions. Multivariable logistic regression analysis was used to determine the factors associated with COVID-19 vaccine hesitancy.ResultsOf the 19,714 responses received, 90.4% (95% CI 81.8-95.3) reported likely or extremely likely to receive COVID-19 vaccine. A high proportion of likely or extremely likely to receive the COVID-19 vaccine was reported in Australia (96.4%), China (95.3%) and Norway (95.3%), while a high proportion reported being unlikely or extremely unlikely to receive the vaccine in Japan (34.6%), the U.S. (29.4%) and Iran (27.9%). Males, those with a lower educational level and those of older age expressed a higher level of COVID-19 vaccine hesitancy. Less than two-thirds (59.7%; 95% CI 58.4-61.0) reported only being willing to accept a vaccine with an effectiveness of more than 90%, and 74.5% (95% CI 73.4-75.5) said they would accept a COVID-19 vaccine with minor adverse reactions. A total of 21.0% (95% CI 20.0-22.0) reported not accepting an mRNA vaccine and 51.8% (95% CI 50.3-53.1) reported that they would only accept a COVID-19 vaccine from a specific country-of-origin. Countries from the Southeast Asia region reported the highest proportion of not accepting mRNA technology. The highest proportion from Europe and the Americas would only accept a vaccine produced by certain countries. The foremost important vaccine characteristic influencing vaccine choice is adverse reactions (40.6%; 95% CI 39.3-41.9) of a vaccine and effectiveness threshold (35.1%; 95% CI 33.9-36.4).ConclusionsThe inter-regional and individual country disparities in COVID-19 vaccine hesitancy highlight the importance of designing an efficient plan for the delivery of interventions dynamically tailored to the local population.

Dataset Information

Psychological characteristics and the mediating role of the 5C Model in explaining students' COVID-19 vaccination intention.

Publications

Psychological characteristics and the mediating role of the 5C Model in explaining students' COVID-19 vaccination intention.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets