ArticleVaccines2023
Exploration into the Influencing Factors for the Intention of the Public to Vaccinate against Infectious Diseases Based on the Theory of Planned Behavior-Example of the COVID-19 Vaccine.
Article in Vaccines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Physicians' Intentions to Recommend Influenza Vaccine: A Multi-Centered Hospital-Based Study Using the Theory of Planned Behavior in Bangladesh.International journal of environmental research and public health · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesThe coronavirus disease 2019 (COVID-19) was applied as an example, and the Theory of Planned Behavior (TPB) was used as a conceptual model. This study aimed to explore the impact of subjective norms (SNs), attitude towards the behavior (ATT), and perceived behavioral control (PBC) on the intention of the public for regular vaccination during COVID-19. The outcomes can provide certain recommendations for relevant policymakers in developing targeted health education intervention programs in the event of similar events.
methodsAn online survey was performed between 17 April and 14 May 2021, via the online survey platform "WENJUANXING". The multistage stratified cluster sampling was employed, and 2098 participants (1114 males; 53.10%) with a mean age of 31.22 years (SD = 8.29) completed the survey. The survey covered the factors influencing the public's intention to receive future regular vaccinations during COVID-19 based on TPB. The effects of different variables on the public's vaccination intention were analyzed using hierarchical stepwise regression.
resultsThe public's intention to receive the COVID-19 vaccine (i.e., behavioral intention) in the future was taken as the dependent variable. Gender, age, marital status, education level, per capita monthly household income, vaccine-related knowledge, whether the COVID-19 vaccine was received, subjective norms (SNs), attitude towards the behavior (ATT), and perceived behavioral control (PBC) were used as independent variables. In this way, a hierarchical stepwise multiple regression model was developed. It can be seen from the final model that gender, age, vaccine-related knowledge, vaccination, attitude, SNs, and PBC were all influential factors in the public's intention to get vaccinated in the future, with R
conclusionTPB explains the intention of the public to receive future vaccinations to a large extent, and ATT and SNs are the most important influencing factors. It is suggested that vaccine intervention programs be developed to enhance public awareness and acceptance of vaccination. This can be achieved in three aspects, namely, improving the ATT of the public, SNs, and PBC. Furthermore, the influence of gender, age, vaccine knowledge, and previous vaccination behavior on vaccination intention should be taken into account.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.