ArticleVaccines2023
Deepening Our Understanding of COVID-19 Vaccine Decision-Making amongst Healthcare Workers in Southwest Virginia, USA Using Exploratory and Confirmatory Factor Analysis.
Article in Vaccines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
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Who cites it
3 citing papers in PubMed.
- Article
- Modelling the interplay between responsive individual vaccination decisions and the spread of SARS-CoV-2.Epidemics · 2025Article
- The impact of vaccine hesitancy on psychological impairment among healthcare workers in a Total Worker HealthFrontiers in public health · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Vaccine hesitancy amongst healthcare workers (HCWs) has been a major challenge throughout the COVID-19 pandemic. While many studies have identified HCW characteristics and specific attitudes associated with COVID-19 vaccine hesitancy, researchers are still working towards developing a holistic understanding of the psychological constructs that influence COVID-19 vaccine decision-making in this population. Between 15 March and 29 March 2021, we distributed an online survey assessing individual characteristics and vaccine-related perceptions to employees of a not-for-profit healthcare system in Southwest Virginia (N = 2459). We then performed exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to describe patterns of vaccine-related thought amongst HCWs and identify latent psychometric constructs involved in vaccine decision-making. The goodness of model fit was assessed using the Tucker-Lewis Index (TLI), the Comparative Fit Index (CFI), and the Root Mean Square Error of Approximation (RMSEA). Internal consistency and reliability of each factor were assessed using Cronbach's alpha. EFA identified four latent psychometric constructs: Lack of trust in the COVID-19 vaccine; Anti-science sentiment; Adverse side-effects; and Situational risk assessment. The goodness of EFA model fit was adequate (TLI > 0.90, RMSEA ≤ 0.08) with acceptable internal consistency and reliability for three of four factors (Cronbach's alpha > 0.70). The CFA model also had adequate goodness of fit (CFI > 0.90, RMSEA ≤ 0.08). We believe the psychometric constructs identified in this study can provide a useful framework for interventions to improve vaccine uptake amongst this critical population.
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Registered trials
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