COVID-19 vaccine literacy: A scoping review

Abstract

To address vaccine hesitancy, specific self-rated tools have been developed to assess vaccine literacy (VL) related to COVID-19, including additional variables, such as beliefs, behavior, and willingness to be vaccinated. To explore the recent literature a search was performed selecting articles published between January 2020 and October 2022: 26 papers were identified using these tools in the context of COVID-19. Descriptive analysis showed that the levels of VL observed in the studies were generally in agreement, with functional VL score often lower than the interactive-critical dimension, as if the latter was stimulated by the COVID-19-related infodemic. Factors associated with VL included vaccination status, age, educational level, and, possibly, gender. Effective communication based on VL when promoting vaccination is critical to sustaining immunization against COVID-19 and other communicable diseases. The VL scales developed to date have shown good consistency. However, further research is needed to improve these tools and develop new ones.

Keywords: COVID-19; Vaccine literacy; health literacy; vaccine hesitancy; vaccine uptake.

Figure 1.

Preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram.

Figure 2.

Functional and interactive-critical VL score means (CI 95%), and lower tertile distribution of 22 study populations using COVID-19-VLS or HLVa, and respective references; lower tertiles bounds (functional = 2.64, interactive-critical = 2.78,) are represented by dotted lines; arbitrary cutoff value is set at 2.50 (solid lines). Authors’ names and study populations are numbered and listed alphabetically on the left side of the graph; markers dimension reflects variability in the sample size of the studies.

Figure 3.

Spearman’s correlation (CI 95%) between functional and interactive-critical VL (refer to Figure 2 for study numbering identification).

Figure 4.

Weighted linear regression (95% CI) between age and functional VL, and between age and interactive-critical VL; for studies where average values were not reported, age was estimated from the age class distribution - Refer to Figure 2 for study numbering identification.

Figure 5.

VL factor loading, using PCA extraction method, in populations from Itay (Biasio et al., 2020), Japan (Takahashi et al. 2022), Croatia (Gusar et al. 2021), and Thailand (Maneesriwongul et al. 2002, unpublished data kindly provided by the Author).