Development of Tools to Assess Vaccine Literacy: A Scoping Review and Future Perspectives

1. Introduction

2. Materials and Methods

3. Results

3.1. Review update

In addition to those selected in our previous review [19], we found a total of 367 papers on PubMed and the other databases, published from December 1st 2022 until November 30th 2023 out of which we selected those where VL was assessed using specific tools, as described in Methods. Of the 246 papers screened by title and abstract, 17 publications were selected for this review, as shown in Figure 1 (PRISMA diagram) and summarized in Table 1. Other publications found in the screened literature were devoted to the use of HL assessment instruments, which were analyzed, and some commented, but were not considered for review, as not specifically dedicated to VL.

Table 1. Selected studies published in 2023 using VL tools.

Table 1. Selected studies published in 2023 using VL tools.

Author, Ref #, Year	Title	Country, Study population	Subjects N, Gender, mean age	Study design, period	Determinants In addition to age, gender, education	VL Tools, score	Mediators	Dependant Variable(s)	Main findings: Bold= exploring mediation Italic= VL & VH pos.association
Akova et al. [28] 2023	Covid-19 Vaccine Literacy and Vaccine Hesitancy Level Among Healthcare Professionals in Turkey, Their Relationship and Influencing Factors: A cross-Sectional Study	Turkey, HCWs	1,111, females 59.6%, mean age 34.3 ± 9.2 years	online, cross-sectional,15.02.2022-15.03.2023	Occupation, working time, area of residence, presence of chronic disease	Covid-19-VLS, FUVL 2.6 ± 0.7 ICVL 3.0 ± 0.6	VH	Opinions on coronavirus and Covid-19 vaccines	High VL decreased VH
Alyahya [29] et al. 2023	The Social Attitudes Towards the Booster Dose of the Covid-19 Vaccine and the Associated Factors Among Residents of Riyadh, Saudi Arabia	Saudi Arabia, residents 16+ years old	435, females 72.6%, mean age 38.1 ± 13.6 years	online, cross-sectional, from 22.08.2022 to 25.08.2022	no association investigated	HLVa- functional 80.3% > 2 critical 77.4% >2 communicative 78.3% >2	none investigated	VH	VL higher in non hesitants, not statistically significant
Bektas et al. [30] 2023	The effects of parents’ vaccine hesitancy and Covid-19 vaccine literacy on attitudes toward vaccinating their children during the pandemic	Turkey, parents of children aged 0–18	199 female 87.9% mean age 38.74 ± 6.39 years	cross-sectional online	HCWs, income, number of children and age, children & parentsì Covid disease & vaccination status	Covid-19-VLS Score not reported	none investigated	parents’ attitudes toward getting children vaccinated, VH Scale 10 items, 2sub dimensions (Larson)	VH Scale alone significantly affected attitudes during the pandemic. VL did not affect the parents’ attitudes toward vaccinating children
Bellomo et al. [31] 2023	Who chooses alternative sources of information about childhood vaccinations? A cross-sectional study	Italy, parents	2,301, females 81%, mean age 47.7 ± 6.4 years	online, cross-sectional, from June to October 2021	no association investigated	HLVa-IT, functional 80.3% >2 critical 77.4% >2 communicative 78.3% >2	none investigated	use of alternative information sources	parents with lower HLVa score more inclined to use alternative sources of information
Collini et al. [1] 2023	Does Vaccine Confidence Mediate the Relationship between Vaccine Literacy and Influenza Vaccination? Exploring Determinants of Vaccination among Staff Members of Nursing Homes in Tuscany, Italy, during the Covid-19 Pandemic	Italy, Nursing Homes Staff	1,794, females 86.3%, median age 46	online, cros sectional, August-September 2020	Professional qualification, Concomitant diseases	HLVa Median Total 3.1 Finctional 1.8 Inter-critical 3.2	Vaccine confidence index (VCI)	Intention to be vaccinated against flu	Vaccine confidence completely mediated the effect between ICVL and flu vaccine intention
Han et al. [32] 2023	Factors Influencing Human Papillomavirus Vaccination Among Asian Immigrant College Students During the Covid-19 Pandemic	USA, college students	133, females 69.9%, mean age 25.12 ± 5.38 years	cross-sectional from June through August 2021	no association investigated	HPV VL Scale,3.31 ± 1.83	11-item HPVattitude scale; 4-item HPVvaccine norms scale; 3-item HPV Self-efficacy scale; HPV VH and vaccine intention	HPV Vaccination	Vaccine subjective norms and literacy directly affected vaccination intention. Vaccine attitudes and self-efficacy directly and negatively affected VH.
Iskender et al. [33] 2023	The effect of Covid-19 vaccine literacy on attitudes towards Covid-19 vaccine among university students	Turkey, students	2,384, female 1,574, mean age 21.77 years	cross-sectional survey online Sep-Oct 2021	Socioeconomic level parents’ education, Covid diagnosis	Covid-19 VLS FUVL 2.6 ICVL 2.87 (calculated from the summative score)	none investigated	Attitudes towards Covid-19-VLS (nine items, two subscales (positive attitude and negative attitude)	Low levels of correlation between VL and attitudes
Kerkez et al. [34] 2023	An assessment on the knowledge and attitudes of university students concerning adult immunization and Covid-19 vaccine in Turkey	Turkey. students	307 females 52.4 %, mean age 20.4 ± 0.56 years	cross-sectional from June through August 2021	no association investigated	Covid-19 VLS, FUVL 2.40 ± 0.71 ICVL 2.93 ± 0.81	none investigated	Attitudes toward the Covid-19 vaccine scale; Knowledge for adult vaccines	Significant difference between level of knowledge about adult immunization and mean VL scores
Lu et al. [35] 2023	Lessons learned from Covid-19 vaccination implementation: How psychological antecedents of vaccinations mediate the relationship between vaccine literacy and vaccine hesitancy	China, General population	1,015, female 53.3%,	Apr 2021	Income, Place od residence, Marital status	Covid-19 VLS Score range 1-5, Low hesitant FUVL 3.8 ICVL 3.56 High hesitant FUVL 3.6 ICVL 3.24	‘‘3Cs’’ psycholo= gical antecedents of vaccination	Covid-19 vaccine uptake 11-point self-reported scale on ‘3Cs’; 10-point VH visual scale on non- vaccinated particiipants	‘‘3Cs’’ psychological antecedents were significant mediators between VL (mainly ICVL) and VH; Time-to-event analysis confirmed the role of VH in delaying vaccination
Maneesriwongul et al. [36] 2023	Parental Vaccine Literacy: Attitudes towards the Covid-19 Vaccines and Intention to Vaccinate Their Children Aged 5–11 Years against Covid-19 in Thailand	Thailand, parents	542, female 83.2%, 60.9% between ages 36 and 45 years	online cross-sectional study, from Jan to Feb 2022	income sufficiency, occupation, child’s age, underlying diseases, parents’ vaccinat status	Covid-19 VLS FUVL 2.67 ±0.69 ICVL 3.31 ±0.51	parents’ attitudes towards Covid-19 vaccine (10 questions)	parents’ intention to have children vaccinated against Covid-19	Factors influencing intention to vaccinate: child age, parents’ education, ICVL, positive attitudes toward vaccine
Maneesriwongul et al. [37] 2023	Parental Hesitancy on Covid-19 Vaccination for Children Under Five Years in Thailand: Role of Attitudes and Vaccine Literacy	Thailand, parents	455, female 83.7%, 55.8 % < 35 years	online cross-sectional study	income sufficiency, occupation, child’s age, underlying diseases, parents’ vaccination status	Covid-19 VLS FUVLl 2.8 ±0.71 ICVL 3.3 ±0.56	parents’ attitudes towards Covid-19 vaccine (10 questions)	parents’ intention to have children vaccinated against Covid-19	Factors influencing intention to vaccinate: parents’ age > 35, education, income, ICVL, positive attitudes toward vaccine
Montagni et al. [38] 2022	Measuring Digital Vaccine Literacy: Development and Psychometric Assessment of the Digital Vaccine Literacy Scale	France, adults	848, females 73.1%, mean age 29.9 ± 12.3 years	cross sectional validation study	field of study	Digital vaccine literacy scale Score 19.5 ± 2.8	none investigated	flu vaccination, source of vaccine-related information	Digital Vaccine Literacy tool showed good psychometric proprieties
Shon et al. [4] 2023	Effects of Vaccine Literacy, Health Beliefs, and Flu Vaccination on Perceived Physical Health Status among Under/Graduate Students	USA, Students	382, females 73.8%, mean age 22.37 ± 5.97 years	Web-based survey, September 2019 to March 2020	Family income, parents’ education, Insurance, Race	VL: single question on flu vaccine, nominal scale	Health Beliefs (HBM scale, 16 questions)	Flu vaccine uptake (seelf reported)	Results showed direct effect of VL on flu vaccine uptake, and mediating effects of health beliefs (benefit, severity and susceptibility) between VL and vaccination
Us et al. [39] 2023	Turkish parents’ attitudes towards Covid-19 vaccination of their children aged 12-17 years: A cross-sectional study: parents’ attitudes to Covid-19 vaccination	Turkey, parents	259 female 81.9%, mean age 41.93 ± 5.68 years	online cross-sectional	no association was investigated	Covid-19-VLS Total 2.61±0.55, FUVL 2.64±0.83 ICVL 2.60±0.71	Perception of Control of Covid Scale, Perception of Causes of Covid-19, Attitudes Towards the Covid-19 Vaccine Scale	children vaccination status	VL increased, both the reduction in misconceptions and the positive effect on families’ vaccination attitudes
Yang et al. [40] 2023	Assessing vaccine literacy and exploring its association with vaccine hesitancy: A validation of the vaccine literacy scale in China	China, adultd	12,586, females 43.9%, mean age 31.56 ± 9.12 years	online, cross-sectional validation study, May 2022 to June 2022	no association investigated	HLVa range 1-5 functional 3.23 ± 1.24, interactive 4.03 ± 0.81, critical 4.03 ± 0.84	VH	Vaccine acceptance	People who scored lower on the functional scale were more likely to be hesitant in all vaccine acceptance subgroups
Yilmazel [41] et al. 2023	Attitudes towards Covid-19 vaccination, vaccine hesitancy and vaccine literacy among unvaccinated young adults	Turkey, adults	860, females 67.7%, mean age 22.9 ± 3.3 years	cross-sectional January to April 2021	no association investigated	Covid-19-VLS 27.3 ± 6.5 (summative score)	None investigatd	vaccine hesitancy scale in pandemics, Attitudes towards Covid-19 vaccine	Use of social media perday, VL and Covid-19 vaccine attitude were effective factors on pandemic VH
Yorulmaz et al. [42] 2023	A vaccine literacy scale for childhood vaccines: Turkish validity and reliability vaccine literacy scale	Turkey, parents	285, females % not reported, mean age 34.7 ± 6.6 years	online, cross-sectional validation study, From 25.05.2022 to 25.06.2022	no association investigated	Vaccine Literacy Scale (Aharon et al. 2017)	None investigated	Health Literacy Scale (HLS-14)	There was a negative correlation between the VLS and HLS-14

Diverse populations were included in the 17 papers selected in the present review (Table 1). Samples’ size varied from 133 to 12,586. Participants were distributed in different classes of age, but they were mostly young female adults. Nine publications out of the 17 selected for the present review confirmed the association between VL and vaccine acceptance or intention to be vaccinated (Table 1).

The scales employed in the selected articles were mainly modified versions of those used to measure HL chronic patients [43], and founded on the three-level HL model proposed by Nutbeam [44], including functional, interactive (or communicative) and critical levels. The HLVa-IT tool (Vaccine HL for adults in Italian) [45], later translated into English (HLVa) aims at measuring VL levels associated with routine vaccination of adulthood, including five questions assessing functional VL (FUVL), in addition to five and four items for interactive and critical skills, respectively. The functional sub-scale engages the semantic system, whereas the interactive and critical subscales regard more advanced cognitive efforts. The interactive-critical component of literacy may include also abilities regarding eHealth and AI-based approaches. A measure with the same construct has also been used in parents of children [46,47]. In all these tools, answers are rated on a forced 4-point Likert scale: a mean (± SD) score is calculated (range 1 to 4), treated as continuous, a higher value corresponding to a higher VL level. The validation process of HLVa in different languages is described elsewhere [19]. A study of the tool translated and adapted into Chinese has been published recently [40].

Based on the same construct, a measure was also developed and largely used to assess specifically Covid-19 VL (Covid-19-VLS), where the interactive and critical subscales have been merged and identified as interactive-critical VL (ICVL) and the total number of questions reduced from 14 to 12, to lessen redundancy. Covid-19-VLS also includes items to assess other variables (mediating factors, like beliefs and attitudes), and behaviors, like vaccine Covid-19 vaccine intention and flu vaccine acceptance and self-reported uptake [19,48]. Two versions of this tool were used, before and after the SARS-CoV-2 vaccines authorization and availability. Both measures are reported in Appendix A During the pandemic, other tools were developed that utilized the HLVa construct. However, some of these instruments had a reduced number of items or employed different scoring methods than the original instructions. As a result, making descriptive comparisons became challenging [15].

3.4. Theoretical Framework

The logical framework developed depicts the relationship between knowledge, motivation, and competencies incorporating them along with functional, interactive, and critical VL levels. We considered moderators (proximal and distal determinants), and possible mediators (i.e., variables that explain the reasons and mechanisms behind outcomes). These variables include communication, knowledge, beliefs, attitudes, behaviors, self-efficacy and competencies (Figure 2).

Figure 2. VL theoretical framework identifying constructs, their influence, and measures. VL is located between background (moderators) and mediators and partially overlaps these last, this explaining its mediating and mediated role toward attitudes, behaviors and health outcomes. Adapted from Squiers’ Health Literacy Skills Framework [54]) and Paasche-Orlow [55]. HBM= Health Belief Model [4,56], TPB= Theory of Planned Behavior [57], PMT= Protection Motivation Theor [58], Self-efficacy Scale [59].

Figure 2. VL theoretical framework identifying constructs, their influence, and measures. VL is located between background (moderators) and mediators and partially overlaps these last, this explaining its mediating and mediated role toward attitudes, behaviors and health outcomes. Adapted from Squiers’ Health Literacy Skills Framework [54]) and Paasche-Orlow [55]. HBM= Health Belief Model [4,56], TPB= Theory of Planned Behavior [57], PMT= Protection Motivation Theor [58], Self-efficacy Scale [59].

4. Discussion

4.3. Future perspectives

As for HL [77], new methods for VL measurement should explicitly refer to the domains outlined in relevant conceptual frameworks. In addition, to address the limitations of current measures, and align them as much as possible with the most recent definitions of VL, the construct of new instruments should contain and integrate items related to all the three components (motivation, knowledge, competencies), thus reducing the risk of underestimating latent factors. We attempted to determine an effective approach for incorporating them along with the three VL levels (functional, interactive, and critical) within the Health Literacy Skills Framework (HLSF), as illustrated in Figure 2. The framework, proposed by Squiers [54] was used for our analysis together with the Paasche-Orlow and Wolf model [55]. We considered moderators (proximal and distal determinants), and possible mediators (i.e., variables that explain the reasons and mechanisms behind outcomes). These variables include communication, knowledge, beliefs, attitudes, behaviors, self-efficacy and competencies, incorporating concepts from various psychological theories, such as, among others, the Health Belief Model (HBM) [4], and the Protection Motivation Theory (PMT) [57]. We referred to tools designed for assessing these variables, relevant in the vaccination field, also taking into account the mentioned VH models (Table 2). Based on this, we have endeavored to outline potential new VL tools.

Motivation: there are different definitions for motivation [78]; according to the American Psychological Association) [79], motivation refers to “a person’s willingness to exert physical or mental effort in pursuit of a goal or outcome”. It is a dynamic concept, resulting of internal and external inputs that lead to decisions and behaviors [78]. Motivation encompasses attitudes, which includes beliefs, emotions, and evaluations. In clinical settings there are various tools for measuring motivation [78]. Considering the consistency of the results reported so far from studies using HLVa and derived measures (Covid-19-VLS), the VL scales entailed in these tools appear suitable for assessing motivation also for future research, in particular in the interactive-critical subscale. Redundancy of questions identified during the validation process was addressed through factor analysis [80] reducing the number of questions from 14 to 12 overall (four for FUVL and eight ICVL) [21]. As reported above, additional analyses can be performed to further reduce the number of questions to lessen as much as possible their total number and facilitate their filling in. It is also possible to design VL tools to assess motivation by adapting items from the PMT, which explains how people respond to fear-evoking or threatening messages, or from the HBM, which explains and predicts health behaviors by examining the attitudes and beliefs, as previously demonstrated by others [81]. The mediating role of beliefs, evaluated by the HBM, in the relationship between VL and flu vaccination has been studied in one of the selected publications [4]. Noteworthy, the papers on behavorial change models cited in Table 2 represent just examples of a very extensive literature.

Knowledge: is the state of being familiar with something or aware of its existence, usually resulting from experience or study (i.e., information learned) [79]. It is part of the conceptual VL definition and a key mediating component in the VL framework. Procedural knowledge, which involves understanding how to carry out specific tasks or actions, serves as the basis for ICVL skills and fluid cognitive abilities, whereas crystallized abilities, including generalized knowledge and vocabulary, are typically more associated with functional skills, particularly in the elderly population [74]. Understanding the relation of VL to basic cognitive abilities is important since research has shown that both general intellectual abilities and literacy are related to health [82]. While IQ tests can provide a broad assessment of cognitive abilities, adding psychological assessments to the tools designed for the general population can be challenging. Evaluating the level of crystallized knowledge through a vaccine quiz can offer a straightforward, relevant, and efficient performance-based method. This approach has been previously employed for validating the theoretical construct of HLVa-IT, where the quiz was administered together with the VL questionnaire [80]. In addition, vaccines quizzes can be structured to objectively evaluate the individual’s functional reading and understanding skills, when administered through face-to-face interviews or by paper-and-pencil. Regarding online surveys, there is an inherent risk that individuals may seek assistance or refer to external sources, which can potentially inflate their scores on assessments. However, measures can be taken to reduce this risk, such as underlining the anonymity of the survey, or by designing the questionnaire in a linear, one-directional flow where respondents can only move forward, and by including control or confirmation questions in the final page.

The content of the scales can be adapted over time according to the vaccines that will become available in the future, although addressing the general knowledge about vaccination and on the most common routine vaccines (D, T, Polio, Influenza) would reduce disparities. Items can be selected from vaccine scales available in the literature [83], and online resources provided by academic [84] and international institutions [85]. Common questions on the knowledge of vaccines and diseases should be identified and used for comparability purposes, while taking into account cultural and socio-economic differences between populations.

Table 2. - Psychological theories explaining behaviors toward vaccination and related assessment measures, usually rated through odd-points scales. Different examples of items reported in the literature (for influenza, Covid-19, and HPV) are proposed for each component of the models, to be possibly used or adapted for building new VL tools to explore motivation and competencies, while knowledge can be assessed by performance-based measures, administering standardized stimuli.

Table 2. - Psychological theories explaining behaviors toward vaccination and related assessment measures, usually rated through odd-points scales. Different examples of items reported in the literature (for influenza, Covid-19, and HPV) are proposed for each component of the models, to be possibly used or adapted for building new VL tools to explore motivation and competencies, while knowledge can be assessed by performance-based measures, administering standardized stimuli.

Psychological Frameworks / Models
Self-efficacy theory VacSE Włodarczyk [59] explains how individual’s belief in their own abilities drives to successfully perform tasks		Health Belief Model HBM Abraham [86],Shon [4] explains and predict health behaviors by examining the attitudes and beliefs		Theory of Planned Behavior TPB Ajzen [57], Catalano [87] explains how intention to engage in a behavior is influenced by the attitude toward that behavior		Protection Motivation Theory PMT Marikyan [27], Kowalski [58] explains how people respond to fear-evoking or threatening messages		‘3Cs’ and 5Cs McDonald [13],Betsch [15] Lu [35] explains respectively 3 and 5 key determinants that contribute to VH
__________________________________________ Models’ items and vaccine related examples of statements_______________________________________________
To what extent are you sure that you will vaccinate in the current season even if…	“.… you have to pay in full or in part for the influenza vaccination”	perceived severity	“I am afraid the flu will make me very sick”	attitudes	I think getting all three doses of the HPV vaccine within 12 months is …” very bad – very good, extremely harmful – extremely beneficial, unnecessary – necessary.	perceived severity	“The negative impact of Covid-19 is very severe”	confidence (see also §)	“Generally, I trust the information released by the state on a Covid-19 vaccine”
	“… friends or the media tell you that this flu vaccine is harmful or unnecessary, or that it is does not give a 100% guarantee”	perceived benefits	“Flu vaccinations are an effective protection against the flu”	subjective norms	“Most people who are important to me think that I should get all three doses of the HPV vaccine in the next 12 months”	perceived susceptibility/ vulnerability	“If I don’t get the Covid-19 vaccination, I am at risk of catching the Covid-19 virus”	complacency	“I’m healthy and resistant to infection, so I don’t have to get the Covid-19 vaccine”
	“… you will need to find out where and how to get the flu vaccine”	perceived barriers	“Flu vaccination has unpleasant side-effects”	perceived behavioral control	“If I wanted to, I am sure I could get all three doses of the HPV vaccine in the next 12 months”	maladaptive response rewards MMR	“If I do not get a Covid-19 vaccine, I will not have to spend time and money getting vaccinated”	convenience	“I don’t like going to medical facilities, so I’m reluctant to get the Covid-19 vaccine”
	“.… you will be overwhelmed by the excess of other things and responsibilities”	perceivedsusceptibility	“I have an increased risk of falling ill with flu”	behavioral intention	“I plan to get all three doses of the HPV vaccine in the next 12 months”	outcome efficaciousness	“I’m sure that having a Covid-19 vaccine would be effective in reducing my personal risk of contracting the virus”	calculation	“When I think about getting vaccinated, I weigh benefits and risks to make the best decision possible”
	.”… vaccination will have to be rescheduled, for example due to a cold”					self-efficacy	“I’d be able to get a Covid-19 vaccine if I wanted to”	collectiveresponsibility	“When everyone is vaccinated, I don’t have to get vaccinated, too”
	“.... it will be necessary to make further attempts to make an appointment ,,,,during the pandemic”					response cost	“Being vaccinated against Covid-19 is painful”

§ = there are several scales to assess VH [15]; a frequently adopted measure is VCI [88,89] - Flu example [1,66] assessed on 4-point Likert scale - VCI = [ (A1+A2+A3+A4) / 4] / [(B1+B2+B3+B4) / 4]. (A1) Flu is a serious illness - (A2) Flu vaccine is effective - (A3) HCWs must get vaccinated - (A4) By getting vaccinated I can protect people close to me; (B1) It is better to contract flu than to get the vaccination - (B2) Flu vaccines have serious side effects - (B3) Vaccine can cause flu - (B4) Opposed to flu vaccinaton.

Competencies: can be viewed as a set of knowledge, skills, capabilities (abilities), and behaviors that contribute to the individual’s performance [90]. Given that knowledge on vaccines can be evaluated as described above, and that skills and abilities can be assessed through the existing VL scales (such as the interactive-critical sub-scale of HLVa), it is suggested to complete the assessment of competencies by incorporating standardized items that evaluate vaccination behavior (such as vaccines received), together with the educational level of respondents. This suggestion is based on the general understanding that individuals with higher education levels are more likely to adopt healthy behaviors [91]. Education plays a crucial role in providing individuals with knowledge and skills required to develop competencies in various domains such as health, although HL is not solely dependent on educational levels, and these competencies can also be developed through other means in addition to education. Selected items from self-efficacy scales [59] specifically developed and adapted to the vaccination field may be useful in completing the assessment of competencies. However, it’s important to underline that competencies refer to the actual knowledge and skills possessed by an individual, while self-efficacy relates to an individual’s belief in their capability to use their competencies effectively [79].

In the literature, composite instruments are reported combining scales to evaluate different variables related to vaccination [15,92], while creating multidimensional composite VL tools is challenging because of the complexity of influencing factors, and the many concepts involved. Elements related to psychological content, such as motivation, beliefs, and attitudes, are often included in a variety of other tools usually administered together with HL or VL questionnaires in conducting investigations. Incorporating some of these elements in a single VL tool would standardize responses, making comparisons easier. Our proposed approach involves selecting a few items for each VL dimension and incorporating additional questions related to beliefs, attitudes, and behaviors, in addition to knowledge. The selection of these elements can be guided by meaningful grouping [93], reliability and factor analyses, in addition to specific statistical methods to handle categorical variables, like the two-stage path analysis [94]. These methods can ensure the construct validity of composite instruments, despite the reduction in the number of elements [73].

Indeed, Covid-19-VLS, frequently utilized in recent studies [10,18,19], can already be considered a composite VL measure. In addition to the VL subscales, it includes questions related to beliefs and attitudes underlying confidence, complacency, and convenience, in addition to coronavirus vaccines intention, and behaviors such as flu vaccine uptake (Appendix A). Although a reduction in VL items was made compared to HLVa, we were able to further reduce their dimensionality by applying PCA as a method of data reduction. This exercise was done also by considering the results of the mediation analysis, balancing the weight of the single VL items, with the purpose to ensure the use of similar elements in future research. This involves including additional questions on knowledge and skills to new assessment scales, maintaining an acceptable total number of items in order to balance the length of the questionnaire with people’s willingness to participate in the surveys. However, the decision on how many items to use should consider the trade-off between maintaining significant factors, reliability, and data interpretation. This approach will also be useful in addressing a limitation of the current VL instruments, related to a possible underestimation of their specific dimensions [6]. In fact, the current VL instruments are derived from tools that were originally developed to assess HL in other areas of medicine (chronic patients), although they have been validated in various languages and cultural settings [19].

In summary, using similar metrics on all elements studied, at the same time balancing them, and considering their association with each other (i.e., VL linked to beliefs and attitudes, linked to outcomes), a composite - possibly unit-weighted - VL score can be sought for future assessments. In addition to measuring separately each scale included in a multidimensional framework - useful to observe the correlations and the mediating role of the variables between them -, adding a standardized combined index would allow simplified representation and easier interpretation of results, as well as improve statistical power [95]. Moreover, including self-reported and performance-based elements in the same tool would facilitate a better assessment of the overall individual VL levels, without the need for additional tests. In fact, it has been shown that the combination of the results obtained using at the same time performance-based measures of functional HL and self-assessed measures of general HL may results in an increase in sensitivity (i.e., the identification of people with low HL skills) and improve the understanding of the relationship between HL and its antecedents [96]. It is reasonable to assume that the same can be valid for VL.

5. Conclusions

References

1. Collini, F.; Bonaccorsi, G.; Del Riccio, M.; Bruschi, M.; Forni, S.; Galletti, G.; Gemmi, F.; Ierardi, F.; Lorini, C. Does Vaccine Confidence Mediate the Relationship between Vaccine Literacy and Influenza Vaccination? Exploring Determinants of Vaccination among Staff Members of Nursing Homes in Tuscany, Italy, during the COVID-19 Pandemic. Vaccines (Basel) 2023, 11. [Google Scholar] [CrossRef]
2. Jiang, F.; Zhao, Y.; Bai, J.; Yang, X.; Zhang, J.; Lin, D.; Li, X. Perceived health literacy and COVID-19 vaccine acceptance among Chinese college students: A mediation analysis. PLoS ONE 2022, 17, e0273285. [Google Scholar] [CrossRef]
3. Hurstak E., F.F., Paasche-Orlow M.K., Hahn, E., Henault L., Moreno P., Weaver C., Marquez M., Serrano E., Thomas J. and Griffith J.W. COVID-19 Vaccine Confidence Mediates the Relationship between Health Literacy and Vaccination in a Diverse Sample of Urban Adults. Vaccines 2023. [CrossRef]
4. Shon, E.J.; Lee, L. Effects of Vaccine Literacy, Health Beliefs, and Flu Vaccination on Perceived Physical Health Status among Under/Graduate Students. Vaccines (Basel) 2023, 11. [Google Scholar] [CrossRef]
5. Cadeddu, C.; Regazzi, L.; Bonaccorsi, G.; Rosano, A.; Unim, B.; Griebler, R.; Link, T.; De Castro, P.; D’Elia, R.; Mastrilli, V.; et al. The Determinants of Vaccine Literacy in the Italian Population: Results from the Health Literacy Survey 2019. Int J Environ Res Public Health 2022, 19. [Google Scholar] [CrossRef]
6. Ratzan, S.C. Vaccine literacy: a new shot for advancing health. J Health Commun 2011, 16, 227–229. [Google Scholar] [CrossRef]
7. Costantini, H. COVID-19 Vaccine Literacy of Family Carers for Their Older Parents in Japan. Healthcare (Basel) 2021, 9. [Google Scholar] [CrossRef]
8. Soeprobowati, T.R.; Budiyanti, R.T.; Ganggi, R.I.P.; Murni, M.; Warsito, B.; Triadi Putranto, T. Barrier Factors Related to COVID-19 Vaccine Literacy in Developing Countries: A Traditional Literature Review. E3S Web of Conferences 2021, 317. [Google Scholar] [CrossRef]
9. Badua, A.R.; Caraquel, K.J.; Cruz, M.; Narvaez, R.A. Vaccine literacy: A concept analysis. Int J Ment Health Nurs 2022, 31, 857–867. [Google Scholar] [CrossRef] [PubMed]
10. Zhang, E.; Dai, Z.; Wang, S.; Wang, X.; Zhang, X.; Fang, Q. Vaccine Literacy and Vaccination: A Systematic Review. International Journal of Public Health 2023, 68. [Google Scholar] [CrossRef] [PubMed]
11. Lorini, C.; Del Riccio, M.; Zanobini, P.; Biasio, R.L.; Bonanni, P.; Giorgetti, D.; Ferro, V.A.; Guazzini, A.; Maghrebi, O.; Lastrucci, V.; et al. Vaccination as a social practice: towards a definition of personal, community, population, and organizational vaccine literacy. BMC Public Health 2023, 23, 1501. [Google Scholar] [CrossRef]
12. Barrett, A.D.T. Vaccinology in the twenty-first century. NPJ Vaccines 2016, 1, 16009. [Google Scholar] [CrossRef] [PubMed]
13. MacDonald, N.E.; Hesitancy, S.W.G.o.V. Vaccine hesitancy: Definition, scope and determinants. Vaccine 2015, 33, 4161–4164. [Google Scholar] [CrossRef]
14. Larson, H.J.; Lin, L.; Goble, R. Vaccines and the social amplification of risk. Risk Anal 2022, 42, 1409–1422. [Google Scholar] [CrossRef]
15. Betsch, C.; Schmid, P.; Heinemeier, D.; Korn, L.; Holtmann, C.; Bohm, R. Beyond confidence: Development of a measure assessing the 5C psychological antecedents of vaccination. PLoS ONE 2018, 13, e0208601. [Google Scholar] [CrossRef] [PubMed]
16. Geiger, M.; Rees, F.; Lilleholt, L.; Santana, A.P.; Zettler, I.; Wilhelm, O.; Betsch, C.; Böhm, R. Measuring the 7Cs of Vaccination Readiness. European Journal of Psychological Assessment 2022, 38, 261–269. [Google Scholar] [CrossRef]
17. Isonne, C.; Iera, J.; Sciurti, A.; Renzi, E.; De Blasiis, M.R.; Marzuillo, C.; Villari, P.; Baccolini, V. How well does vaccine literacy predict intention to vaccinate and vaccination status? A systematic review and meta-analysis. Hum Vaccin Immunother 2024, 20, 2300848. [Google Scholar] [CrossRef] [PubMed]
18. Fenta, E.T.; Tiruneh, M.G.; Delie, A.M.; Kidie, A.A.; Ayal, B.G.; Limenh, L.W.; Astatkie, B.G.; Workie, N.K.; Yigzaw, Z.A.; Bogale, E.K.; et al. Health literacy and COVID-19 vaccine acceptance worldwide: A systematic review. SAGE Open Med 2023, 11, 20503121231197869. [Google Scholar] [CrossRef]
19. Biasio, L.R.; Zanobini, P.; Lorini, C.; Monaci, P.; Fanfani, A.; Gallinoro, V.; Cerini, G.; Albora, G.; Del Riccio, M.; Pecorelli, S.; et al. COVID-19 vaccine literacy: A scoping review. Human Vaccines & Immunotherapeutics 2023. [CrossRef]
20. Biasio, L.R.; Zanobini, P.; Lorini, C.; Monaci, P.; Fanfani, A.; Gallinoro, V.; Cerini, G.; Albora, G.; Del Riccio, M.; Pecorelli, S.; et al. COVID-19 vaccine literacy: A scoping review. Hum Vaccin Immunother 2023, 19, 2176083. [Google Scholar] [CrossRef]
21. Biasio, L.R.; Bonaccorsi, G.; Lorini, C.; Pecorelli, S. Assessing COVID-19 vaccine literacy: a preliminary online survey. Hum Vaccin Immunother 2021, 17, 1304–1312. [Google Scholar] [CrossRef]
22. Arksey, H.; O’Malley, L. Scoping studies: towards a methodological framework. International Journal of Social Research Methodology 2005, 8, 19–32. [Google Scholar] [CrossRef]
23. Peters, M.D.; Godfrey, C.M.; Khalil, H.; McInerney, P.; Parker, D.; Soares, C.B. Guidance for conducting systematic scoping reviews. Int J Evid Based Healthc 2015, 13, 141–146. [Google Scholar] [CrossRef] [PubMed]
24. IBM SPSS Statistics. Available online: https://www.ibm.com/it-it/products/spss-statistics.
25. Gallucci, M. jAMM: jamovi Advanced Mediation Models. [jamovi module]. 2020. Available online: https://jamovi-amm.github.io/.
26. Sheeran, C.A.a.P. The health belief model. In Predicting and changing health behaviour - Research and Practice with Social Cognition Models - Third edition, Norman, M.C.a.P., Ed. McGraw-Hill, Open University Press: 2015.
27. Marikyan, D.P.S. Protection Motivation Theory: a Review. 2023. Available online: https://open.ncl.ac.uk.
28. Akova. COVID-19 Vaccine Literacy and Vaccine Hesitancy Level Among Healthcare Professionals in Türkiye, Their Relationship and Influencing Factors: A Cross-Sectional Stud. Turkiye Klinikleri Journal of Medical Sciences 2022. [CrossRef]
29. Alyahya, K.; Almousa, W.Y.; Binsalamh, L.F.; Alturaifi, G.A.; Alabdely, L.H.; Aljulaihim, N.F.; Aldosari, L.M. The Social Attitudes Towards the Booster Dose of the COVID-19 Vaccine and the Associated Factors Among Residents of Riyadh, Saudi Arabia. Cureus 2023, 15, e46556. [Google Scholar] [CrossRef] [PubMed]
30. Bektas, I.; Bektas, M. The effects of parents’ vaccine hesitancy and COVID-19 vaccine literacy on attitudes toward vaccinating their children during the pandemic. J Pediatr Nurs 2023, 71, e70–e74. [Google Scholar] [CrossRef] [PubMed]
31. Bellomo, R.K.; Cerabona, V.; Massimi, A.; Migliara, G.; Sparano, M.; Novello, F.; Schiliro, T.; Siliquini, R.; Villari, P.; De Vito, C. Who chooses alternative sources of information about childhood vaccinations? A cross-sectional study. Front Public Health 2023, 11, 1225761. [Google Scholar] [CrossRef] [PubMed]
32. Han, S.; Kang, H.S.; Eum, K.; Seo, J.Y.; Karsten, K. Factors Influencing Human Papillomavirus Vaccination Among Asian Immigrant College Students During the COVID-19 Pandemic. SAGE Open 2023, 13. [Google Scholar] [CrossRef]
33. Durmus Iskender, M.; Eren, H.; Durmus, A. The effect of COVID-19 vaccine literacy on attitudes towards COVID-19 vaccine among university students. Health Info Libr J 2023, 40, 307–318. [Google Scholar] [CrossRef]
34. Kerkez, M.; Capuk, H. An assessment on the knowledge and attitudes of university students concerning adult immunization and COVID-19 vaccine in Turkey. Appl Nurs Res 2023, 73, 151717. [Google Scholar] [CrossRef]
35. Lu, Y.; Wang, Q.; Zhu, S.; Xu, S.; Kadirhaz, M.; Zhang, Y.; Zhao, N.; Fang, Y.; Chang, J. Lessons learned from COVID-19 vaccination implementation: How psychological antecedents of vaccinations mediate the relationship between vaccine literacy and vaccine hesitancy. Soc Sci Med 2023, 336, 116270. [Google Scholar] [CrossRef]
36. Maneesriwongul, W. Parental Vaccine Literacy: Attitudes towards the COVID-19 Vaccines and Intention to Vaccinate Their Children Aged 5–11 Years against COVID-19 in Thailand. Vaccines 2023, 1803. [CrossRef]
37. Maneesriwongul, W.; Butsing, N.; Deesamer, S. Parental Hesitancy on COVID-19 Vaccination for Children Under Five Years in Thailand: Role of Attitudes and Vaccine Literacy. Patient Prefer Adherence 2023, 17, 615–628. [Google Scholar] [CrossRef]
38. Montagni, I.; Pouymayou, A.; Pereira, E.; Tzourio, C.; Schuck, S.; Texier, N.; Gonzalez-Caballero, J.L.; Group, C. Measuring Digital Vaccine Literacy: Development and Psychometric Assessment of the Digital Vaccine Literacy Scale. J Med Internet Res 2022, 24, e39220. [Google Scholar] [CrossRef]
39. Us, M.C.; Akarsu, O. Turkish parents’ attitudes towards COVID-19 vaccination of their children aged 12-17 years: A cross-sectional study. Annals of Clinical and Analytical Medicine 2023, 14. [Google Scholar] [CrossRef]
40. Yang, J. Assessing vaccine literacy and exploring its association with vaccine hesitancy_ A validation of the vaccine literacy scale in China. Journal of Affective Disorders 2023, 330, 275–282. [Google Scholar] [CrossRef] [PubMed]
41. Yilmazel, G.; Keles, E.; Calmaz, A.; Daysal Guler, B. Attitudes towards COVID-19 vaccination, vaccine hesitancy and vaccine literacy among unvaccinated young adults. Universa Medicina 2022, 41, 228–235. [Google Scholar] [CrossRef]
42. Yorulmaz, D.S.; Kocoglu-Tanyer, D. A vaccine literacy scale for childhood vaccines: Turkish validity and reliability vaccine literacy scale. Journal of Public Health, 2023. [Google Scholar] [CrossRef]
43. Ishikawa, H.; Takeuchi, T.; Yano, E. Measuring functional, communicative, and critical health literacy among diabetic patients. Diabetes Care 2008, 31, 874–879. [Google Scholar] [CrossRef] [PubMed]
44. Nutbeam, D. Health literacy as a public health goal: a challenge for contemporary health education and communication strategies into the 21st century. Health Promotion International 2000, 15, 259–267. [Google Scholar] [CrossRef]
45. Health_Literacy_Tools_Shed. Health Literacy about Vaccination of adults in ITalian - HLVa-IT. 2023. Available online: https://healthliteracy.bu.edu/hlva-it.
46. Amit Aharon, A.; Nehama, H.; Rishpon, S.; Baron-Epel, O. Parents with high levels of communicative and critical health literacy are less likely to vaccinate their children. Patient Educ Couns 2017, 100, 768–775. [Google Scholar] [CrossRef] [PubMed]
47. Del Giudice, P.; Bravo, G.; Poletto, M.; De Odorico, A.; Conte, A.; Brunelli, L.; Arnoldo, L.; Brusaferro, S. Correlation Between eHealth Literacy and Health Literacy Using the eHealth Literacy Scale and Real-Life Experiences in the Health Sector as a Proxy Measure of Functional Health Literacy: Cross-Sectional Web-Based Survey. J Med Internet Res 2018, 20, e281. [Google Scholar] [CrossRef]
48. Health_Literacy_Tools_Shed. Adolescents’ tools. 2023. Available online: https://healthliteracy.bu.edu/validation_sample_pop_age=0.
49. Maneesriwongul, W. Translation and Psychometric Testing of the Thai COVID-19 Vaccine Literacy Scale. Pacific Rim Int J Nurs Res 2022, 26, 175–186. [Google Scholar]
50. Biasio, L.R.; Lorini, C.; Abbattista, G.; Bozzola, E.; De Castro, P.; Della Seta, M.; Villani, A.; Bonaccorsi, G. Assessment of health literacy skills in family doctors’ patients by two brief, self-administered Italian measures. Ann Ist Super Sanita 2018, 54, 214–222. [Google Scholar] [CrossRef]
51. Hooper, Structural Equation Modelling: Guidelines for Determining Model Fit. Electronic Journal of Business Research Methods 2008, 6, 53–60.
52. Sacco, A.; Robbins, M.L.; Paiva, A.L.; Monahan, K.; Lindsey, H.; Reyes, C.; Rusnock, A. Measuring Motivation for COVID-19 Vaccination: An Application of the Transtheoretical Model. American Journal of Health Promotion 2023, 37, 1109–1120. [Google Scholar] [CrossRef]
53. Fernandez, A.C.; Amoyal, N.R.; Paiva, A.L.; Prochaska, J.O. Motivation for HPV Vaccination Among Young Adult Men: Validation of TTM Decisional Balance and Self-Efficacy Constructs. Am J Health Promot 2016, 30, 163–171. [Google Scholar] [CrossRef] [PubMed]
54. Squiers, L.; Peinado, S.; Berkman, N.; Boudewyns, V.; McCormack, L. The health literacy skills framework. J Health Commun 2012, 17 Suppl 3, 30–54. [Google Scholar] [CrossRef]
55. Paasche-Orlow, M.K.; Wolf, M.S. The Causal Pathways Linking Health Literacy to Health Outcomes. American Journal of Health Behavior 2007, 31, 19–26. [Google Scholar] [CrossRef]
56. Carpenter, C.J. A meta-analysis of the effectiveness of health belief model variables in predicting behavior. Health Commun 2010, 25, 661–669. [Google Scholar] [CrossRef] [PubMed]
57. Ajzen, I. The theory of planned behaviour: reactions and reflections. Psychol Health 2011, 26, 1113–1127. [Google Scholar] [CrossRef] [PubMed]
58. Kowalski, R.M.; Deas, N.; Britt, N.; Richardson, E.; Finnell, S.; Evans, K.; Carroll, H.; Cook, A.; Radovic, E.; Huyck, T.; et al. Protection Motivation Theory and Intentions to Receive the COVID-19 Vaccine. Health Promot Pract 2023, 24, 465–470. [Google Scholar] [CrossRef] [PubMed]
59. Wlodarczyk, D.; Zietalewicz, U. Medics as a Positive Deviant in Influenza Vaccination: The Role of Vaccine Beliefs, Self-Efficacy and Contextual Variables. Vaccines (Basel) 2022, 10. [Google Scholar] [CrossRef]
60. Eiden, A.L.; Barratt, J.; Nyaku, M.K. Drivers of and barriers to routine adult vaccination: A systematic literature review. Hum Vaccin Immunother 2022, 18, 2127290. [Google Scholar] [CrossRef]
61. Zanobini, P.; Lorini, C.; Caini, S.; Lastrucci, V.; Masocco, M.; Minardi, V.; Possenti, V.; Mereu, G.; Cecconi, R.; Bonaccorsi, G. Health Literacy, Socioeconomic Status and Vaccination Uptake: A Study on Influenza Vaccination in a Population-Based Sample. Int J Environ Res Public Health 2022, 19. [Google Scholar] [CrossRef]
62. Yamashita, T.; Keene, J.R.; Moonie, S.A.; Shen, J.J.; Pharr, J.R.; Yoo, J.W. Literacy activity and health among older adults in the USA. Educational Gerontology 2018, 44, 627–638. [Google Scholar] [CrossRef]
63. Lastrucci, V.; Lorini, C.; Caini, S.; Florence Health Literacy Research, G.; Bonaccorsi, G. Health literacy as a mediator of the relationship between socioeconomic status and health: A cross-sectional study in a population-based sample in Florence. PLoS ONE 2019, 14, e0227007. [Google Scholar] [CrossRef]
64. Turhan, Z.; Dilcen, H.Y.; Dolu, I. The mediating role of health literacy on the relationship between health care system distrust and vaccine hesitancy during COVID-19 pandemic. Curr Psychol 2022, 41, 8147–8156. [Google Scholar] [CrossRef]
65. Hurstak, E.E.; Paasche-Orlow, M.K.; Hahn, E.A.; Henault, L.E.; Taddeo, M.A.; Moreno, P.I.; Weaver, C.; Marquez, M.; Serrano, E.; Thomas, J.; et al. The mediating effect of health literacy on COVID-19 vaccine confidence among a diverse sample of urban adults in Boston and Chicago. Vaccine 2023, 41, 2562–2571. [Google Scholar] [CrossRef] [PubMed]
66. Lorini, C.; Collini, F.; Gasparini, F.; Paolini, D.; Grazzini, M.; Ierardi, F.; Galletti, G.; Zanobini, P.; Gemmi, F.; Bonaccorsi, G. Health Literacy, Vaccine Confidence and Influenza Vaccination Uptake among Nursing Home Staff: A Cross-Sectional Study Conducted in Tuscany. Vaccines (Basel) 2020, 8. [Google Scholar] [CrossRef] [PubMed]
67. Arzilli, G.; Stacchini, L.; Casigliani, V.; Mazzilli, S.; Aquino, F.; Oradini-Alacreu, A.; Bruni, B.; Quattrone, F.; Papini, F.; Sironi, D.; et al. Assessing vaccine hesitancy and health literacy using a new Italian vaccine confidence index and a modified Italian medical term recognition test: A cross-sectional survey on Italian parents. Hum Vaccin Immunother 2023, 19, 2271765. [Google Scholar] [CrossRef] [PubMed]
68. Lorini, C.; Lastrucci, V.; Mantwill, S.; Vettori, V.; Bonaccorsi, G.; Florence Health Literacy Research, G. Measuring health literacy in Italy: a validation study of the HLS-EU-Q16 and of the HLS-EU-Q6 in Italian language, conducted in Florence and its surroundings. Ann Ist Super Sanita 2019, 55, 10–18. [Google Scholar] [CrossRef] [PubMed]
69. Thomson, A.; Robinson, K.; Vallee-Tourangeau, G. The 5As: A practical taxonomy for the determinants of vaccine uptake. Vaccine 2016, 34, 1018–1024. [Google Scholar] [CrossRef] [PubMed]
70. An, L.; Bacon, E.; Hawley, S.; Yang, P.; Russell, D.; Huffman, S.; Resnicow, K. Relationship Between Coronavirus-Related eHealth Literacy and COVID-19 Knowledge, Attitudes, and Practices among US Adults: Web-Based Survey Study. J Med Internet Res 2021, 23, e25042. [Google Scholar] [CrossRef] [PubMed]
71. Okan, O.; Bollweg, T.M.; Berens, E.M.; Hurrelmann, K.; Bauer, U.; Schaeffer, D. Coronavirus-Related Health Literacy: A Cross-Sectional Study in Adults during the COVID-19 Infodemic in Germany. Int J Environ Res Public Health 2020, 17. [Google Scholar] [CrossRef] [PubMed]
72. Dietscher, The Action Network on Measuring Population and Organizational Health Literacy (M-POHL) A network under the umbrella of the WHO European Health Information Initiative (EHII). PUBLIC HEALTH PANORAMA 2019, 5, 1–121.
73. Zhang, H.; Li, Y.; Peng, S.; Jiang, Y.; Jin, H.; Zhang, F. The effect of Health Literacy on COVID-19 Vaccine Hesitancy: The Moderating Role of Stress. MedRXiv, 2021. [CrossRef]
74. Kobayashi, L.C.; Wardle, J.; Wolf, M.S.; von Wagner, C. Aging and Functional Health Literacy: A Systematic Review and Meta-Analysis. J Gerontol B Psychol Sci Soc Sci 2016, 71, 445–457. [Google Scholar] [CrossRef] [PubMed]
75. Nguyen, T.H.; Paasche-Orlow, M.K.; McCormack, L.A. The state of the science of health literacy measurement. Information Services & Use 2017, 37, 189–203. [Google Scholar] [CrossRef]
76. George, M. The Vaccine Conundrum. Economic & Political Weekly EPW 2019, lIV. [Google Scholar]
77. Pleasant, A.; McKinney, J.; Rikard, R.V. Health literacy measurement: a proposed research agenda. J Health Commun 2011, 16 Suppl 3, 11–21. [Google Scholar] [CrossRef]
78. Hosseini, F.; Alavi, N.M.; Mohammadi, E.; Sadat, Z. Scoping Review on the Concept of Patient Motivation and Practical Tools to Assess it. Iran J Nurs Midwifery Res 2021, 26, 1–10. [Google Scholar] [CrossRef] [PubMed]
79. American_Psychological_Association. APA Dictionary of Psychology. 2023. Available online: https://dictionary.apa.org/belief.
80. Biasio, L.R.; Giambi, C.; Fadda, G.; Lorini, C.; Bonaccorsi, G.; D’Ancona, F. Validation of an Italian tool to assess vaccine literacy in adulthood vaccination: a pilot study. Ann Ig 2020, 32, 205–222. [Google Scholar] [CrossRef] [PubMed]
81. Gilkey, M.B.; Reiter, P.L.; Magnus, B.E.; McRee, A.L.; Dempsey, A.F.; Brewer, N.T. Validation of the Vaccination Confidence Scale: A Brief Measure to Identify Parents at Risk for Refusing Adolescent Vaccines. Acad Pediatr 2016, 16, 42–49. [Google Scholar] [CrossRef] [PubMed]
82. Ownby, R.L.; Acevedo, A.; Waldrop-Valverde, D.; Jacobs, R.J.; Caballero, J. Abilities, skills and knowledge in measures of health literacy. Patient Educ Couns 2014, 95, 211–217. [Google Scholar] [CrossRef]
83. Zingg, A.; Siegrist, M. Measuring people’s knowledge about vaccination: developing a one-dimensional scale. Vaccine 2012, 30, 3771–3777. [Google Scholar] [CrossRef]
84. University, R. Health Encyclopedia - Vaccination quiz. 2023. Available online: https://www.urmc.rochester.edu/encyclopedia/content.aspx?contenttypeid=40&contentid=ImmunQuiz.
85. PAHO. Quiz: Immunization & Vaccine Administration (JA2015-12). 2023. Available online: https://www.paho.org/en/documents/quiz-immunization-vaccine-administration-ja2015-12.
86. Sheeran, C.A.a.P., The health belief model in Predicting and changing health behaviour - Research and Practice with Social Cognition Models Third edition, M.C.a.P. Norman, Editor. 2015, McHraw-Hill.
87. Hannah Priest Catalano, K.R., Katherine Hyatt Hawkins. Theory of Planned Behavior-based Correlates of HPV Vaccination Intentions and Series Completion among University Students in the Southeastern United States. The Health Educator 2017, 49.
88. Larson HJ, S.W., Tucker JD, Smith DM. Measuring Vaccine Confidence: Introducing a Global Vaccine Confidence Index. Plos Current Outbreaks 2015.
89. Frew PM, M.R., Mehta C, Chamberlain A, Hinman A, Nowak G, et al. Development of an Index for Measurement of Parents’ Vaccine Confidence and Linkage to Pediatric Immunization Acceptance. Available online: https://www.hhs.gov/sites/default/files/Frew_Development%20of%20a%20Vaccine%20Confidence%20Index%20to%20Measure%20Parental%20Confidence%20in%20Childhood%20Vaccinations_remediated.pdf.
90. NIH. What are competencies? 2023. Available online: https://hr.nih.gov/about/faq/working-nih/competencies/what-are-competencies#:~:text=Competencies%20are%20the%20knowledge%2C%20skills,repeatedly%20applying%20knowledge%20or%20ability.
91. Margolis, R. Educational differences in healthy behavior changes and adherence among middle-aged Americans. J Health Soc Behav 2013, 54, 353–368. [Google Scholar] [CrossRef]
92. Oduwole, E.O.; Pienaar, E.D.; Mahomed, H.; Wiysonge, C.S. Overview of Tools and Measures Investigating Vaccine Hesitancy in a Ten Year Period: A Scoping Review. Vaccines (Basel) 2022, 10. [Google Scholar] [CrossRef]
93. Song, M.K.; Lin, F.C.; Ward, S.E.; Fine, J.P. Composite variables: when and how. Nurs Res 2013, 62, 45–49. [Google Scholar] [CrossRef] [PubMed]
94. Lai, M.H.C.; Hsiao, Y.Y. Two-stage path analysis with definition variables: An alternative framework to account for measurement error. Psychol Methods 2022, 27, 568–588. [Google Scholar] [CrossRef] [PubMed]
95. Complete_Dissertation_by_Statistic_Solutions. What are Composite Scores? 2023. Available online: https://www.statisticssolutions.com/composite-scores/.
96. Lorini, C.; Lastrucci, V.; Paolini, D.; Bonaccorsi, G.; Florence Health Literacy Research, G. Measuring health literacy combining performance-based and self-assessed measures: the roles of age, educational level and financial resources in predicting health literacy skills. A cross-sectional study conducted in Florence (Italy). BMJ Open 2020, 10, e035987. [Google Scholar] [CrossRef]
97. Khiari, H.; Cherif, I.; M’Ghirbi, F.; Mezlini, A.; Hsairi, M. COVID-19 Vaccination Acceptance and Its Associated Factors among Cancer Patients in Tunisia. Asian Pac J Cancer Prev 2021, 22, 3499–3506. [Google Scholar] [CrossRef]
98. Correa-Rodriguez, M.; Rueda-Medina, B.; Callejas-Rubio, J.L.; Rios-Fernandez, R.; de la Hera-Fernandez, J.; Ortego-Centeno, N. COVID-19 vaccine literacy in patients with systemic autoimmune diseases. Curr Psychol 2022, 1–16. [Google Scholar] [CrossRef]
99. Takahashi, Y.; Ishitsuka, K.; Sampei, M.; Okawa, S.; Hosokawa, Y.; Ishiguro, A.; Tabuchi, T.; Morisaki, N. COVID-19 vaccine literacy and vaccine hesitancy among pregnant women and mothers of young children in Japan. Vaccine 2022, 40, 6849–6856. [Google Scholar] [CrossRef]
100. Krishnamurthy, K.; Sobers, N.; Kumar, A.; Ojeh, N.; Scott, A.; Cave, C.; Gupta, S.; Bradford-King, J.; Sa, B.; Adams, O.P.; et al. COVID-19 Vaccine Intent Among Health Care Professionals of Queen Elizabeth Hospital, Barbados. J Multidiscip Healthc 2021, 14, 3309–3319. [Google Scholar] [CrossRef] [PubMed]
101. Al Fayez, N.; Nassar, M.S.; Alshehri, A.A.; Alnefaie, M.K.; Almughem, F.A.; Alshehri, B.Y.; Alawad, A.O.; Tawfik, E.A. Recent Advancement in mRNA Vaccine Development and Applications. Pharmaceutics 2023, 15. [Google Scholar] [CrossRef] [PubMed]
102. Gray, A.; Fisher, C.B. Determinants of COVID-19 Vaccine Uptake in Adolescents 12-17 Years Old: Examining Pediatric Vaccine Hesitancy Among Racially Diverse Parents in the United States. Front Public Health 2022, 10, 844310. [Google Scholar] [CrossRef] [PubMed]
103. Nelson, L.R.; Stupiansky, N.W.; Ott, M.A. The Influence of Age, Health Literacy, and Affluence on Adolescents’ Capacity to Consent to Research. J Empir Res Hum Res Ethics 2016, 11, 115–121. [Google Scholar] [CrossRef] [PubMed]
104. Maki, W.; Ishitsuka, K.; Yamaguchi, K.; Morisaki, N. Vaccine Literacy, COVID-19 Vaccine-Related Concerns, and Intention to Recommend COVID-19 Vaccines of Healthcare Workers in a Pediatric and Maternity Hospital: A Cross-Sectional Study. Vaccines (Basel) 2022, 10. [Google Scholar] [CrossRef]
105. Declich, S. Organizational Vaccine Literacy (VL) can remove system barriers to Newly Arrived Migrants vaccination. in 16th European Public Health Conference. 2023. [CrossRef]
106. Rosenfeld, L.; Miller, A.; Garverich, S.; Guyer, M.; Steiner, R.; Lincoln, A.K. Performing an Organizational Health Literacy Assessment in a Shelter Serving People with Mental Illness. Health Lit Res Pract 2022, 6, e167–e174. [Google Scholar] [CrossRef]
107. Brega, A.G.; Freedman, M.A.; LeBlanc, W.G.; Barnard, J.; Mabachi, N.M.; Cifuentes, M.; Albright, K.; Weiss, B.D.; Brach, C.; West, D.R. Using the Health Literacy Universal Precautions Toolkit to Improve the Quality of Patient Materials. J Health Commun 2015, 20 Suppl 2, 69–76. [Google Scholar] [CrossRef]
108. Biasio, L.R.; Bonaccorsi, G.; Lorini, C.; Mazzini, D.; Pecorelli, S. Italian Adults’ Likelihood of Getting COVID-19 Vaccine: A Second Online Survey. Vaccines (Basel) 2021, 9. [Google Scholar] [CrossRef]