Skip to content
EvidenceHelixEvidenceLib · Scientific Encyclopedia
⌘ K

Scientific library

EvidenceLib encyclopediaAll articles A–Z2,100Open textbooks35Open-access articles1,010Cancer study catalog458How it is made

My workspace this browser

Saved pages0Notes & annotations0

Recently viewed

Explore by field

Cancer and Oncology182Genetics and Genomics170Neuroscience185Cardiovascular Medicine180Immunology162Pharmacology174Molecular Biology161Infectious Diseases150Rare and Inherited Diseases181Clinical Research173Anatomy and Physiology617Drugs and Chemicals621Psychiatry and Psychology75Public Health and Nutrition64Diagnostics and Medical Technology15
Plans & pricingCompare EvidenceHelix workspace plans
Library›Open-access articles›Article

Continue where you left off ()

Explore more with EvidenceHelix Workspace

Compare studies, analyze evidence and create research reports with premium tools.

Explore Researcher plans

EvidenceLib · Open-access article · Immunology

What Demographic, Social, and Contextual Factors Influence the Intention to Use COVID-19 Vaccines: A Scoping Review

Bara’ Abdallah AlShurman, Amber Fozia Khan, Christina Mac, Meerab Majeed, Zahid Ahmad Butt

International Journal of Environmental Research and Public Health 2021 · doi:10.3390/ijerph18179342

CC BY 4.0Full textApproximately 34 min read84 references

Table of Contents

Abstract1. Introduction2. Materials and Methods3. Results4. Discussion5. ConclusionsReferences

Abstract

Background: During the COVID-19 crisis, an apparent growth in vaccine hesitancy has been noticed due to different factors and reasons. Therefore, this scoping review was performed to determine the prevalence of intention to use COVID-19 vaccines among adults aged 18–60, and to identify the demographic, social, and contextual factors that influence the intention to use COVID-19 vaccines. Methods: This scoping review was conducted by using the methodological framework for scoping review outlined by Arksey and O’Malley. A search strategy was carried out on four electronic databases: PubMed, Scopus, CINAHL, and PsycINFO. All peer-reviewed articles published between November 2019 and December 2020 were reviewed. Data were extracted to identify the prevalence of, and factors that influence, the intention to use COVID-19 vaccines. Results: A total of 48 relevant articles were identified for inclusion in the review. Outcomes presented fell into seven themes: demographics, social factors, vaccination beliefs and attitudes, vaccine-related perceptions, health-related perceptions, perceived barriers, and vaccine recommendations. Age, gender, education level, race/ethnicity, vaccine safety and effectiveness, influenza vaccination history, and self-protection from COVID-19 were the most prominent factors associated with intention to use COVID-19 vaccines. Furthermore, the majority of studies (n = 34/48) reported a relatively high prevalence of intention to get vaccinated against COVID-19, with a range from 60% to 93%. Conclusion: This scoping review enables the creation of demographic, social, and contextual constructs associated with intention to vaccinate among the adult population. These factors are likely to play a major role in any targeted vaccination programs, particularly COVID-19 vaccination. Thus, our review suggests focusing on the development of strategies to promote the intention to get vaccinated against COVID-19 and to overcome vaccine hesitancy and refusal. These strategies could include transparent communication, social media engagement, and the initiation of education programs.

1. Introduction

Vaccination has been acknowledged as a significant public health achievement in decreasing the prevalence of infectious diseases since the first vaccine was invented in 1796, for use against smallpox [1]. Despite the various benefits of immunization and vaccines, the spread of misinformation and anti-vaccination movements have led to rising levels of vaccine hesitancy worldwide. In the mid-19th century, Britain had passed laws that made vaccination mandatory for children, resulting in the creation of the Anti-Vaccination League by the anti-vaccination movement in London. Since then, anti-vaccination movements have continued, resulting in a further decline in vaccination rates as the world began to witness disease outbreaks once again. For instance, the belief that the measles, mumps, and rubella (MMR) vaccine caused autism in children led to a decline in MMR vaccine uptake, even after various studies disproved the causation [2,3,4,5,6].

In November 2011, members of the Strategic Advisory Group of Experts (SAGE) recognized the reluctance to accept immunization, which affects the uptake of vaccines in both developed and developing countries [7]. Vaccine hesitancy, which can be defined as the “delay in acceptance or refusal of vaccination despite the availability of vaccine services” according to the SAGE working group, has increased worldwide due to different factors and barriers that should be addressed to improve the acceptance of global vaccination programs [8,9]. As a result, the SAGE working group established two conceptual models to understand the factors that influence the decision to accept the vaccines: the first was the “3Cs” model, composed of three approaches—complacency, convenience, and confidence—while the second was a comprehensive matrix that better portrayed the involvement of contextual, individual, and group influences alongside the vaccine-/vaccination-specific issues [8].

Following the outbreak of coronavirus disease 2019 (COVID-19), the WHO declared that the whole world faces a serious global health emergency of international concern in January 2020 [8,10]. On 11 December 2020, the U.S. Food and Drug Administration issued the first emergency use authorization (EUA) for a vaccine for the prevention of COVID-19 in individuals 16 years of age and older. The emergency use authorization allowed the Pfizer-BioNTech COVID-19 vaccine to be distributed in the U.S as the first approved COVID-19 vaccine [11]. Recent reports indicate that, as of 28 February 2021, the number of global deaths from COVID-19 reached more than 2.5 million, and the estimated number of confirmed infected cases was 114 million, making the outbreak one of the worst crises in history [12]. Therefore, global efforts and urgent actions were taken rapidly, and more than 150 countries engaged in developing safe and effective COVID-19 vaccines to help control the widespread pandemic [13,14]. At present, a dozen vaccines have been authorized and approved worldwide, and other vaccines are currently being tested in clinical trials on humans, while over 200 remain in various stages of clinical development [15]. However, previous studies have shown that the anti-vaccine movement is still increasing at a great rate, which could undermine and jeopardize researchers’ efforts to end the pandemic [16,17]. For that reason, in the era of the infodemic, it is essential that the safety and benefits of the vaccines are emphasized to the public to increase vaccine uptake.

To date, numerous observational studies have been conducted to identify various reasons that may explain the rise of COVID-19 vaccine hesitancy and investigate the factors that affect the intention to use the vaccine [18,19,20,21,22,23,24,25,26,27,28]. As mentioned in the literature, the most common reasons that contributed to COVID-19 vaccine acceptance, hesitancy, and refusal are related to socio-demographic factors, perceived risks and benefits, and vaccine-related perceptions [13]. A systematic review was performed to provide an updated assessment of COVID-19 vaccination acceptance rates worldwide [29]; the findings revealed considerable variability in COVID-19 vaccine acceptance rates, but the authors did not provide a thorough understanding of the socio-demographic, psychological, contextual, and political factors implicated in regional and cultural differences in COVID-19 vaccine hesitancy. Another rapid systematic review aimed to explore people’s perceptions regarding COVID-19 vaccines over time and analyze factors pertaining to vaccine perceptions and intention during the pandemic [30]; however, in this review, a limited screening strategy and search terms were used, which may not address all the relevant studies; additionally, the inclusion of studies was restricted to include only surveys and questionnaires; moreover, the use of Google search to obtain a large number of related articles was another limitation of this study, as many authors argue that the usage of Google search in systematic reviews might be inappropriate, as it results in personalization of search results and, thus, leads to a form of selection bias [31,32]. Another recent scoping review investigated the vaccine hesitancy among Chinese scholars and identified a number of determinants of vaccine hesitancy in China; these determinants were categorized into four different approaches: vaccine safety, vaccine incident response, professional conduct of vaccination, and parental concern [33]; however, this review focused only on publications in China, and addressed the vaccine hesitancy in general, not specific to COVID-19 [33].

To overcome the aforementioned gaps in the existing research, we conducted a comprehensive scoping review. In addition, the scarcity of previous reviews allowed us to outline a framework that maps all of the key concepts underpinning the factors that affect the intention to use COVID-19 vaccines. This enhances the significance of our review, as this area has not previously been reviewed comprehensively. Furthermore, analyzing, summarizing, and disseminating research findings in a scoping review can provide a mechanism to policymakers and practitioners by which to visualize the depth and breadth of the intention to get COVID-19 vaccines. This scoping review also went further in identifying the factors that affect the intention to use COVID-19 vaccines based on constructs of the health belief model (HBM); this theoretical model has been widely used to assess the factors behind decision making and help in understanding what encourages and discourages people from adopting health-related behaviors [34,35]. The HBM has also been used in the context of vaccination—particularly influenza vaccination [34,36]. Consequently, conducting this scoping review helped us to scope a body of literature related to the factors that influence the intention to use COVID-19 vaccines; thus, it could be a helpful precursor to promote the identification of parameters for future systematic reviews. Likewise, the adoption of health belief model components in this review was useful to clarify significant predictors of COVID-19 vaccination acceptance, refusal, and hesitancy. On the other hand, it is worth mentioning that this review focused on adults aged 18–60 years as the target population, because several studies have reported a decline in adults’ willingness to get vaccinated against COVID-19 when compared to those above the age of 60 [19,20,37,38,39,40]. Therefore, our objectives were to determine the prevalence of intention to use COVID-19 vaccines among adults aged 18-60 years of age, and to identify the demographic, social, and contextual factors that influence the intention to use COVID-19 vaccines.

2. Materials and Methods

2.1. Overview

This scoping review was conducted by using the methodological framework for scoping review outlined by Arksey and O’Malley [41]. It also followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping reviews’ guidelines [42].

2.2. Search Strategy and Selection Criteria

A comprehensive search strategy was carried out on four electronic databases: PubMed, Scopus, CINAHL, and PsycINFO. The search strategy included extensive keywords and MeSH terms for each database to cover all the articles related to the research question. Generally, the search was done using the following strategy: (vaccin* OR immuniz* OR immunis* OR inoculat* OR Moderna OR Pfizer OR anti-vaccin* OR immunization OR vaccines OR mass vaccination) AND (hesitan* OR accept* OR refus* OR preference* OR willingness OR intention OR trust OR mistrust OR attitude* OR avoidance OR distrust OR knowledge OR doubt OR fear OR perception* OR misconception* OR misinformation OR belief OR dilemma OR behavio* OR concern* OR delay OR confidence OR adherence OR nonadherence OR noncomplian* OR complian* OR uptake OR opinion* OR anxiety* OR decision* OR attitude to health OR health attitudes OR vaccination refusal OR health knowledge, attitudes, practice OR patient acceptance of health care OR trust). Additionally, CADTH’s database search strings were used to search for articles related to COVID-19, since these strings have been extensively used in published articles; thus, the CADTH database helps to conduct comprehensive literature searches for both scoping and systematic reviews (search strategy details in Appendix A). All peer-reviewed articles published between November 2019 and December 2020 resulting from these searches, along with relevant references cited in those articles, were reviewed. A list of inclusion and exclusion criteria was set out, and studies were selected according to these criteria (Section 2.6 in the methods).

2.3. Screening Procedure

All peer-reviewed articles published between November 2019 and December 2020 were reviewed and imported into Covidence, which was used for the screening process. Title/abstract screening and full-text screening were performed by the primary reviewer (B.A.A.) and the secondary reviewers (C.M. and A.F.K.). Disagreements were resolved by the primary reviewer (B.A.A.), and the entire scoping review process, including the search strategy and manuscript, was monitored by the tertiary reviewer (Z.A.B.).

2.4. Extracting the Data

All relevant publications were recorded in a spreadsheet in Microsoft Excel, including information as follows: first author, country, type of study, study population, the prevalence of intention to vaccinate, key findings and relevant factors (demographic, social, and contextual factors) (Table 1).

2.5. Presenting and Reporting the Results

All of the factors that influence the intention to use COVID-19 vaccines were extracted from the Excel sheet. Then, the results were presented and categorized into four main sections: (1) selected articles; (2) descriptive analysis of articles; (3) the prevalence of intention to use COVID-19 vaccines; and (4) identifying the factors of vaccine intention: demographic, social, and contextual.

All of the extracted factors were categorized according to a modified health belief model. First, modifying variables within the HBM were captured as demographic factors, such as gender, age, marriage status, race/ethnicity, education level, profession, household income, and employment status. Second, social factors were considered—those factors and sources that affect thoughts or attitude in social contexts in general situations, such as social density and pro-social concern, communication and media, socioeconomic status, social solidarity, trust in government, and political beliefs. Third, contextual factors were defined as those specific factors related to the intrapersonal or surrounding circumstances that influence the person’s behaviors or attitudes in a particular instance (e.g., the intention to take or refuse vaccines). In this review, many contextual factors were identified, including vaccine safety, vaccine efficacy/effectiveness, health history, influenza vaccination history, anti-vaccine attitudes or beliefs, vaccine recommendations by scientists, and many others.

The actual HBM consists of six main concepts: perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy. These concepts were modified in order to categorize the studied factors into more appropriate themes under the category of “contextual factors”. Perceived susceptibility and perceived severity were combined and referred to as “health-related perceptions”. The perceived benefits concept was replaced with vaccine-related perceptions, while cues to action was substituted for vaccine recommendations. In addition to this, we added vaccination beliefs and attitudes to investigate more related factors in-depth, as this category can be a surrogate for the self-efficacy category within the HBM. Lastly, demographics and social factors were considered to modify factors that already existed in the original HBM.

2.6. Inclusion and Exclusion Criteria

Throughout the title/abstract screening and full-text screening, the following inclusion and exclusion criteria were used to determine the final set of studies in the scoping review: Firstly, the inclusion criteria consisted of scholarly peer-reviewed articles that were related to vaccine hesitancy, acceptance, refusal, trust/distrust, perceptions, concerns, confidence, knowledge, attitudes, and beliefs about the COVID-19 vaccines. For predictors and exposure, studies that presented data on possible demographic, social, and contextual predictors that affect the uptake of COVID-19 vaccines were included. These studies included cross-sectional studies, case–control studies, randomized controlled trials, cohort studies, and/or qualitative studies. The criteria included studies from any country of origin with publication dates from November 2019 to December 2020. Lastly, studies that focused on adults aged 18 years old and above were included.

The exclusion criteria consisted of studies that were not related to the COVID-19 vaccine. Non-peer reviewed articles—such as editorials, perspectives, analyses, reports, preprints, letters, commentary/opinion pieces, reviews, conference articles, essays, and pilot studies—were excluded from the final study selection. Studies that were focused on safety and vaccine development research—such as immunogenicity and serological studies, preclinical trials, and efficacy trials—were excluded. Furthermore, cost–benefit analysis or cost-effectiveness studies, along with animal vaccination studies or trials, were also excluded. Views of the public’s or healthcare workers’ recommendations were also an exclusion criterion. Lastly, studies that were not in the English language and not available as full-text articles were excluded from the final study pool.

3. Results

3.1. Selected Articles

A total of 4239 studies were identified through the database searches (Scopus (2002 articles), PubMed (1455 articles), CINAHL (721 articles), and PsycINFO (61 articles)), from which 1337 duplicates were removed, resulting in 2902 studies included in the screening process. After title and abstract screening, 2772 were excluded because they were irrelevant to the research question. Out of the remaining 130 full-text articles, 82 papers were excluded based on the exclusion criteria (Figure 1). Finally, 48 relevant articles were identified for inclusion in the review.

3.2. Descriptive Analysis of Articles

The 48 included studies were conducted in various countries around the world. The majority (27%) of these studies were conducted in the USA (27%; 13/48) [19,21,23,43,44,45,48,50,53,56,65,67,75], followed by China (12.5%; 6/48) [46,54,55,57,63,69], the UK (12.5%; 6/48) [39,51,52,60,65,68], and Italy (12.5%; 6/48) [20,37,47,59,64,70]. The rest were conducted in European countries (France, Spain, Ireland, and Germany), Canada, the Democratic Republic of Congo, Indonesia, India, Turkey, Saudi Arabia, Australia, Mexico, Malta, Israel, Mexico, and Malaysia. Most of the studies were cross-sectional surveys, except for four studies, which comprised discrete choice experiments (4%; 2/48) [55,63], a follow-up experiment (2%; 1/48) [48], and a randomized control experiment (2%; 1/48) [67]. The majority of research did not focus on a specific risk group, but addressed the general public (73%; 35/48) [9,19,20,21,23,25,27,28,37,39,43,44,45,46,47,48,51,52,53,55,56,58,59,61,62,63,64,65,66,67,68,69,73,74,75]. Other studied risk groups were healthcare workers (health professionals, nurses, or others) (17%; 8/48) [22,24,26,38,40,54,57,71], university students and academics (8%; 4/48) [26,49,70,72], and parents and their guardians (2%; 1/48) [60]. The intention to vaccinate against COVID-19 was the main outcome variable in the majority of the studies (39.5%; 19/48) [20,21,23,26,39,40,43,48,50,54,55,57,58,59,61,63,64,66,75]; vaccine acceptance was assessed in 9 studies [19,25,27,28,38,45,46,53,60], while vaccine hesitancy was investigated in 10 studies [9,22,24,44,51,52,69,70,71,72]. Other outcomes were to assess the uncertainty and misconceptions about COVID-19, the attitudes towards potential COVID-19 vaccines, and to understand the barriers and facilitators to receiving a future COVID-19 vaccine [37,47,49,56,62,65,67,68,73,74].

3.3. The Prevalence of Intention to Use COVID-19 Vaccine

Most of the studies (94%; 45/48) in this review reported the prevalence of intention to get a COVID-19 vaccine [9,19,20,21,22,24,25,26,27,28,37,38,39,40,43,44,45,46,47,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,66,67,68,69,70,71,72,73,74,75], while only three studies did not measure this prevalence [23,48,65]. The global trend of intention to get a COVID-19 vaccine showed a fluctuation in public intentions to get vaccinated over time, from February to October (Figure 2). The highest acceptance rates were noticed among adults from Indonesia (93%) [28], Italy (92%) [47], and China (91%) [46], followed by India and Australia (86%) [27,61]. On the other hand, the lowest acceptance rates were found in the Democratic Republic of Congo among healthcare workers (28%) [38], in Malta among university students and academics (31%) [72], and in China among nurses (40%) [57]. Furthermore, the majority of studies (n = 34/45) [9,19,20,24,25,26,27,28,39,40,43,44,45,46,47,49,50,51,52,53,54,55,56,58,60,61,62,63,66,68,69,70,71,75], reported a relatively high prevalence of intention to get vaccinated against COVID-19, with a range from 60% [75], to 93% [28].

3.4. Identifying the Factors of Vaccine Intention: Demographic, Social, and Contextual

3.4.1. Theoretical Constructs

All factors that affect intentions to receive COVID-19 vaccines were extracted from the 48 articles. In order to identify the most relevant factors, the outcomes presented fell into 55 theoretical constructs. These were classified into seven themes: demographics, social factors, vaccination beliefs and attitudes, vaccine-related perceptions, health-related perceptions, perceived barriers, and vaccine recommendations. Themes were derived from the health belief model (HBM)—a widely used framework for guiding health promotion and disease prevention programs and understanding health-related behaviors. The actual HBM consists of six main concepts: perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy. These concepts were modified in order to categorize the studied factors into more appropriate themes under the category of “contextual factors”. Perceived susceptibility and perceived severity were combined and referred to as “health-related perceptions”. The perceived benefits concept was replaced with vaccine-related perceptions, while cues to action was substituted for vaccine recommendations. In addition to this, we added vaccination beliefs and attitudes to investigate more related factors in-depth, as this category can serve as a surrogate to the self-efficacy category within the HBM. Lastly, demographics and social factors were considered to modifying factors that already existed in the original HBM.

Figure 3 provides an overview of identified theoretical constructs and themes using a conceptual framework based on a modified health belief model for the hypothesized predictors of intention to receive a COVID-19 vaccine. In this review, some of the theoretical constructs and factors were significantly associated with COVID-19 vaccination beliefs and attitudes, while others were not (Table 2). Age, gender, education level, race/ethnicity, vaccine safety and effectiveness, influenza vaccination history, and protection from COVID-19 were the most prominent factors associated with intention to get vaccinated against COVID-19. Table 2 shows the studied variables that have been significantly associated with intentions to use COVID-19 vaccines in the literature; however, it does not report the actual significance values.

3.4.2. Demographic Factors

All studies reported demographic factors associated with COVID-19 vaccination amongst adults older than 18 years. The most frequently assessed demographics were age, gender, education, and ethnicity. The less frequently used constructs included having children, place of work, religiosity, and smoking status. Age, gender, and education in most studies were significantly associated with intention to receive COVID-19 vaccines. Eight studies conducted at different times after the coronavirus outbreak in March, April, May, and September 2020 showed that men and older people were more likely to receive the vaccination than women and younger people [38,40,45,46,53,58,62,65,72]. A study conducted in the USA found that the risk of mortality elicits a larger proportion willing to vaccinate than morbidity alone, which explains why older populations were more willing than younger ones [76]. In contrast, five studies indicated that younger people tended to be more receptive to coronavirus vaccination, while only two studies—in China and Australia—reported that females were more likely to get the vaccine at the beginning of the pandemic [19,20,44,54,61,63,75]. One study in Italy reported that middle-aged individuals (35–59 years) had lower willingness to vaccinate for COVID-19 than the 18–34 and over 60 age groups [59]. Of note, there is a growing gap between those with low and high education levels; many studies showed that higher education level was associated with greater vaccination intention than lower education level [19,21,25,43,51,53,56], while others recorded the opposite [44,52,55].

Regarding race and ethnicity, Reiter et al., found that White people in the U.S. were five times more willing to vaccinate (67%) against COVID-19 than Black people (12%), even though Black people experienced the highest COVID-19 incidence and mortality rates in the U.S., which in turn raises serious concerns about the burden of COVID-19 [45]. Nine surveys conducted in the U.S. and UK showed that White people consistently expressed greater acceptance of COVID-19 vaccines than Black people [19,21,23,45,50,51,53,60,75]. These different levels of COVID-19 vaccine hesitancy exhibit a distinct challenge and threat to achieving health equity [75]. Other socio-demographic factors were also measured, including employment status, profession, and place of work. Medical jobs were the occupation with the highest projected vaccine uptake, followed by academics, students, and those employed in the public sector [9,24,25,28,37,38,40,58,71,73]. Additionally, low income, unemployment or retirement, living in rural settings, being married, and having children were all associated with a low percentage of intention to receive a vaccine [21,44,45,50,51,75].

3.4.3. Social Factors

Ten constructs related to social factors were identified across the studies; these were: social solidarity, socioeconomic status, social density and prosocial concern, child protection/parental concerns, communication and media, trust in government, political beliefs, recent or upcoming travel, trust in scientists/WHO/CDC/FDA, and work stress/anxiety. The most common investigated factor was political leaning; three U.S.-based surveys were carried out to provide an overview of public opinion surrounding COVID-19 vaccination. All of these studies found that people with liberal political views expressed the strongest SARS-CoV-2 vaccine intentions, followed by moderates, and then conservatives [43,45,50]. This was explained by the political polarization during the pandemic, which may lead individuals with different political inclinations to have various perceptions of risk and level of threats and, thus, different notions of the necessary actions to be taken [45]. Social norms and prosocial concerns were studied by Freeman, Taylor, and Jung, who examined the interactions between social factors and vaccine hesitancy, as well as the motivational roots of this hesitancy [44,48,51]; their findings showed that people with prosocial behaviors and social contacts/activities were less hesitant to receive a vaccine compared with those with individual concern conditions. The reasoning behind this is that people with more prosocial concerns tend to protect the vulnerable members of their community and to decrease coronavirus transmission risk as much as possible [44].

Reviewing the literature, we found that three social sources were responsible for the motivation or refusal to get the vaccine: the government; the scientists, and trusted agencies such as the WHO, CDC, or FDA; and the communication and social media. A large international study showed that fake news can increase susceptibility to misinformation, which may make people less likely to report willingness to get vaccinated against COVID-19. Moreover, higher trust in scientists was associated with a 73% increase in the odds of getting vaccinated, and a 79% increase in the odds of recommending vaccination to others [65]. Another cross-sectional study in the UK concluded that reluctance to receive a vaccine was associated with the belief that the media have over-exaggerated the risks of COVID-19, and that the timeline for the outbreak will be short [68]. Malik and his colleagues reported that participants with the highest confidence in healthcare professionals (75%), the CDC (64%), and state health departments (62%) were more likely to get vaccinated against COVID-19 [53]. Likewise, Kreps et al. revealed that the FDA, CDC, and WHO recommendations to encourage people to take COVID-19 vaccine have contributed to increasing the likelihood of vaccination more than recommendations from political figures [19]. Child protection and parental concerns were also observed as predictors that influence vaccination intention. Parents were hesitant to give the vaccine to their children, as the statistical results showed that 34.3% of parents were unsure of taking the vaccine for themselves, while 41% were unsure of giving their children the vaccine [60]. Only two studies investigated work stress and its relation to vaccine uptake; the findings from both studies showed that work stress and anxiety were positively associated with intention to receive a COVID-19 vaccine [54,73].

3.4.4. Contextual Factors

Five themes emerged under this category: vaccination beliefs and attitudes, vaccine-related perceptions, health-related perceptions, perceived barriers, and vaccine recommendations. These factors were reported frequently across the included studies in the scoping review.

Vaccination Beliefs and Attitudes

Among these constructs, the most significant ones presented in studies were vaccine confidence and vaccine hesitancy. Vaccine confidence is the trust that the person has in taking the recommended vaccine, whereas vaccine hesitancy refers to emerging concerns and hesitance to take a vaccine. According to Kowk et al., who conducted a cross-sectional survey among nurses, those who had stronger vaccine confidence were more likely to receive a COVID-19 vaccine [54]. Another study found that trust and confidence in the vaccines led to a higher probability of vaccination intention [55]. In comparison, vaccine hesitancy is associated with a decrease in intention to take COVID-19 vaccines [20,40]. A study conducted in the UK found that higher vaccine hesitancy was associated with lower adherence to all safety guidelines and a lower likelihood of getting tested [51]. Freeman et al. found that vaccine hesitancy was lower in those at very high risk of severe COVID-19 illness. In contrast, mistrust, beliefs that vaccine safety data was often fabricated, and deceit about vaccine efficacy and safety from the government and pharmaceutical companies were reasons associated with higher levels of vaccine hesitancy [51]. Similarly, anti-vaccine attitudes or beliefs were associated with higher vaccine hesitancy, resulting in lower intention to vaccinate [21]. Bertin et al. found that all types of conspiracy beliefs negatively impacted vaccine attitudes and the intention to vaccinate against COVID-19 [49]. Lastly, preference for natural immunity and believing COVID-19 vaccination is unnecessary were both associated with lower intent to vaccinate against COVID-19 [44,57]; however, these themes were poorly represented in the literature, as there is a lack of studies surrounding these topics.

Vaccine-Related Perceptions

Nine constructs were identified under vaccine-related perceptions; vaccine efficacy/effectiveness, vaccine safety, influenza vaccination history, and vaccine adverse side effects were the most dominant and significant in the literature. In general, studies found that higher vaccine efficacy and evidence of the vaccine’s efficacy were associated with a higher likelihood of receiving the vaccine [19,27,28,44,45,50,55,56,62,63]. When determining the factors that impact vaccination decisions, a study from the U.S. reported that 81% of participants said that the vaccine’s efficacy was a significant factor [45]. Another study in Indonesia revealed that 93.3% of adults were willing to be vaccinated with a 95%-effective vaccine, whereas 67% were willing to be vaccinated with a 50%-effective vaccine; thus, vaccine effectiveness was one of the factors to change the direction of vaccine intention [28]. In contrast, concerns about vaccine efficacy were associated with a decrease in likelihood to receive the vaccines due to worries about the accelerated vaccine development [21,27,50,51,57,60,66,69]. Trends for vaccine safety were similar to those of vaccine efficacy; overall, individuals who received evidence of the vaccine’s safety and believed that the vaccine was safe were more likely to accept the vaccine [9,27,39,44,50]. Adverse side effects from the vaccine were also an important factor in willingness to take COVID-19 vaccines. A decrease in intention to vaccinate was associated with the presence of adverse side effects and individuals who were concerned about potential adverse side effects [27,44,66,69]; this includes concerns related to insufficient information about the long-term side effects of a novel vaccine [22]. Conversely, fewer adverse side effects and the belief that vaccination would not cause side effects were associated with higher intention to vaccinate [9,19,39,55,61,63]. In addition, influenza vaccination history was a significant factor, with individuals who had previously received an influenza vaccine being more likely to receive a COVID-19 vaccine [9,19,21,39,40,46,47,53,56,57,62,63,72]. Kreps et al. stated that vaccine history was the most important predictor of COVID-19 vaccination intention [19].

For the remaining constructs, vaccine price was also a determinant of vaccine intention studied in many articles. The trends from the studies show that lower vaccine price is correlated with higher willingness to vaccinate, although it may not be the most significant factor [55,61,63,66]. Additionally, concerns surrounding the impact of the speed of development on the safety and efficacy of the vaccines were reported to be an explanatory factor for vaccine hesitancy among participants [51], although participants from an Australian study preferred the vaccine to be available in a shorter period [61]. The vaccine’s country of origin was also examined in several studies. Two studies conducted among U.S. adults revealed a strong public preference for a domestically manufactured COVID-19 vaccine (U.S.) rather than an imported one [19,56]. Surprisingly, vaccine preferences were heterogeneous in China; the Chinese population in one study showed a higher willingness to receive a foreign made rather than a national vaccine [63], while another study reported conflicting results [69].

Health-Related Perceptions

High risk of COVID-19 infection and fear about COVID-19 were mentioned in the greatest number of studies. Overall, those who perceived a high risk of COVID-19 infection were associated with a higher likelihood of accepting COVID-19 vaccination [9,25,28,39,40,46,51,55,64,66]. According to a cross-sectional study conducted in Saudi Arabia, those who had a higher perceived risk of infection were 2.13 times more likely to receive a vaccination compared to those with a lower perceived risk [25]. Health history/medical history, insurance coverage, and contact with COVID-19 cases were also significant factors impacting vaccination intentions. Wang et al. found that those with chronic conditions were more likely to have the intention to receive a COVID-19 vaccine [57]. A different study by Grüner et al. found that individuals who were immunocompromised or had family with compromised immune systems were more likely to intend to be vaccinated [26]. Moreover, individuals without health insurance were less likely to vaccinate, whereas those with private health insurance were more likely to vaccinate [21,45,50,56,73,75]. Finally, being sick with COVID-19, and trust in homeopathy and naturopathy, were not well supported in the examined literature. A cross-sectional study conducted in the USA found that being sick with COVID-19 was associated with an increased likelihood of intention to vaccinate [45]. In contrast, a cross-sectional study conducted in Germany reported that trust in homeopathy and naturopathy was associated with a lower likelihood of intention to vaccinate [26].

Perceived Barriers

Perceived barriers decrease the likelihood of vaccination and negatively impact vaccination beliefs and attitudes. In this category, there are four constructs, consisting of financial barriers, lack of trust, misinformation, and concerns about commercial profiteering. With respect to misinformation, Roozenbeek et al. administered a cross-sectional study in Ireland, the USA, Spain, Mexico, and the UK, finding that increased susceptibility to misinformation decreased compliance with health guidance, willingness to vaccinate, and likelihood to recommend the vaccine to vulnerable friends and family [65]. Furthermore, being exposed to information about COVID-19 on social media was correlated with higher susceptibility to misinformation in Ireland, the UK, and the USA [65]. Additionally, lack of trust was associated with lower intention to vaccinate [20,21,51]. According to a cross-sectional study from the USA, lack of trust was the second most common reason for responding “no” towards vaccination intention. In this study, lack of trust encompassed lack of trust towards vaccines, the government and the CDC, pharmaceutical companies, and vaccine development or testing processes, as well as reference to conspiracy theories [21]. In relation to financial barriers, 6.17% of participants in a study from the USA stated they would omit vaccination due to lack of financial resources [50]. Concerns about commercial profiteering were correlated with lower intention to vaccinate [44]. However, both financial barriers and concerns about commercial profiteering were poorly mentioned in the literature, since only one study examined each.

Vaccine Recommendations

Previous studies showed that a recommendation by a health professional/scientist increased the likelihood of vaccination [27,44,45,46,60]. A study in the USA showed that the percentage of adults who were more likely to get the vaccine increased from 56.6% to 61.8% if they received a recommendation from their healthcare providers [43]. Likewise, Reiter et al. found that 73% of participants responded that a doctor’s recommendation would be an important factor in their vaccination decisions [45]. Another cross-sectional study conducted in China found that those who valued their doctor’s recommendation were more likely to receive a COVID-19 vaccine as soon as possible [46]. Furthermore, Leng et al. found a positive correlation between willingness to take the vaccine and the proportion of acquaintances—including friends and family—being vaccinated [55]. Concerning the impact of government advice to vaccinate, Bokemper et al. found that endorsement by political leaders has a polarized effect, where there is an increase in vaccine confidence among supporters of that party. Among supporters of a different political party, the endorsement by political leaders tends to be ignored, or even undermine vaccine confidence [67]. However, the impact of government advice to vaccinate was only found to be significant in one out of two studies examined; therefore, this factor was poorly mentioned in the literature.

4. Discussion

This is the first comprehensive scoping review describing demographic, social, and contextual factors associated with COVID-19 vaccination. It enables the identification of factors related to COVID-19 vaccine acceptance, refusal, and hesitancy among adults (18–60 years). Seven interconnected themes on the basis of our modified health belief model framework were identified, including demographics, social factors, vaccination beliefs and attitudes, vaccine-related perceptions, health-related perceptions, perceived barriers, and vaccine recommendations. The adoption of the health belief model was uniquely modified in this review, as some of the original categories were replaced by others to fit appropriately with our research question. Demographic variables were used as a separate category that interacted with the HBM as well as the social influences category. These two categories were considered to be important factors that influence health behaviors, such as an individual’s perceived threat of sickness or disease, or even a new treatment. Meanwhile, the six main components of the HBM—perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy—were renamed and classified into five themes under a major category termed “contextual factors”. Perceived susceptibility and perceived severity (which are the two dimensions of “threat”) were combined and referred to as “health-related perceptions”. The perceived benefits concept was replaced with vaccine-related perceptions, while cues to action was substituted for vaccine recommendations. In addition to this, the vaccination beliefs and attitudes category was added to investigate more related factors in-depth, as this category can act as a surrogate for self-efficacy within the primary HBM.

In our review, both demographic and contextual factors were mentioned in nearly 96% (46/48) of the reviewed articles, whereas social factors were only reported in 75% (36/48) of the chosen articles. In line with findings from previous reviews, our scoping review showed a wide variability in the rates of COVID-19 vaccine acceptance, refusal, and hesitancy across different countries and subgroups, including healthcare providers and parents [29,30]. However, a relatively high tendency toward acceptance was observed in China, European countries, and North American countries. In contrast, the lowest acceptance rates were reported in the Democratic Republic of Congo, followed by Malaysia. Moreover, a recent study reported high refusal and hesitancy rates among the Middle Eastern population [77]. This could be explained by the lack of transparent health communication and effective tools in the developing countries, which are needed to reformulate the decision-making process and to provide a better understanding of the benefits and risks of vaccination, thus facilitating optimal vaccine uptake [78]. Other explanations could be related to several misconceptions that work against vaccination in developing countries. For instance, there are such socio-cultural issues in some societies, as they believe that the vaccines are given to developing countries because they have excessive production of children, and that this is a way to make them infertile (the infertility myth). Another misconception is that pharmaceutical companies encourage politicians to convince people to take vaccines in order to achieve their own financial benefits. Notably, these misconceptions arise from the notion of politicization—especially during the COVID-19 pandemic—and the poor communication between scientists and the general population.

In this review, the underlying factors that influence the intention to receive COVID-19 vaccines varied significantly by national- and the individual-level preferences, and were attributed to complex socio-demographic, psychological, and contextual influences. Demographic variables such as age and gender were the most reported factors, but also the most inconsistent predictors of COVID-19 vaccination. Although most of the included studies showed that men and older individuals were more willing to get vaccinated [38,40,53,58,62,65,72], a few studies reported the opposite results, as women and younger adults showed stronger intention to receive a vaccine [54,63,73,75]. Men are usually seen as being more receptive to vaccines than women because of some barriers and social norms that affect women and their decisions. Justifications for such a situation were reported by the WHO SAGE group, as women—most of the time—considered themselves responsible for the consequences of their decisions on their families which, in turn, decreases their confidence in the use of immunization services [79]. In addition, the control of women’s mobility by other family members, their education level, gender inequality, women’s disempowerment, and poverty alleviation are all correlated with women’s concerns about accessing healthcare and, therefore, associated with their decision making in the context of vaccination status [79]. Generally, older adults are more concerned about being infected with COVID-19 because they believe that they are more likely to require hospitalization if they contract COVID-19. In addition, the risk of COVID-19 infection and death increases with age group, which affects older adults’ decisions about getting vaccinated. In contrast, low risk perception and the perception of safety around healthy young adults discourage them from getting vaccinated [59]. Healthcare workers were also found to have higher acceptance rates than other professions because they are the first line of defense in combating the virus and, thus, most susceptible to being infected [22,26,38,58,73]. Interestingly, other demographic factors such as education level, race, and income levels were consistent across many studies. People with low educational levels, Black ethnicity, and low income levels were generally less likely to take the vaccines [19,21,43,45,47,50,51,61]. Health disparities that relate to these demographic and racial issues are a factor in the lower vaccine acceptance rate. Thus, overcoming these racial inequalities and disparities will be key to distributing COVID-19 vaccines among various communities. These disadvantaged and minority groups should be prioritized in the vaccine distribution process to improve equity.

With respect to the sources from which people get their knowledge about COVID-19, we noted a dichotomy of two major sources through the studies: The first group of people rely on trusted information from either the government, the CDC, or the WHO [19,53,55]. In comparison, the second group use social media as their primary source of information [26,62,68]. Our findings allude to the significance of source selection, as it can be associated with the likelihood to accept or refuse the vaccine. The problem of the misinformation and fake news from social media is considered to be one the biggest barriers that stand against building trust between scientific research and the general population [65]. Uniquely, our review emphasizes the effect of socio-political factors on attitudes towards the vaccines. Based on previous studies that indicated that people’s ideologies and worldviews strongly influence their perceptions and acceptance of risk, our findings investigated the effects of political leaning on the intention to receive COVID-19 vaccines [19,53,55,80,81]. In line with the findings of a nationally representative survey in the U.S. about vaccinations for flu, pertussis, and measles, our study showed that political conservatives were less likely to get vaccinated than liberals [80]. The reason for this could be that conservatives’ leaders have publicly and repeatedly expressed anti-vaccination opinions in their attempts to link childhood vaccines to autism [82]. Many studies in this review point to the major role of the government in making COVID-19 vaccination one of the leading public health interventions [26,53,62,67]. Moreover, among the main social influencers to get the vaccine are family, friends, and healthcare providers. Most of the studies emphasized the role of family and peers in convincing individuals to accept COVID-19 vaccines [27,46,60,66,69]. As a result, healthcare providers can help with the implementation of COVID-19 vaccine programs to increase the vaccination coverage rates for their patients.

A number of contextual variables have been associated with people’s behaviors with regards to COVID-19 vaccination. While there is an overlap between the constructs related to vaccination beliefs and attitudes, health-related perceptions, and other constructs, these factors are tightly bound to vaccine acceptance, refusal, and hesitancy. Vaccine efficacy/effectiveness, vaccine safety, and adverse vaccine side effects are the most influential factors that affect people’s willingness to vaccinate [9,21,27,39,46,47,50,51,57]. Consistent findings were observed in a systematic review concerning the flu vaccine [83]. There was a general consensus among all of the included studies that influenza vaccination history was a strong motivator to accept a COVID-19 vaccine [9,21,39,46,47,57]. On the other hand, the speed of developing COVID-19 vaccines was an impediment to their acceptance [9,44,51,60,61]. Although clinical trials have maintained rigorous testing, many individuals are still concerned about the speed of vaccine development and its impact on the vaccines’ efficacy and safety [9,44,51,60,61]. Of note, the distrust in healthcare systems was another crucial factor that determined the choice of many to be vaccinated or not [20,21,51]. Many previous studies have assigned the responsibility for vaccine hesitancy to conspiracy beliefs, which were substantially and negatively related to the intention to be vaccinated against COVID-19 [20,21,49,51,65]. These beliefs revolve around the politicization of COVID-19, the fabrication of vaccine safety data, the manufacturing of antibody testing to harvest people’s DNA, and the harmful effects of vaccines on children, resulting in the erosion of people’s trust [20,21,49,51,65]. Child protection was found to be the primary reason that parents were more hesitant to vaccinate their children than themselves [60]. Hence, our findings indicate the necessity of increasing parents’ knowledge about the vaccines by ensuring effective communication between the parents and their healthcare providers.

Notably, a number of studies documented that people feel the need to take the vaccines to protect themselves, their families, and their communities from catching the virus [26,60,62,64,68]. Thus, it is considered critical to enhance the notion of the prosocial benefits of vaccination and herd immunity among people to strengthen their intentions to vaccinate [48]. Accordingly, this can help to reduce the transmission of the disease not only at the individual level, but also in the community as whole. Only a handful of studies have attempted to establish a correlation between testing positive for COVID-19 and the intention to be vaccinated against it, and the results have been ambiguous. Callaghan et al. found that individuals who have been tested for COVID-19 are 68% less likely to refuse vaccination [50], while similar findings were reported by Reiter et al. [45]. Conversely, results from another two surveys reported that being infected with COVID-19 was not significantly associated with willingness to take the vaccines [39,69]. One possible explanation is that people who have been infected with COVID-19 assume that they now have a natural immunity against COVID-19, with a lower chance of getting infected again, thus making them less inclined to take the vaccines. Lastly, it is worth mentioning that the origin of vaccine manufacturing seems to affect people’s inclinations to take or refuse the vaccine. Strong preference was observed for receiving a U.S.-made vaccine rather than a Chinese one [19,56,63]. Interestingly, a previous study indicated public skepticism with regards to the effectiveness of nationally manufactured health products in China [84].

Strengths and Limitations

Our review enabled us to conceptualize the influence of demographic, social, political, and contextual variables on acceptance of COVID-19 vaccines by using a comprehensive framework built on the constructs of the health belief model. This enhances our findings to generate more in-depth explanations and better describe the landscape of the studied phenomena compared to previous reviews. Moreover, we used an exhaustive search strategy including possible keywords and MeSH terms that related to our research question, which allowed us to cover a large number of the relevant studies tackling the subject of this review. It is also important to note that even though our topic focused on the intention to use COVID-19 vaccines, high terminological diversity—including vaccine hesitancy, acceptance, willingness, and refusal—was utilized in the screening process. However, the results of this scoping review should be interpreted with caution, since it still has some limitations. First, most of the included studies were conducted before the authorization of any COVID-19 vaccine; therefore, people’s opinions may have changed over time, particularly during this unstable pandemic. Second, we excluded non-peer-reviewed literature such as public opinions and grey literature, which previous studies have suggested should be used within reviews to foster a balanced picture of available evidence. Third, using a modified health belief model with modified components rather than the original one could result—unintentionally—in ignoring some of the important factors that relate to our research question. Fourth, no quality assessment was conducted, as would be the case in systematic reviews. Finally, literature that was not written in English was excluded, which could result in reducing the quality and the generalizability of the results.

5. Conclusions

Vaccine hesitancy is a serious challenge in the fight against COVID-19, because attaining herd immunity is dependent on the vaccines’ effectiveness and the population’s intention to accept them. Our review offered an overview of various factors, themes, and constructs associated with intention to vaccinate against COVID-19 among adult populations. Consistent with the literature, demographic, social, and contextual factors are likely to play major roles in any targeted vaccination programs, especially COVID-19 vaccination. Multiple factors—including age, gender, education level, race/ethnicity, vaccine safety and effectiveness, perceived disease risk, influenza vaccination history, and vaccine recommendations by health professionals—could influence people’s intentions and, ultimately, their decisions to accept COVID-19 vaccines or not. It is possible that it is not only misinformation that affects people’s decisions to reject vaccines, but also the lack of tools with which to restructure the decision-making process and provide a clearer understanding of the vaccines’ benefits and risks. Therefore, our research suggests focusing on developing strategies to promote the intention to get vaccinated against COVID-19 and to overcome vaccine hesitancy and refusal. One potential strategy could be to increase the transparency of communication between the researchers and the general population, considering the wide variations in public beliefs about the vaccine efficacy and safety. Furthermore, the media—and especially social media—will play a key role in shaping and manipulating public attitudes to COVID-19 vaccination. Thus, it could be very effective to engage social media to establish vaccine confidence and share positive examples of vaccine acceptance. Finally, educational programs can be also considered as an effective intervention to portray the potentially serious illness that could develop from COVID-19. Subsequently, it is recommended that health authorities supplement these programs using evidence-based cues to increase people’s awareness about COVID-19 vaccines.

Acknowledgements

AcknowledgmentsWe are thankful to Jackie Stapleton for her continuous support and help with the review.

Competing interests

Conflicts of InterestThe authors declare no conflict of interest.

References

  1. Smallpox-WHO|World Health Organization. 1981
  2. Hussain A., Ali S., Ahmed M., Hussain S.. The Anti-vaccination Movement: A Regression in Modern Medicine. Cureus. 2018 doi:10.7759/cureus.2919 PubMed
  3. DeStefano F., Thompson W.W.. MMR vaccine and autism: An update of the scientific evidence. Expert Rev. Vaccines. 2004 doi:10.1586/14760584.3.1.19 PubMed
  4. Farrington C., Miller E., Taylor B.. MMR and autism: Further evidence against a causal association. Vaccine. 2001 doi:10.1016/S0264-410X(01)00097-4 PubMed
  5. Fombonne E., Chakrabarti S.. No evidence for a new variant of measles-mumps-rubella–induced autism. Pediatrics. 2001 doi:10.1542/peds.108.4.e58 PubMed
  6. Taylor B., Miller E., Farrington C., Petropoulos M.C., Favot-Mayaud I., Li J. et al. Autism and measles, mumps, and rubella vaccine: No epidemiological evidence for a causal association. Lancet. 1999 doi:10.1016/S0140-6736(99)01239-8 PubMed
  7. Lane S., MacDonald N.E., Marti M., Dumolard L.. Vaccine hesitancy around the globe: Analysis of three years of WHO/UNICEF Joint Reporting Form data-2015–2017. Vaccine. 2018 doi:10.1016/j.vaccine.2018.03.063 PubMed
  8. MacDonald N.E.. Vaccine hesitancy: Definition, scope and determinants. Vaccine. 2015 doi:10.1016/j.vaccine.2015.04.036 PubMed
  9. Dror A.A., Eisenbach N., Taiber S., Morozov N.G., Mizrachi M., Zigron A. et al. Vaccine hesitancy: The next challenge in the fight against COVID-19. Eur. J. Epidemiol.. 2020 doi:10.1007/s10654-020-00671-y PubMed
  10. Sohrabi C., Alsafi Z., O’Neill N., Khan M., Kerwan A., Al-Jabir A. et al. World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19). Int. J. Surg.. 2020 doi:10.1016/j.ijsu.2020.02.034 PubMed
  11. Pfizer-BioNTech COVID-19 Vaccine. 2021
  12. Novel Coronavirus (‎2019-nCoV)‎: Situation Report, 3. 2020
  13. Draft Landscape and Tracker of COVID-19 Candidate Vaccines
  14. More than 150 Countries Engaged in COVID-19 Vaccine Global Access Facility. 2020
  15. Sharma O., Sultan A.A., Ding H., Triggle C.R.. A Review of the Progress and Challenges of Developing a Vaccine for COVID-19. Front. Immunol.. 2020 doi:10.3389/fimmu.2020.585354 PubMed
  16. Megget K.. Even covid-19 can’t kill the anti-vaccination movement. BMJ. 2020 doi:10.1136/bmj.m2184 PubMed
  17. Burki T.. The online anti-vaccine movement in the age of COVID-19. Lancet Digit. Health. 2020 doi:10.1016/S2589-7500(20)30227-2 PubMed
  18. Ritchie H., Ortiz-Ospina E., Beltekian D., Mathieu E., Hasell J., Macdonald B. et al. Statistics and Research: Coronavirus (COVID-19) Vaccinations
  19. Kreps S., Prasad S., Brownstein J.S., Hswen Y., Garibaldi B.T., Zhang B. et al. Factors Associated with US Adults’ Likelihood of Accepting COVID-19 Vaccination. JAMA Netw. Open. 2020 doi:10.1001/jamanetworkopen.2020.25594 PubMed
  20. Prati G.. Intention to receive a vaccine against SARS-CoV-2 in Italy and its association with trust, worry and beliefs about the origin of the virus. Health Educ. Res.. 2020 doi:10.1093/her/cyaa043 PubMed
  21. Fisher K.A., Bloomstone S.J., Walder J., Crawford S., Fouayzi H., Mazor K.M.. Attitudes toward a potential SARS-CoV-2 vaccine: A survey of US adults. Ann. Intern. Med.. 2020 doi:10.7326/M20-3569 PubMed
  22. Grech V., Gauci C., Agius S.. Withdrawn: Vaccine hesitancy among Maltese Healthcare workers toward influenza and novel COVID-19 vaccination. Early Hum. Dev.. 2020 doi:10.1016/j.earlhumdev.2020.105213 PubMed
  23. Olagoke A.A., Olagoke O., Hughes A.M.. Intention to Vaccinate Against the Novel 2019 Coronavirus Disease: The Role of Health Locus of Control and Religiosity. J. Relig. Health. 2021 doi:10.1007/s10943-020-01090-9 PubMed
  24. Kose S., Mandiracioglu A., Sahin S., Kaynar T., Karbus O., Ozbel Y.. Vaccine hesitancy of the COVID-19 by health care personnel. Int. J. Clin. Pr.. 2021 doi:10.1111/ijcp.13917
  25. Al-Mohaithef M., Padhi B.K.. Determinants of COVID-19 Vaccine Acceptance in Saudi Arabia: A Web-Based National Survey. J. Multidiscip. Health. 2020 doi:10.2147/JMDH.S276771 PubMed
  26. Grüner S., Krüger F.. The intention to be vaccinated against COVID-19: Stated preferences before vaccines were available. Appl. Econ. Lett.. 2020 doi:10.1080/13504851.2020.1854445
  27. Khan S., Rahman C.K.F., Haritha C.V., Bosco J., Ruchi T., Kuldeep D.. COVID-19 Vaccine Acceptance: Beliefs and Barriers Associated with Vaccination among the General Population in India. J. Exp. Biol. Agric. Sci.. 2020 doi:10.18006/2020.8(spl-1-sars-cov-2).s210.s218
  28. Harapan H., Wagner A.L., Yufika A., Winardi W., Anwar S., Gan A.K. et al. Acceptance of a COVID-19 Vaccine in Southeast Asia: A Cross-Sectional Study in Indonesia. Front. Public Health. 2020 doi:10.3389/fpubh.2020.00381 PubMed
  29. Sallam M.. COVID-19 Vaccine Hesitancy Worldwide: A Concise Systematic Review of Vaccine Acceptance Rates. Vaccines. 2021 doi:10.3390/vaccines9020160 PubMed
  30. Lin C., Tu P., Beitsch L.M.. Confidence and Receptivity for COVID-19 Vaccines: A Rapid Systematic Review. Vaccines. 2020 doi:10.3390/vaccines9010016 PubMed
  31. Gusenbauer M., Haddaway N.R.. Which academic search systems are suitable for systematic reviews or meta-analyses? Evaluating retrieval qualities of Google Scholar, PubMed, and 26 other resources. Res. Synth. Methods. 2020 doi:10.1002/jrsm.1378 PubMed
  32. Piasecki J., Waligora M., Dranseika V.. Google Search as an Additional Source in Systematic Reviews. Sci. Eng. Ethic.. 2017 doi:10.1007/s11948-017-0010-4 PubMed
  33. Yang R., Penders B., Horstman K.. Addressing Vaccine Hesitancy in China: A Scoping Review of Chinese Scholarship. Vaccines. 2019 doi:10.3390/vaccines8010002 PubMed
  34. Shmueli L.. Predicting intention to receive COVID-19 vaccine among the general population using the health belief model and the theory of planned behavior model. BMC Public Health. 2021 doi:10.1186/s12889-021-10816-7 PubMed
  35. Shahnazi H., Ahmadi-Livani M., Pahlavanzadeh B., Rajabi A., Hamrah M.S., Charkazi A.. Assessing preventive health behaviors from COVID-19: A cross sectional study with health belief model in Golestan Province, Northern of Iran. Infect. Dis. Poverty. 2020 doi:10.1186/s40249-020-00776-2 PubMed
  36. Kan T., Zhang J.. Factors influencing seasonal influenza vaccination behaviour among elderly people: A systematic review. Public Health. 2018 doi:10.1016/j.puhe.2017.12.007 PubMed
  37. La Vecchia C., Negri E., Alicandro G., Scarpino V.. Attitudes towards influenza vaccine and a potential COVID-19 vaccine in Italy and differences across occupational groups, September 2020. Med. Lav.. 2020 doi:10.23749/mdl.v111i6.10813 PubMed
  38. Kabamba Nzaji M., Kabamba Ngombe L., Ngoie Mwamba G., Banza Ndala D.B., Mbidi Miema J., Lungoyo C.L. et al. Acceptability of Vaccination Against COVID-19 Among Healthcare Workers in the Democratic Republic of the Congo. Pragmatic Obs. Res.. 2020 doi:10.2147/POR.S271096 PubMed
  39. Sherman S.M., Smith L.E., Sim J., Amlôt R., Cutts M., Dasch H. et al. COVID-19 vaccination intention in the UK: Results from the COVID-19 vaccination acceptability study (CoVAccS), a nationally representative cross-sectional survey. Hum. Vaccines Immunother.. 2021 doi:10.1080/21645515.2020.1846397 PubMed
  40. Gagneux-Brunon A., Detoc M., Bruel S., Tardy B., Rozaire O., Frappe P. et al. Intention to get vaccinations against COVID-19 in French healthcare workers during the first pandemic wave: A cross-sectional survey. J. Hosp. Infect.. 2021 doi:10.1016/j.jhin.2020.11.020 PubMed
  41. Arksey H., O’Malley L.. Scoping studies: Towards a methodological framework. Int. J. Soc. Res. Methodol.. 2005 doi:10.1080/1364557032000119616
  42. Zhang X., Tan R., Lam W.C., Yao L., Wang X., Cheng C.W. et al. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Extension for Chinese Herbal Medicines 2020 (PRISMA-CHM 2020). Am. J. Chin. Med.. 2020 doi:10.1142/S0192415X20500639 PubMed
  43. Head K.J., Kasting M.L., Sturm L.A., Hartsock J.A., Zimet G.D.. A National Survey Assessing SARS-CoV-2 Vaccination Intentions: Implications for Future Public Health Communication Efforts. Sci. Commun.. 2020 doi:10.1177/1075547020960463 PubMed
  44. Taylor S., Landry C.A., Paluszek M.M., Groenewoud R., Rachor G.S., Asmundson G.J.G.. A Proactive Approach for Managing COVID-19: The Importance of Understanding the Motivational Roots of Vaccination Hesitancy for SARS-CoV2. Front. Psychol.. 2020 doi:10.3389/fpsyg.2020.575950 PubMed
  45. Reiter P.L., Pennell M.L., Katz M.L.. Acceptability of a COVID-19 vaccine among adults in the United States: How many people would get vaccinated?. Vaccine. 2020 doi:10.1016/j.vaccine.2020.08.043 PubMed
  46. Wang J., Jing R., Lai X., Zhang H., Lyu Y., Knoll M.D. et al. Acceptance of COVID-19 Vaccination during the COVID-19 Pandemic in China. Vaccines. 2020 doi:10.3390/vaccines8030482 PubMed
  47. Biasio L.R., Bonaccorsi G., Lorini C., Pecorelli S.. Assessing COVID-19 vaccine literacy: A preliminary online survey. Hum. Vaccines Immunother.. 2021 doi:10.1080/21645515.2020.1829315 PubMed
  48. Jung H., Albarracín D.. Concerns for others increases the likelihood of vaccination against influenza and COVID-19 more in sparsely rather than densely populated areas. Proc. Natl. Acad. Sci. USA. 2021 doi:10.1073/pnas.2007538118 PubMed
  49. Bertin P., Nera K., Delouvée S.. Conspiracy Beliefs, Rejection of Vaccination, and Support for hydroxychloroquine: A Conceptual Replication-Extension in the COVID-19 Pandemic Context. Front. Psychol.. 2020 doi:10.3389/fpsyg.2020.565128 PubMed
  50. Callaghan T., Moghtaderi A., Lueck J.A., Hotez P., Strych U., Dor A. et al. Correlates and disparities of intention to vaccinate against COVID-19. Soc. Sci. Med.. 2021 doi:10.1016/j.socscimed.2020.113638 PubMed
  51. Freeman D., Loe B.S., Chadwick A., Vaccari C., Waite F., Rosebrock L. et al. COVID-19 vaccine hesitancy in the UK: The Oxford coronavirus explanations, attitudes, and narratives survey (Oceans) II. Psychol. Med.. 2020 doi:10.1017/s0033291720005188 PubMed
  52. Salali G.D., Uysal M.S.. COVID-19 vaccine hesitancy is associated with beliefs on the origin of the novel coronavirus in the UK and Turkey. Psychol. Med.. 2020 doi:10.1017/S0033291720004067 PubMed
  53. Malik A.A., McFadden S.M., Elharake J., Omer S.B.. Determinants of COVID-19 vaccine acceptance in the US. EClinicalMedicine. 2020 doi:10.1016/j.eclinm.2020.100495 PubMed
  54. Kwok K.O., Li K.-K., Wei W.I., Tang A., Wong S.Y.S., Lee S.S.. Influenza vaccine uptake, COVID-19 vaccination intention and vaccine hesitancy among nurses: A survey. Int. J. Nurs. Stud.. 2021 doi:10.1016/j.ijnurstu.2020.103854 PubMed
  55. Leng A., Maitland E., Wang S., Nicholas S., Liu R., Wang J.. Individual preferences for COVID-19 vaccination in China. Vaccine. 2021 doi:10.1016/j.vaccine.2020.12.009 PubMed
  56. Pogue K., Jensen J.L., Stancil C.K., Ferguson D.G., Hughes S.J., Mello E.J. et al. Influences on Attitudes Regarding Potential COVID-19 Vaccination in the United States. Vaccines. 2020 doi:10.3390/vaccines8040582 PubMed
  57. Wang K., Wong E.L.Y., Ho K.F., Cheung A.W.L., Chan E.Y.Y., Yeoh E.K. et al. Intention of nurses to accept coronavirus disease 2019 vaccination and change of intention to accept seasonal influenza vaccination during the coronavirus disease 2019 pandemic: A cross-sectional survey. Vaccine. 2020 doi:10.1016/j.vaccine.2020.09.021 PubMed
  58. Detoc M., Bruel S., Frappe P., Tardy B., Botelho-Nevers E., Gagneux-Brunon A.. Intention to participate in a COVID-19 vaccine clinical trial and to get vaccinated against COVID-19 in France during the pandemic. Vaccine. 2020 doi:10.1016/j.vaccine.2020.09.041 PubMed
  59. Palamenghi L., Barello S., Boccia S., Graffigna G.. Mistrust in biomedical research and vaccine hesitancy: The forefront challenge in the battle against COVID-19 in Italy. Eur. J. Epidemiol.. 2020 doi:10.1007/s10654-020-00675-8 PubMed
  60. Bell S., Clarke R., Mounier-Jack S., Walker J.L., Paterson P.. Parents’ and guardians’ views on the acceptability of a future COVID-19 vaccine: A multi-methods study in England. Vaccine. 2020 doi:10.1016/j.vaccine.2020.10.027 PubMed
  61. Borriello A., Master D., Pellegrini A., Rose J.M.. Preferences for a COVID-19 vaccine in Australia. Vaccine. 2021 doi:10.1016/j.vaccine.2020.12.032 PubMed
  62. Faasse K., Newby J.. Public Perceptions of COVID-19 in Australia: Perceived Risk, Knowledge, Health-Protective Behaviors, and Vaccine Intentions. Front. Psychol.. 2020 doi:10.3389/fpsyg.2020.551004 PubMed
  63. Dong D., Xu R.H., Wong E.L., Hung C., Feng D., Feng Z. et al. Public preference for COVID-19 vaccines in China: A discrete choice experiment. Health Expect.. 2020 doi:10.1111/hex.13140 PubMed
  64. Graffigna G., Palamenghi L., Boccia S., Barello S.. Relationship between Citizens’ Health Engagement and Intention to Take the COVID-19 Vaccine in Italy: A Mediation Analysis. Vaccines. 2020 doi:10.3390/vaccines8040576 PubMed
  65. Roozenbeek J., Schneider C.R., Dryhurst S., Kerr J., Freeman A.L.J., Recchia G. et al. Susceptibility to misinformation about COVID-19 around the world. R. Soc. Open Sci.. 2020 doi:10.1098/rsos.201199 PubMed
  66. Wong L.P., Alias H., Wong P.-F., Lee H.Y., Abubakar S.. The use of the health belief model to assess predictors of intent to receive the COVID-19 vaccine and willingness to pay. Hum. Vaccines Immunother.. 2020 doi:10.1080/21645515.2020.1790279 PubMed
  67. Bokemper S.E., Huber G.A., Gerber A.S., James E.K., Omer S.B.. Timing of COVID-19 vaccine approval and endorsement by public figures. Vaccine. 2021 doi:10.1016/j.vaccine.2020.12.048 PubMed
  68. Williams L., Gallant A.J., Rasmussen S., Nicholls L.A.B., Cogan N., Deakin K. et al. Towards intervention development to increase the uptake of COVID-19 vaccination among those at high risk: Outlining evidence-based and theoretically informed future intervention content. Br. J. Health Psychol.. 2020 doi:10.1111/bjhp.12468 PubMed
  69. Lin Y., Hu Z., Zhao Q., Alias H., Danaee M., Wong L.P.. Understanding COVID-19 vaccine demand and hesitancy: A nationwide online survey in China. PLoS Negl. Trop. Dis.. 2020 doi:10.1371/journal.pntd.0008961 PubMed
  70. Barello S., Nania T., Dellafiore F., Graffigna G., Caruso R.. ‘Vaccine hesitancy’ among university students in Italy during the COVID-19 pandemic. Eur. J. Epidemiol.. 2020 doi:10.1007/s10654-020-00670-z PubMed
  71. Grech V., Bonnici J., Zammit D.. Withdrawn: Vaccine hesitancy in Maltese family physicians and their trainees vis-à-vis influenza and novel COVID-19 vaccination. Early Hum. Dev.. 2020 doi:10.1016/j.earlhumdev.2020.105259 PubMed
  72. Grech V., Gauci C.. Withdrawn: Vaccine hesitancy in the University of Malta Faculties of Health Sciences, Dentistry and Medicine vis-à-vis influenza and novel COVID-19 vaccination. Early Hum. Dev.. 2020 doi:10.1016/j.earlhumdev.2020.105258 PubMed
  73. Akarsu B., Özdemir D.C., Baser D.A., Aksoy H., Fidancı I., Cankurtaran M.. While studies on COVID-19 vaccine is ongoing, the public’s thoughts and attitudes to the future COVID-19 vaccine. Int. J. Clin. Pr.. 2021 doi:10.1111/ijcp.13891 PubMed
  74. Marcec R., Majta M., Likic R.. Will vaccination refusal prolong the war on SARS-CoV-2?. Postgrad. Med. J.. 2020 doi:10.1136/postgradmedj-2020-138903 PubMed
  75. Guidry J.P., Laestadius L.I., Vraga E.K., Miller C.A., Perrin P.B., Burton C.W. et al. Willingness to get the COVID-19 vaccine with and without emergency use authorization. Am. J. Infect. Control. 2021 doi:10.1016/j.ajic.2020.11.018 PubMed
  76. Baumgaertner B., Ridenhour B.J., Justwan F., Carlisle J.E., Miller C.R.. Risk of disease and willingness to vaccinate in the United States: A population-based survey. PLoS Med.. 2020 doi:10.1371/journal.pmed.1003354 PubMed
  77. Al-Qerem W.A., Jarab A.S.. COVID-19 Vaccination Acceptance and Its Associated Factors among a Middle Eastern population. Front. Public Health. 2021 doi:10.3389/fpubh.2021.632914 PubMed
  78. Nachega J.B., Sam-Agudu N.A., Masekela R., van der Zalm M.M., Nsanzimana S., Condo J. et al. Addressing challenges to rolling out COVID-19 vaccines in African countries. Lancet Glob. Health. 2021 doi:10.1016/S2214-109X(21)00097-8 PubMed
  79. Gender and Immunisation: Summary Report for SAGE, November 2010, Basel
  80. Baumgaertner B., Carlisle J.E., Justwan F.. The influence of political ideology and trust on willingness to vaccinate. PLoS ONE. 2018 doi:10.1371/journal.pone.0191728 PubMed
  81. Zhang E.J., Chughtai A.A., Heywood A., MacIntyre C.R.. Influence of political and medical leaders on parental perception of vaccination: A cross-sectional survey in Australia. BMJ Open. 2019 doi:10.1136/bmjopen-2018-025866 PubMed
  82. Miller M., Miller M.E.. The GOP’s Dangerous “Debate” on Vaccines and Autism. 2015
  83. Yeung M.P.S., Lam F.L., Coker R.. Factors associated with the uptake of seasonal influenza vaccination in adults: A systematic review. J. Public Health. 2016 doi:10.1093/pubmed/fdv194 PubMed
  84. Zhou M., Qu S., Zhao L., Kong N., Campy K.S., Wang S.. Trust collapse caused by the Changsheng vaccine crisis in China. Vaccine. 2019 doi:10.1016/j.vaccine.2019.05.020 PubMed

Attribution. Bara’ Abdallah AlShurman, Amber Fozia Khan, Christina Mac, Meerab Majeed, Zahid Ahmad Butt. What Demographic, Social, and Contextual Factors Influence the Intention to Use COVID-19 Vaccines: A Scoping Review. International Journal of Environmental Research and Public Health (2021);18(17). doi:10.3390/ijerph18179342 © 2021 by the authors. Licensed under CC BY 4.0. Reproduced from the open-access article via Europe PMC (PubMed 34501932). Text, tables and references reproduced from the open-access article; figures and images are not reproduced and no wording was changed.

About this article

Journal
International Journal of Environmental Research and Public Health
Year
2021
Licence
CC BY 4.0
Source
Europe PMC
PubMed
34501932
Field
Immunology

EvidenceLib is a research-education resource, not medical advice. It does not diagnose, prescribe or recommend starting, stopping or changing any treatment. Talk to a qualified clinician about your own situation. Methods, sources and licences · Rights and removal requests · Legal · Support