Sociodemographic Determinants of COVID-19 Vaccine Hesitancy, Fear of Infection, and Protection Self-Efficacy

McElfish, Pearl A.; Willis, Don; Shah, Sumit K.; Bryant-Moore, Keneshia; Rojo, Martha; Selig, James P.

doi:10.1177/21501327211040746

Cited by 105 publications

(88 citation statements)

References 17 publications

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“…The present study found that people with high levels of fear of COVID-19 at waves 1 and 3 were more likely to be willing to receive a vaccine at wave 3. This finding is consistent with most studies that addressed this issue [ 15 , 22 , 26 , 27 , 41 , 46 – 48 , 54 ]. A typical characteristic of fear is that people tend to avoid what they fear.…”

Section: Discussionsupporting

confidence: 92%

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Association between COVID-19 vaccine hesitancy and generalized trust, depression, generalized anxiety, and fear of COVID-19

Sekizawa

Hashimoto²,

Denda

et al. 2022

BMC Public Health

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Background Although numerous studies have been published on the predictors of COVID-19 vaccine hesitancy, some possible predictors remain underexplored. In this study, we explored the associations of unwillingness and indecisiveness regarding COVID-19 vaccination with generalized trust, mental health conditions such as depression and generalized anxiety, and fear of COVID-19. Methods Data of wave 1 (from October 27 till November 6, 2020) and wave 3 (from April 23 till May 6, 2021) of a longitudinal online study conducted in Japan were used for the analyses. Unvaccinated participants were asked at wave 3 about their willingness to be vaccinated, with possible responses of willing, unwilling, or undecided. These three responses were used as the outcome variable, and multinomial logistic regression analyses were conducted with willingness to be vaccinated as the reference group. Explanatory variables included generalized trust, depression, generalized anxiety, and fear of COVID-19 both at wave 1 and 3, and sociodemographic and health-related variables. Results Of the 11,846 valid respondents, 209 (1.8%) answered that they had already been vaccinated against COVID-19, 7089 (59.8%) responded that they were willing to be vaccinated, 3498 (29.5%) responded that they were undecided, and 1053 (8.9%) responded that they were unwilling to be vaccinated. After adjusting for covariates, we found that: (1) participants with lower levels of generalized trust at wave 1 and 3 were more likely to be undecided or unwilling at wave 3; (2) respondents with moderately severe or severe depression at wave 1 and 3 were more likely to be undecided at wave 3; (3) participants with moderate or severe levels of generalized anxiety at wave 3 but not at wave 1 were more likely to be unwilling at wave 3; and (4) respondents with high levels of fear of COVID-19 at wave 1 and 3 were less likely to be undecided and unwilling at wave 3. Conclusions Generalized trust, mental health conditions such as depression and generalized anxiety, and low level of fear of COVID-19 are associated with unwillingness or indecision regarding being vaccinated against COVID-19.

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Section: Discussionsupporting

confidence: 92%

“…Regarding fear of COVID-19, several studies have already explored the association between fear of COVID-19 and vaccine hesitancy [ 15 , 22 , 26 , 27 , 41 , 46 – 48 ]. All of them except one [ 46 ] found that fear of COVID-19 was positively associated with willingness to be vaccinated against COVID-19.…”

Section: Introductionmentioning

confidence: 99%

Association between COVID-19 vaccine hesitancy and generalized trust, depression, generalized anxiety, and fear of COVID-19

Sekizawa

Hashimoto²,

Denda

et al. 2022

BMC Public Health

View full text Add to dashboard Cite

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“…Variables in the symbol column correspond to Equation 1 . INDEX DOMAIN INDICATOR SOURCE LEVEL SYMBOL NOTES REFERENCES SEVI 1 Jobseekers Allowance Rate NOMIS 1 MSOA v 1 6 , 11 , 12 1 Rank of Index of Multiple Deprivation (IMD) Gov.uk 2 LSOA v 2 Averaged over LSOAs within MSOA 6 , 12 , 13 , 14 , 15 1 Long term unemployment, per 100 population of working age† PHE Fingertips 6 MSOA v 3 6 , 11 , 12 , 16 2 Proportion population over 65 ONS 4 MSOA v 4 17 , 18 2 Ethnicity (% non-white population) * NOMIS 1 MSOA v 5 5 , 19 , 20 2 Household overcrowding* Gov.uk 2 LSOA v 6 Averaged over LSOAs within each MSOA 2 , 6 , 21 …”

Section: Methodsmentioning

confidence: 99%

“…These are similar to those characteristics found to be associated with vaccine hesitancy in other works from the UK and further afield. 10 , 11 …”

Section: Introductionmentioning

confidence: 99%

Static Socio-Ecological COVID-19 Vulnerability Index and Vaccine Hesitancy Index for England

Welsh

Sinclair

Matthews

2022

The Lancet Regional Health - Europe

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Background Population characteristics can be used to infer vulnerability of communities to COVID-19, or to the likelihood of high levels of vaccine hesitancy. Communities harder hit by the virus, or at risk of being so, stand to benefit from greater resource allocation than their population size alone would suggest. This study reports a simple but efficacious method of ranking small areas of England by relative characteristics that are linked with COVID-19 vulnerability and vaccine hesitancy. Methods Publicly available data on a range of characteristics previously linked with either poor COVID-19 outcomes or vaccine hesitancy were collated for all Middle Super Output Areas of England (MSOA, n=6790, excluding Isles of Scilly), scaled and combined into two numeric indices. Multivariable linear regression was used to build a parsimonious model of vulnerability (static socio-ecological vulnerability index, SEVI) in 60% of MSOAs, and retained variables were used to construct two simple indices. Assuming a monotonic relationship between indices and outcomes, Spearman correlation coefficients were calculated between the SEVI and cumulative COVID-19 case rates at MSOA level in the remaining 40% of MSOAs over periods both during and out with national lockdowns. Similarly, a novel vaccine hesitancy index (VHI) was constructed using population characteristics aligned with factors identified by an Office for National Statistics (ONS) survey analysis. The relationship between the VHI and vaccine coverage in people aged 12+years (as of 2021-06-24) was determined using Spearman correlation. The indices were split into quintiles, and MSOAs within the highest vulnerability and vaccine hesitancy quintiles were mapped. Findings The SEVI showed a moderate to strong relationship with case rates in the validation dataset across the whole study period, and for every intervening period studied except early in the pandemic when testing was highly selective. The SEVI was more strongly correlated with case rates than any of its domains ( r s 0·59 95% CI 0.57-0.62) and outperformed an existing MSOA-level vulnerability index. The VHI was significantly negatively correlated with COVID-19 vaccine coverage in the validation data at the time of writing ( r s -0·43 95% CI -0·46 to -0·41). London had the largest number and proportion of MSOAs in quintile 5 (most vulnerable/hesitant) of SEVI and VHI concurrently. Interpretation The indices presented offer an efficacious way of identifying geographical disparities in COVID-19 risk, thus helping focus resources according to need. Funding Funder: Integrated Covid Hub North East Award number n/a Grant recipient Fiona Matthews

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“…These are similar to those characteristics found to be associated with vaccine hesitancy in other works from the UK and further afield. 10,11 Avoiding unchecked viral spread is important for reasons beyond the obvious need to safeguard life. COVID-19 infection comes with at least two additional major risks; the risk of inducing 'Long COVID' in a substantial proportion of patients, 12 and the risk of allowing yet more virulent or transmissible variants to emerge which may evade the current vaccines.…”

Section: Introductionmentioning

confidence: 99%

Static Socio-Ecological COVID-19 Vulnerability Index and Vaccine Hesitancy Index for England

2021

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Background Population characteristics can be used to infer vulnerability of communities to COVID-19, or to the likelihood of high levels of vaccine hesitancy. Communities harder hit by the virus, or at risk of being so, stand to benefit from greater resource allocation than their population size alone would suggest. This study reports a simple but efficacious method of ranking small areas of England by relative characteristics that are linked with COVID-19 vulnerability and vaccine hesitancy.Methods Publicly available data on a range of characteristics previously linked with either poor COVID-19 outcomes or vaccine hesitancy were collated for all Middle Super Output Areas of England (MSOA, n=6790, excluding Isles of Scilly), scaled and combined into two numeric indices. Multivariable linear regression was used to build a parsimonious model of vulnerability (static socio-ecological vulnerability index, SEVI) in 60% of MSOAs, and retained variables were used to construct two simple indices. Assuming a monotonic relationship between indices and outcomes, Spearman correlation coefficients were calculated between the SEVI and cumulative COVID-19 case rates at MSOA level in the remaining 40% of MSOAs over periods both during and out with national lockdowns. Similarly, a novel vaccine hesitancy index (VHI) was constructed using population characteristics aligned with factors identified by an Office for National Statistics (ONS) survey analysis. The relationship between the VHI and vaccine coverage in people aged 12+years (as of 2021-06-24) was determined using Spearman correlation. The indices were split into quintiles, and MSOAs within the highest vulnerability and vaccine hesitancy quintiles were mapped. FindingsThe SEVI showed a moderate to strong relationship with case rates in the validation dataset across the whole study period, and for every intervening period studied except early in the pandemic when testing was highly selective. The SEVI was more strongly correlated with case rates than any of its domains (r s 0¢59 95% CI 0.57-0.62) and outperformed an existing MSOA-level vulnerability index. The VHI was significantly negatively correlated with COVID-19 vaccine coverage in the validation data at the time of writing (r s -0¢43 95% CI -0¢46 to -0¢41). London had the largest number and proportion of MSOAs in quintile 5 (most vulnerable/hesitant) of SEVI and VHI concurrently.Interpretation The indices presented offer an efficacious way of identifying geographical disparities in COVID-19 risk, thus helping focus resources according to need.

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Sociodemographic Determinants of COVID-19 Vaccine Hesitancy, Fear of Infection, and Protection Self-Efficacy

Cited by 105 publications

References 17 publications

Association between COVID-19 vaccine hesitancy and generalized trust, depression, generalized anxiety, and fear of COVID-19

Association between COVID-19 vaccine hesitancy and generalized trust, depression, generalized anxiety, and fear of COVID-19

Static Socio-Ecological COVID-19 Vulnerability Index and Vaccine Hesitancy Index for England

Static Socio-Ecological COVID-19 Vulnerability Index and Vaccine Hesitancy Index for England

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