The influence of pediatricians' recommendation on caregivers' COVID-19 vaccine acceptance for children: A nationwide cross-sectional survey study from USA.

Background: The influence of pediatricians on parental acceptance of COVID-19 vaccine for children has not been well studied. We designed a survey to estimate the impact of pediatricians' recommendations on caregivers' vaccine acceptance while accounting for participants' socio-demographic and personal characteristics. The secondary objectives were to compare childhood vaccination rates among different age groups and categorize caregivers' concerns about vaccinating young (under-five) children. Overall, the study aimed to provide insight into potential pro-vaccination strategies that could integrate pediatricians to alleviate parental vaccine hesitancy. Methods: We conducted an online cross-sectional survey study using Redcap, in August 2022. We enquired COVID-19 vaccination status of the children in the family (≥five years). The survey questionnaire included socio-demographic and personal characteristics: age, race, sex, education, financial status, residence, healthcare worker, COVID-19 vaccination status and side effects, children's influenza vaccination status, and pediatricians' recommendations (1-5 scale). Logistic regression and neural network models were used to estimate the influence of socio-demographic determinants on children's vaccine status and build predictors' ranking. Results: The participants (N = 2,622) were predominantly white, female, middle-class, and vaccinated against COVID-19 (89%). The logistic regression model was significant vs. the null (likelihood-ratio χ2 = 514.57, p < 0.001, pseudo-R2 = .440). The neural network model also demonstrated strong prediction ability with a correct prediction rates of 82.9% and 81.9% for the training and testing models, respectively. Both models identified pediatricians' recommendations, self-COVID-19 vaccination status, and post-vaccination side effects as dominant predictors of caregivers' vaccine acceptance. Among the pediatricians, 70.48% discussed and had an affirmative opinion about COVID-19 vaccine for children. Vaccine acceptance was lower for children aged 5-8 years compared to older age groups (9-12 and 13-18 years), and acceptance varied significantly among the three cohorts of children (χ2 = 65.62, p < 0.001). About half of the participants were concerned about inadequate availability of vaccine safety information for under-five children. Conclusions: Pediatricians' affirmative recommendation was significantly associated with caregivers' COVID-19 vaccine acceptance for children while accounting for participants' socio-demographic characteristics. Notably, vaccine acceptance was lower among younger compared to older children, and caregivers' uncertainty about vaccine safety for under-five children was prevalent. Thus, pro-vaccination strategies might incorporate pediatricians to alleviate parental concerns and optimize poor vaccination rate among under-five children.

The Upsurge of Impact Factors in Pediatric Journals Post COVID-19 Outbreak: A Cross-Sectional Study

Background Impact factor (IF) is a quantitative tool designed to evaluate scientific journals' excellence. There was an unprecedented upsurge in biomedical journals' IF in 2020, perhaps contributed by the increased number of publications since the COVID-19 outbreak. We conducted a cross-sectional study (2018–2020) to analyze recent trends in standard bibliometrics (IF, Eigenfactor, SNIP) of pediatric journals. We also estimated reference and publication counts of biomedical journals since publication volume determines the number of citations offered and IF. Methods Various bibliometrics of pediatric journals and reference/publication volumes of biomedical journals were compared between 2020 vs. 2019 and 2019 vs. 2018. We also compared open access (OA) and subscription journals' trends. Finally, we estimated IF changes in the journals of a different specialty, pulmonology. Results The study included 164 pediatric and 4,918 biomedical journals (OA = 1,473, subscription = 3,445). Pediatric journals' IFs had increased significantly in 2020 [median (IQR) = 2.35 (1.34)] vs. 2019 [1.82 (1.22)] (Wilcoxon: p-value < 0.001). IFs were unchanged between 2018 and 2019. Eigenfactor remained stable between 2018 and 2020, while SNIP increased progressively. Reference/publication volumes of biomedical journals escalated between 2018 and 2020, and OA journals experienced faster growth than subscription journals. IFs of pulmonary journals also increased considerably in 2020 vs. 2019. Conclusions We report an upsurge in pediatric journals' IF, perhaps contributed by a sudden increase in publication numbers in 2020. Therefore, considering this limitation, IF should be cautiously used as the benchmark of excellence. Unlike IF, Eigenfactor remained stable between 2018 and 2020. Similar changes in IF were also observed among the journals of another specialty, pulmonology.

The Influence of COVID-19 on Influenza and Respiratory Syncytial Virus Activities.

Background: Respiratory viral diseases have considerably declined since the COVID-19 outbreak, perhaps through influence by nonpharmaceutical interventions. We conducted a cross-sectional study using the CDC database to compare the pre- vs. post-pandemic flu activity (incidence) between the US states. Our secondary objectives were to estimate the association between flu activity and flu vaccination rates and compare the national trends of flu and RSV activities since the pandemic outbreak. Methods: We estimated the difference between pre-pandemic (April 2019-March 2020) and post-pandemic (April 2020-March 2021) flu activity between individual states using the Wilcoxon signed-rank test. The association between flu activity and immunization rates was also measured. Finally, parallel time trend graphs for flu and RSV activities were illustrated with a time series modeler. Results: The median (IQR) pre-pandemic flu activity was 4.10 (1.38), higher than the post-pandemic activity (1.38 (0.71)) (p-value < 0.001). There was no difference between pre-pandemic (45.50% (39.10%)) and post-pandemic (45.0% (19.84%)) flu vaccine acceptance (p-value > 0.05). Flu activity and vaccination rates were not associated (p-value > 0.05). Flu activity has declined since the COVID-19 outbreak, while RSV made a strong comeback in June 2021. Conclusion: Flu activity has significantly diminished throughout the pandemic while a sudden upsurge in RSV is a public health concern indicative of possible resurgence of other viruses. Flu vaccine acceptance neither changed during the pandemic nor influenced the diminished Flu activity.

Perceived Stress, Knowledge, and Preventive Behaviors in Indian versus US-based Participants During COVID-19: A Survey Study.

Rationale: India and the USA, the worst affected countries by COVID-19, experienced very different pandemic courses. By 2020, COVID-19 cases had steadily declined in India, whereas the fight continued in the US. The people of India and the USA perhaps perceived threats very differently, influenced by their knowledge, available healthcare facilities, and social security. We conducted an online survey study to compare COVID-related perceptions between Indian participants (IND-P) and US-based participants (US-P). Methods: COVID-related perceptions such as stress, knowledge, and preventive behaviors were measured with specific questionnaires, and normalized scores were computed. T-tests were used to compare the perception scores, while the Kruskal-Wallis-H (KWH) tests were used to compare socioeconomic distributions between participants from two countries. Generalized linear model (GLM) adjusted for sociodemographic confounders estimated the association between the country of residence and COVID-perception. Results: The IND-P (N = 242) were younger and male-dominated compared with the US-P (N = 531) (age: KWH = 97.37, p < 0.0001, gender: KWH = 140.38, p < 0.0001). Positive attitudes toward preventive guidelines were associated with higher perceived risk and stress (r = 0.35, p < 0.001, and r = 0.21, p < 0.001, respectively) but not with the knowledge (r = -0.05, p = 0.14). Compared with the US-P, the IND-P had lower knowledge (5.19 ± 1.95 vs. 7.82 ± 1.35; t-test: p < 0.0001), higher stress (7.01 ± 1.51 vs. 6.07 ± 1.61; t-test: p < 0.0001), and better adherence to preventive guidelines (8.84 ± 1.30 vs. 8.34 ± 2.09; t-test: p = 0.0006). GLM demonstrated a significant association between the country and COVID-perception scores. Conclusion: The IND-P experienced higher stress and perceived threat during COVID-19 than the US-P, perhaps due to a lack of faith in the healthcare system and insecurity. Despite lower knowledge, the IND-P had better acceptance of preventive guidelines than the US-P.

The Influence of Sociodemographic Heterogeneity on the Perceptions of COVID-19: A Countrywide Survey Study in the USA.

Background: Sociodemographic factors such as age, race, education, family income, and sex have been reported to influence COVID-related perceptions, reflected by knowledge, stress, and preventive behavior. We conducted a US-based survey to estimate the difference in COVID-related perceptions among diverse sociodemographic groups and the influence of sociodemographic heterogeneity on COVID-related perceptions. Methods: The survey enquired about sociodemographic parameters and relevant information to measure knowledge, stress, and preventive behavior. COVID-perception scores among sociodemographic subgroups were compared with ANOVA (Bonferroni). The general linear model (GLM) was used to estimate the association among sociodemographic factors and COVID-related perceptions. Results: Females (75%) and White participants (78%) were the predominant (N = 3734). Females, White participants, wealthy, and educated participants demonstrated better knowledge, while participants of minority races, younger ages, low incomes, and females experienced high stress. Females, African-Americans, and educated participants better adopted preventive behaviors. Race, family income, and sex were the highest contributors to the predictive model. Sociodemographic determinants had statistically significant associations with knowledge (F-score = 7.72, p < 0.001; foremost predictor: race), stress (F-score = 16.46, p < 0.001; foremost predictor: income), and preventive behavior (GLM: F-score = 7.72, p < 0.001, foremost predictor: sex). Conclusion: Sociodemographic heterogeneity significantly influenced COVID-related perceptions, while race, family income, and sex were the strongest determinants of COVID-related perceptions.

Sociodemographic predictors of COVID-19 vaccine acceptance: a nationwide US-based survey study.

OBJECTIVES: Acceptance of COVID-19 vaccination is attributable to sociodemographic factors and their complex interactions. Attitudes towards COVID-19 vaccines in the United States are changing frequently, especially since the launch of the vaccines and as the United States faces a third wave of the pandemic. Our primary objective was to determine the relative influence of sociodemographic predictors on COVID-19 vaccine acceptance. The secondary objectives were to understand the reasons behind vaccine refusal and compare COVID-19 vaccine acceptance with influenza vaccine uptake. STUDY DESIGN: This was a nationwide US-based survey study. METHODS: A REDCap survey link was distributed using various online platforms. The primary study outcome was COVID-19 vaccine acceptance (yes/no). Sociodemographic factors, such as age, ethnicity, gender, education, family income, healthcare worker profession, residence regions, local healthcare facility and 'vaccine launch' period (pre vs post), were included as potential predictors. The differences in vaccine acceptance rates among sociodemographic subgroups were estimated by Chi-squared tests, whereas logistic regression and neural networks computed the prediction models and determined the predictors of relative significance. RESULTS: Among 2978 eligible respondents, 81.1% of participants were likely to receive the vaccine. All the predictors demonstrated significant associations with vaccine acceptance, except vaccine launch period. Regression analyses eliminated gender and vaccine launch period from the model, and the machine learning model reproduced the regression result. Both models precisely predicted individual vaccine acceptance and recognised education, ethnicity and age as the most important predictors. Fear of adverse effects and concern with efficacy were the principal reasons for vaccine refusal. CONCLUSIONS: Sociodemographic predictors, such as education, ethnicity and age, significantly influenced COVID-19 vaccine acceptance, and concerns of side-effects and efficacy led to increased vaccine hesitancy.