Acceptance of COVID-19 Vaccination Among Health System Personnel.

JOURNAL OF THE AMERICAN BOARD OF FAMILY MEDICINE(2021)

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摘要
INTRODUCTION:One-third of the general public will not accept Coronavirus disease 2019 (COVID-19) vaccination but factors influencing vaccine acceptance among health care personnel (HCP) are not known. We investigated barriers and facilitators to vaccine acceptance within 3 months of regulatory approval (primary outcome) among adult employees and students at a tertiary-care, academic medical center. METHODS:We used a cross-sectional survey design with multivariable logistic regression. Covariates included age, gender, educational attainment, self-reported health status, concern about COVID-19, direct patient interaction, and prior influenza immunization. RESULTS:Of 18,250 eligible persons, 3,347 participated. Two in 5 (40.5%) HCP intend to delay (n = 1020; 30.6%) or forgo (n = 331; 9.9%) vaccination. Male sex (adjusted OR [aOR], 2.43; 95% confidence interval [CI], 2.00-2.95; P < .001), prior influenza vaccination (aOR, 2.35; 95% CI, 1.75-3.18; P < .001), increased concern about COVID-19 (aOR, 2.40; 95% CI, 2.07-2.79; P < .001), and postgraduate education (aOR, 1.41; 95% CI, 1.21-1.65; P < .001) - but not age, direct patient interaction, or self-reported overall health - were associated with vaccine acceptance in multivariable analysis. Barriers to vaccination included concerns about long-term side effects (n = 1197, 57.1%), safety (n = 1152, 55.0%), efficacy (n = 777, 37.1%), risk-to-benefit ratio (n = 650, 31.0%), and cost (n = 255, 12.2%).Subgroup analysis of Black respondents indicates greater hesitancy to accept vaccination (only 24.8% within 3 months; aOR 0.13; 95% CI, 0.08-0.21; P < .001). CONCLUSIONS:Many HCP intend to delay or refuse COVID-19 vaccination. Policymakers should impartially address concerns about safety, efficacy, side effects, risk-to-benefit ratio, and cost. Further research with minority subgroups is urgently needed.
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关键词
Academic Medical Centers, Acute Disease, Chronic Disease, COVID-19, Cross-Sectional Studies, Health Personnel, Linear Models, Logistic Models, Outpatients, Pandemics, Primary Health Care, Quality of Life, Self Report, Surveys and Questionnaires, Vaccination
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