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      Vaccine hesitancy and hesitant adoption among nursing students in Texas


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          As the state facing the second-largest nursing workforce shortage in the U.S. and low vaccination rates among residents early in the pandemic, Texas provided a unique opportunity to examine vaccine hesitancy and hesitant adoption among nursing students in an environment where state-level executive orders prohibited mandatory vaccinations.


          The purpose of this study was to describe the level of vaccine hesitancy and hesitant adoption among nursing students in the state of Texas. We used a convenient, opt-in, online survey of nursing students conducted between mid-April and mid-June 2022. The survey was distributed to all pre-licensure nursing programs in Texas.


          The majority of survey respondents (n = 599) were between the ages of 18–28 (68 %), female (88 %) and white (57 %). Most received at least one dose of the COVID-19 vaccination (84 %). Of those receiving the vaccine, a high proportion (82 %) were identified as hesitant adopters. Respondents cited concerns about side effects (57 %) most frequently as the reason for vaccine hesitancy.


          Given the worldwide nursing shortage, factors potentially impacting the future workforce, such as vaccine hesitancy and hesitant adoption, must be closely monitored. More research is needed to understand the concerns of nursing students and the motivations of hesitant and non-hesitant adopters.

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          Most cited references30

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          Vaccine hesitancy: Definition, scope and determinants.

          The SAGE Working Group on Vaccine Hesitancy concluded that vaccine hesitancy refers to delay in acceptance or refusal of vaccination despite availability of vaccination services. Vaccine hesitancy is complex and context specific, varying across time, place and vaccines. It is influenced by factors such as complacency, convenience and confidence. The Working Group retained the term 'vaccine' rather than 'vaccination' hesitancy, although the latter more correctly implies the broader range of immunization concerns, as vaccine hesitancy is the more commonly used term. While high levels of hesitancy lead to low vaccine demand, low levels of hesitancy do not necessarily mean high vaccine demand. The Vaccine Hesitancy Determinants Matrix displays the factors influencing the behavioral decision to accept, delay or reject some or all vaccines under three categories: contextual, individual and group, and vaccine/vaccination-specific influences.
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            COVID-19 vaccine acceptance and hesitancy in low- and middle-income countries

            Widespread acceptance of COVID-19 vaccines is crucial for achieving sufficient immunization coverage to end the global pandemic, yet few studies have investigated COVID-19 vaccination attitudes in lower-income countries, where large-scale vaccination is just beginning. We analyze COVID-19 vaccine acceptance across 15 survey samples covering 10 low- and middle-income countries (LMICs) in Asia, Africa and South America, Russia (an upper-middle-income country) and the United States, including a total of 44,260 individuals. We find considerably higher willingness to take a COVID-19 vaccine in our LMIC samples (mean 80.3%; median 78%; range 30.1 percentage points) compared with the United States (mean 64.6%) and Russia (mean 30.4%). Vaccine acceptance in LMICs is primarily explained by an interest in personal protection against COVID-19, while concern about side effects is the most common reason for hesitancy. Health workers are the most trusted sources of guidance about COVID-19 vaccines. Evidence from this sample of LMICs suggests that prioritizing vaccine distribution to the Global South should yield high returns in advancing global immunization coverage. Vaccination campaigns should focus on translating the high levels of stated acceptance into actual uptake. Messages highlighting vaccine efficacy and safety, delivered by healthcare workers, could be effective for addressing any remaining hesitancy in the analyzed LMICs. Survey data collected across ten low-income and middle-income countries (LMICs) in Asia, Africa and South America compared with surveys from Russia and the United States reveal heterogeneity in vaccine confidence in LMICs, with healthcare providers being trusted sources of information, as well as greater levels of vaccine acceptance in these countries than in Russia and the United States.
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              The Chi-square test of independence

              The Chi-square statistic is a non-parametric (distribution free) tool designed to analyze group differences when the dependent variable is measured at a nominal level. Like all non-parametric statistics, the Chi-square is robust with respect to the distribution of the data. Specifically, it does not require equality of variances among the study groups or homoscedasticity in the data. It permits evaluation of both dichotomous independent variables, and of multiple group studies. Unlike many other non-parametric and some parametric statistics, the calculations needed to compute the Chi-square provide considerable information about how each of the groups performed in the study. This richness of detail allows the researcher to understand the results and thus to derive more detailed information from this statistic than from many others. The Chi-square is a significance statistic, and should be followed with a strength statistic. The Cramer’s V is the most common strength test used to test the data when a significant Chi-square result has been obtained. Advantages of the Chi-square include its robustness with respect to distribution of the data, its ease of computation, the detailed information that can be derived from the test, its use in studies for which parametric assumptions cannot be met, and its flexibility in handling data from both two group and multiple group studies. Limitations include its sample size requirements, difficulty of interpretation when there are large numbers of categories (20 or more) in the independent or dependent variables, and tendency of the Cramer’s V to produce relative low correlation measures, even for highly significant results.

                Author and article information

                Prev Med Rep
                Preventive Medicine Reports
                13 January 2024
                February 2024
                13 January 2024
                : 38
                : 102612
                [a ]3380 College Park Drive, Suite 400, The Woodlands, TX 77384, USA
                [b ]TCU Box 298620, 2800 W. Bowie St., Fort Worth, TX 76129, USA
                Author notes
                [* ]Corresponding author. dmb116@ 123456shsu.edu
                S2211-3355(24)00027-5 102612
                © 2024 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                : 17 October 2023
                : 11 January 2024
                : 12 January 2024
                Regular article

                vaccine,covid-19,hesitancy,hesitant adoption,hesitant adopter,nursing student,workforce


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