scholarly journals Implications of Attitudes and Beliefs about COVID-19 vaccines for Vaccination Campaigns in the United States: a Latent Class Analysis

2021 ◽  
pp. 101584
Author(s):  
Kristin E. Schneider ◽  
Lauren Dayton ◽  
Saba Rouhani ◽  
Carl A. Latkin
Author(s):  
Bruce G Taylor ◽  
Weiwei Liu ◽  
Elizabeth A. Mumford

The purpose of this study is to understand the availability of employee wellness programs within law enforcement agencies (LEAs) across the United States, including physical fitness, resilience/wellness, coping skills, nutrition, mental health treatment, and substance use treatment. The research team investigated whether patterns of LEA wellness programming are identifiable and, if so, what characteristics describe these patterns. We assess using latent class analysis whether there are distinct profiles of agencies with similar patterns offering different types of wellness programs and explore what characteristics distinguish agencies with certain profiles of wellness programming. Data were from a nationally representative sample of 1135 LEAs: 80.1% municipal, 18.6% county and 1.3% other agencies (state-level and Bureau of Indian Affairs LEAs). We found that many agencies (62%) offer no wellness programming. We also found that 23% have comprehensive wellness programming, and that another group of agencies specialize in specific wellness programming. About 14% of the agencies have a high probability of providing resilience coping skill education, mental health and/or substance use treatment services programming. About 1% of the agencies in the United States limit their programming to fitness and nutrition, indicating that fitness and nutrition programs are more likely to be offered in concert with other types of wellness programs. The analyses revealed that agencies offering broad program support are more likely to be large, municipal LEAs located in either the West, Midwest or Northeast (compared with the southern United States), and not experiencing a recent budget cut that impacted wellness programming.


2017 ◽  
Vol 74 ◽  
pp. 134-139 ◽  
Author(s):  
Megan E. Patrick ◽  
Yvonne M. Terry-McElrath ◽  
John E. Schulenberg ◽  
Bethany C. Bray

2013 ◽  
Vol 47 (11) ◽  
pp. 1649-1657 ◽  
Author(s):  
Renée El-Gabalawy ◽  
Jack Tsai ◽  
Ilan Harpaz-Rotem ◽  
Rani Hoff ◽  
Jitender Sareen ◽  
...  

2017 ◽  
Vol 27 (1) ◽  
pp. 83-92 ◽  
Author(s):  
Soumyadeep Mukherjee ◽  
Stefany Coxe ◽  
Kristopher Fennie ◽  
Purnima Madhivanan ◽  
Mary Jo Trepka

Author(s):  
Emily Smail ◽  
Kristin E. Schneider ◽  
Stephanie M. DeLong ◽  
Kalai Willis ◽  
Renata Arrington-Sanders ◽  
...  

2020 ◽  
Vol 8 (2) ◽  
pp. 97
Author(s):  
Wenjuan Sang ◽  
Adam Maltese

Using latent class analysis (LCA), we examine the potential ways of classifying students’ science motivation in the United States and China using data from PISA 2015. Based on a set of nine observed variables of science motivation, we identify three subgroups of cases varied in their internal patterns of motivation, covering, respectively, 24.78%, 12.85%, and 62.37% of the entire sample size. Instead of classifying students into groups with a linear increase in motivation scores, latent class analysis shows that there are students who feel pure enjoyment in learning science but do not associate science with their future careers (Class 1), students who do not like learning science but believe science is important to their future (Class 2), and students who have both high enjoyment and the prospect of doing science for a living in the future (Class 3). Multinomial logistic regression reveals that science motivation groups are significantly affected by gender, nationality, and family background.


2021 ◽  
Vol Volume 14 ◽  
pp. 3865-3871
Author(s):  
Catherine Teng ◽  
Unnikrishnan Thampy ◽  
Ju Young Bae ◽  
Peng Cai ◽  
Richard AF Dixon ◽  
...  

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