Journal of Applied Social Science最新文献

The COVID-19 pandemic is a critical public health concern that has disproportionately affected the Black community in the United States. The purpose of this study was to examine the risk and protective factors faced by residents in the City of Miami Gardens during the COVID-19 pandemic, with emphases placed on racial health disparities and Black heterogeneity. Using convenience and snowball sampling, quantitative and qualitative data for this study were collected via an anonymous online questionnaire using QuestionPro. Survey links were distributed by e-mail invitations with assistance from city officials to the residents of this predominantly Black city in Florida (n = 83). Descriptive statistics and relevant qualitative responses are presented. Furthermore, a machine learning (ML) approach was used to select the most critical variables that characterized the two racial groups (Black versus non-Black participants) based on four ML feature selectors. Study findings offered important and interesting insights. Specifically, despite the greater prevalence of adopting measures to protect themselves and others from COVID-19, Black participants were more susceptible to activities that increased their COVID-19 risk levels. In addition, their rate of infection, particularly among the Afro-Caribbean ethnic group, was reported to be higher, indicating the need to further investigate the underlying conditions and root causes (including vaccine hesitancy and refusal) that contribute to their greater health disparities.

This study presents an original model that features the emotion of fear of COVID-19 as a direct effect on vaccination intentions. A central research question addressed in the study is what roles do the emotion of fear of contracting COVID-19 and the threat posed by uptake of the COVID-19 vaccination play in levels of vaccination intention? The study used a structural equation model (SEM) and applied the SmartPLS 3.2.6 data analysis tool for model estimation and multivariate analysis variables. A key finding is that vaccination resistance is strongest when fear of COVID-19 is lower, and vaccination threat higher. Vaccination threat appraisal and vaccination intention were found to have a negative relationship. Response costs at higher levels lessen motivation for COVID-19 vaccination. Research implications include research-based targeting of differing segments by their primary fear, either fear of COVID-19 or of the preventative vaccine.

Myriad research examines benefits and drawbacks of working from home, both pre- and post-pandemic. Our research looks at how work from home mandates due to the COVID-19 pandemic were implemented, primarily by those who also had caregiver roles to fulfill. We used a convenience sample, drawing from full-time college faculty at a mid-sized state college in Florida, gathering information from caregivers and non-caregivers for comparative purposes. As we analyzed our data, we considered two additional concepts: Elmore's backward mapping, which asks us to consider how employer mandates are implemented and will assist us in making policy recommendations, and Smith's Standpoint, which allowed us to consider our own different gendered experiences as we analyzed survey responses. Our findings reveal that there are some employees well suited to working from home, while others are less enthusiastic about this initiative, and that a significant factor is household caregiving responsibilities, often considered to be the domain of women. Our insights shed light on differences in caregiver-employee statuses; we hope to help guide effective institutional policy should there be a need for workplaces to shut down again and to encourage administrators to consider faculty who may be a good work from home fit should it be considered for everyday work. Understanding where the strengths and weaknesses were/are for workers who work from home will benefit employers.