Predictors of COVID-19 Stress and COVID-19 Vaccination Acceptance among Adolescents in Ghana.

Coronavirus disease 2019 (COVID-19) continues to ravage world economies, and with its recent mutations, countries worldwide are finding ways of ramping up their vaccination programmes. This cross-sectional design study, therefore, examined the predictors of COVID-19 stress and COVID-19 vaccination acceptance among adolescents in Ghana. A total of 817 participants were conveniently selected to respond to measures on fear of COVID-19, perceived stigma from COVID-19, self-stigma from COVID-19, believing COVID-19 information, COVID-19 infection prevention behaviours, COVID-19 stress, and COVID-19 vaccination acceptance. It was found that females believed COVID-19 information and accepted COVID-19 vaccination more than males did. Moreover, there were significant relationships between the majority of the COVID-19-related variables. Furthermore, fear of COVID-19, self-stigma from COVID-19, and COVID-19 infection prevention behaviours were found to be significant predictors of COVID-19 stress. Additionally, believing COVID-19 information, danger and contamination fears (a subscale of COVID-19 stress), and traumatic stress (a subscale of COVID-19 stress) were significant predictors of COVID-19 vaccination acceptance. These findings imply that different factors influence different COVID-19 variable. Therefore, careful considerations and research should be employed by health authorities and policymakers in preparing COVID-19 information to target different age groups and for different COVID-19 purposes.

The psychometric properties of motors of COVID-19 vaccination acceptance scale (MoVac-COVID19S): A dataset across five regions.

The novel coronavirus disease 2019 (COVID-19) continues to plague the world. Hence, there is been an effort to mitigate this virus and its effects with several means including vaccination which is one of the most effective ways of controlling the virus. However, efforts at getting people to vaccinate have met several challenges. To help with understanding the reasons underlying an individual's willingness to take COVID-19 vaccine or not, a scale called Motors of COVID-19 Vaccination Acceptance Scale (MoVac-COVID19S) was developed. To expand its usability worldwide (as it has currently been limited to only China and Taiwan), data were collected in other countries (regions) too. Therefore, this MoVac-COVID19S data is from five countries (that is, India, Ghana, Afghanistan, Taiwan, and mainland China) which cut across five regions. A total of 6053 participants across the stated countries completed the survey between January and March 2021 using a cross-sectional survey design. The different sections of the survey solicited sociodemographic information (e.g., country, age, gender, educational level, and profession) and the MoVac-COVID19S data from the participants. The data collected from this survey were analyzed using descriptive statistics, which were carried out using the IBM SPSS version 22.0.

Motors of COVID-19 Vaccination Acceptance Scale (MoVac-COVID19S): Evidence of Measurement Invariance Across Five Countries

Purpose The percentage of individuals who were fully vaccinated against COVID-19 was 53% worldwide, 62% in Asia, and 11% in Africa at the time of writing (February 9, 2022). In addition to administrative issues, vaccine hesitancy is an important factor contributing to the relatively low rate of vaccination. The Motors of COVID-19 Vaccination Acceptance Scale (MoVac-COVID19S) was developed to assess COVID-19 vaccination acceptance levels. However, it has only been tested among Taiwanese, mainland Chinese, and Ghanaian populations (Chen et al, 2021;Fan et al, 2021;Yeh et al, 2021). Therefore, the present study examined the construct validity and measurement invariance of the MoVac-COVID19S among individuals from five countries (ie, Taiwan, mainland China, India, Ghana, and Afghanistan). Participants and Methods A cross-sectional survey study recruited 6053 participants across five countries who completed the survey between January and March 2021. Confirmatory factor analysis (CFA) fit indices were used to examine factor structure and measurement invariance across the five countries. Results The fit indices of the CFA were relatively good across the countries except for the root mean square error of approximation (RMSEA). Moreover, the four-factor structure (either nine or 12 items) had a better fit than the one-factor structure. However, the four-factor model using nine MoVac-COVID19S items was the only model that had measurement invariance support for both factor loadings and item intercepts across the five countries. Conclusion The present study confirmed that the MoVac-COVID19S has acceptable psychometric properties and can be used to assess an individual’s willingness to get COVID-19 vaccination.

Examining the validity of the drivers of COVID-19 vaccination acceptance scale using Rasch analysis.

BACKGROUND: To well control the pandemic of COVID-19, herd immunity should be achieved. However, people, especially those with better physical conditions (e.g., young adults), may not accept COVID-19 vaccines. Understanding university students' willingness or reluctance to uptake COVID-19 vaccination is important. AIM: This study aimed to examine the psychometric properties of the DrVac-COVID19S, an instrument that helps assess motivations/drivers of COVID-19 vaccination uptake among university students. RESEARCH DESIGN AND METHODS: Using convenience sampling and cross-sectional design, university students (930 from Taiwan [38.0% males] and 1,244 from Ghana [63.3% males]) completed the DrVac-COVID19S using an online survey (Taiwanese students) or paper-and-pen method (Ghanaian students). Rasch analysis was used to examine the psychometric properties of the DrVac-COVID19S. RESULTS: All 12 items in the DrVac-COVID19S had a satisfactory fit in the Rasch models (infit MnSq = 0.74 to 1.49; outfit MnSq = 0.72 to 1.42). Moreover, the seven-point Likert scale used in the DrVac-COVID19S demonstrated monotonically increasing in their difficulties, which indicated the ordered category. Additionally, no differential item functioning was displayed in the DrVacCOVID-19S across Taiwanese and Ghanaian students. CONCLUSIONS: The DrVacCOVID-19S has good psychometric features to help healthcare providers assess individuals' (especially university students) motivations or drivers to get the COVID-19 vaccination.