Factors Affecting HIV Testing among Youth in Kenya.
Allison NallTiffany ChennevilleLindsey M RodriguezJennifer L O'BrienPublished in: International journal of environmental research and public health (2019)
With the high prevalence of HIV among youth in sub-Saharan Africa, it is vital to better understand factors affecting HIV testing among this population; this is the first step in the HIV treatment cascade. The purpose of this study was to examine factors related to behavioral intentions regarding HIV testing using existing pre-test data from the HIV SEERs (Stigma-reduction via Education, Empowerment, and Research) Project, a community-based participatory research program targeting 13-24-year-olds in Kenya. It was hypothesized that HIV knowledge, social support, subjective well-being, and mental health (depression, anxiety, and stress) would serve as facilitators to HIV testing while projected stigma and substance use would serve as barriers to HIV testing. In partial support of our hypotheses, findings from logistic regression analyses revealed that HIV knowledge, substance use, depression, and social support were significant predictors of HIV testing intentions. However, HIV knowledge and substance use served as facilitators while depression and social support served as barriers. While projected stigma was correlated with HIV testing intentions, it was not a significant predictor in the regression analysis. Subjective well-being, anxiety, and stress were not significant predictors in the regression analysis. These findings have important implications for HIV testing initiatives designed for youth in Kenya as well as future research on HIV testing with this population.
Keyphrases
- hiv testing
- social support
- men who have sex with men
- depressive symptoms
- mental health
- hiv positive
- sleep quality
- healthcare
- quality improvement
- human immunodeficiency virus
- physical activity
- young adults
- mental illness
- climate change
- deep learning
- drug delivery
- current status
- electronic health record
- machine learning
- stress induced
- south africa
- heat stress