Objective: There is limited research examining the relationship between socioeconomic status (SES) and neuropsychological functioning, particularly in racial/ethnic minority and HIV+ populations. However, there are complex associations between poverty, education, HIV disease, race/ethnicity, and health outcomes in the US.
Method: We explored these relationships among an ethnically diverse sample of 134 HIV+ adults using a standardized SES measure (i.e., the Hollingshead scale), a comprehensive NP test battery, and a functional evaluation (i.e., Patient's Assessment of Own Functioning Inventory and Modified Instrumental Activities of Daily Living Scale).
Results: Bivariate analyses showed that adult SES was significantly, positively correlated with neuropsychological performance on specific tests within the domains of verbal fluency, attention/concentration, learning, memory, processing speed, and executive functioning, and childhood SES was significantly linked to measures of verbal fluency, processing speed, and executive functioning. In a series of linear regressions, controlling for SES significantly attenuated group differences in NP test scores between racial/ethnic minority individuals and non-Hispanic White individuals. Finally, SES scores significantly differed across HIV-Associated Neurocognitive Disorder (HAND) diagnoses. In a binary logistic regression, SES was the only independent predictor of HAND diagnosis.
Conclusions: HIV+ individuals with lower SES may be more vulnerable to HIV-associated neuropsychological sequelae due to prominent health disparities, although the degree to which this is influenced by factors such as test bias remains unclear. Overall, our results suggest that SES is significantly linked to neuropsychological test performance in HIV+ individuals, and is an important factor to consider in clinical practice.
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http://dx.doi.org/10.1080/13854046.2015.1029974 | DOI Listing |
Virtual hospitals are rapidly being implemented internationally. Research has predominantly focused on clinical outcomes not implementation. We aimed to identify pre-implementation determinants to enable health services to tailor virtual hospital models, increasing likelihood of suitability, acceptability, uptake, clinical effectiveness, and sustainability.
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