Epidemiology of HIV Infection in Communities of Color in the United States

Cargill, Victoria A.; Momplaisir, Florence

doi:10.1007/978-3-030-48744-7_2

Cited by 2 publications

(1 citation statement)

References 123 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, little is known about the factors associated with medical distrust in this subpopulation of AABL PLWH that is understudied because they are poorly engaged in HIV care settings where research is commonly conducted ( Anderson et al, 2020 ), or about the relative importance of these factors and how they may interact with each other. To address these gaps in the literature, we used a machine learning approach ( Liaw & Wiener, 2002 ) to explore associations among medical distrust and sociodemographic characteristics, background risk factors prevalent in the population (homelessness, incarceration, and indications of extreme poverty; Cargill & Momplaisir, 2021 ), substance use patterns, mental health symptoms, as well as potential interactions among these factors. Machine learning, as an approach to data analysis, is a collection of computer-intensive methods capable of yielding new insights with less reliance than classic statistical methods on prior understanding and explicit hypotheses ( Efron & Hastie, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Understanding Medical Distrust Among African American/Black and Latino Persons Living With HIV With Sub-Optimal Engagement Along the HIV Care Continuum: A Machine Learning Approach

Cleland

Gwadz

et al. 2021

Sage Open

View full text Add to dashboard Cite

Medical distrust is a potent barrier to participation in HIV care and medication use among African American/Black and Latino (AABL) persons living with HIV (PLWH). However, little is known about sociodemographic and risk factors associated with distrust. We recruited adult AABL PLWH from low socio-economic status backgrounds with insufficient engagement in HIV care ( N = 512). Participants completed structured assessments on three types of distrust (of health care providers, health care systems, and counter-narratives), HIV history, and mental health. We used a type of machine learning called random forest to explore predictors of trust. On average, participants were 47 years old ( SD = 11 years), diagnosed with HIV 18 years prior ( SD = 9 years), and mainly male (64%) and African American/Black (69%). Depression and age were the most important predictors of trust. Among those with elevated depressive symptoms, younger participants had less trust than older, while among those without depression, trust was greater across all ages. The present study adds nuance to the literature on medical distrust among AABL PLWH and identifies junctures where interventions to build trust are needed most.

show abstract

Section: Introductionmentioning

confidence: 99%

Understanding Medical Distrust Among African American/Black and Latino Persons Living With HIV With Sub-Optimal Engagement Along the HIV Care Continuum: A Machine Learning Approach

Cleland

Gwadz

et al. 2021

Sage Open

View full text Add to dashboard Cite

show abstract

Real Talk: Conversations on HIV with Black Heterosexual Men in Healthcare Settings

Urquhart,

Adams,

Chakraborty

et al. 2024

J Community Health

View full text Add to dashboard Cite

Nearly half of heterosexually transmitted human immunodeficiency virus (HIV) infections occur among Black men in the United States. Yet Black heterosexual men (BHM) are largely ignored in HIV programming, policy implementation, and research. This study explores how masculinity, mental health, and socioeconomic factors such as income, education, and insurance (e.g., enrollment and coverage) correlate with the likelihood of BHM having important conversations surrounding HIV with their healthcare providers and family members. Conversations among social networks (e.g., peers, family, and neighbors) create an opportunity to increase comfortability while discussing HIV-related topics around condom use and testing. This study used a cross-sectional survey design and convenience sampling (N = 279) to recruit participants from a community-academic partnership involving a Federally Qualified Health Center (FQHC) in Detroit between June 1, 2020, and July 31, 2020. Descriptive statistics were used to report demographics, socioeconomic information, and sexual health-related behavior variables. Spearman’s correlation test was used to report bivariate correlations between predictor and outcome variables. 49.3% of the study participants disclosed having ever talked to a healthcare provider about HIV/acquired immune deficiency syndrome (AIDS), and 40.9% disclosed having ever talked to a family member about HIV/AIDS and sexually transmitted infections (STIs). The results from this article highlight potential barriers that may inhibit BHM from engaging in conversations about HIV with their healthcare providers and family members. It is important to include BHM in future research that focuses on HIV prevention and education to support community leaders and clinicians who work to address these disparities.

show abstract

Epidemiology of HIV Infection in Communities of Color in the United States

Cited by 2 publications

References 123 publications

Understanding Medical Distrust Among African American/Black and Latino Persons Living With HIV With Sub-Optimal Engagement Along the HIV Care Continuum: A Machine Learning Approach

Understanding Medical Distrust Among African American/Black and Latino Persons Living With HIV With Sub-Optimal Engagement Along the HIV Care Continuum: A Machine Learning Approach

Real Talk: Conversations on HIV with Black Heterosexual Men in Healthcare Settings

Contact Info

Product

Resources

About