Proceedings (IEEE Int Conf Bioinformatics Biomed)
December 2024
The global decline in HIV incidence has not been mirrored in the United States, where young adults (ages 18-29) continue to account for a significant portion of new infections. In this study, we leverage the All of Us (AoU) Research Program's extensive electronic health records (EHRs) and health survey data to develop machine learning models capable of predicting HIV diagnoses at least three months before clinical identification. Among various models tested, the Support Vector Machine (SVM) model demonstrated a balanced performance, integrating clinically relevant features with robust predictive accuracy (AUC = 0.
View Article and Find Full Text PDFYouth living with HIV have low rates of medication adherence. Youth ages 15-24 years with adherence ≤ 80% or with HIV RNA PCRs (VL) ≥ 200 recruited through social media and clinical sites were randomized to brief weekday cell phone support (CPS) calls or daily, two-way, personalized text message (SMS) reminders for 3 months. Those with VL ≥ 200 or adherence ≤ 80% were rerandomized to receive SMS or CPS with monthly incentives for those utilizing the intervention at least 75% of days for 3 months.
View Article and Find Full Text PDFBackground: Adolescents and young adults (AYAs) (age 13-24 years) accounted for 20% of HIV diagnoses in the United States and 6 dependent areas in 2020. Optimal treatment adherence during adolescence and young adulthood decreases the pool of infectious individuals during the risky sexual activity commonly reported among AYAs living with HIV.
Methods: Adolescents and young adults newly recommended to start antiretroviral therapy (ART) were recruited, nationally, from 7 clinical sites.
Introduction: Adolescents and young adults (AYA) living with chronic medical conditions often struggle to develop medication adherence skills. This pilot trial evaluated the impact of a mobile health coaching intervention, Cell Phone Support (CPS), on medication adherence.
Methods: Interventions in this randomized trial were CPS delivered by phone calls (CPS-C), CPS delivered by text messages (CPS-T), or automated text message reminders (ATR).
Background: Emerging adults (aged 18-29) are less likely to receive the COVID-19 vaccine than any other adult age group. Black Americans are less likely than non-Hispanic white Americans to be fully vaccinated against COVID-19. This study explored factors which affect vaccine intention and attitudes in Black American emerging adults with asthma.
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