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Faculty & Staff Honors

Faculty & Staff Honors

UIC Receives Grant to Explore Real-Time ART Adherence Monitoring

Dr. Mark Dworkin, professor in epidemiology and biostatistics at the University of Illinois at Chicago School of Public Health, recently received a two-year award of just over $445,000 from the National Institute of Nursing Research to examine a promising new intervention using real-time adherence monitoring and to determine reasons for missed antiretroviral therapy (ART) doses in young African American men who have sex with men (MSM).

[Photo: Dr. Mark Dworkin]

In the United States, African American men account for the largest proportion of new HIV infections by race and disproportionately experience associated mortality. Among HIV-positive persons treated with ART, African Americans are significantly less likely than Whites and Hispanics to be virally suppressed. In addition, young MSM have low adherence to Pre-Exposure Prophylaxis (PrEP).

According to Dr. Dworkin, improving adherence to ART has multiple benefits. “Not only is there a personal health benefit, such as arresting the progression from HIV to AIDS, there’s also the population benefit,” he said, adding, “When a person adheres to ART, the amount of the virus in every drop of blood is so low it is undetectable, which reduces that individual’s risk of transmission to others.”

An important feature of the study is the use of a wireless pill bottle, which will monitor participants’ adherence and send feedback immediately when they miss a dose of medication. This will allow researchers to contact participants in real-time to learn why they missed their medication, rather than following up with them weeks or months after the fact when the information may be less reliable.

“This model could lead to feedback such as a text message, for example, that they just missed their medicine. We want to find out what they think of this idea – is it great? Or is it repellent to them?” Dr. Dworkin explained. Once the study reveals how the target population reacts to this model, it could be used in the design of an intervention to better reach this high-risk group.