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AIDS Behav. 2018 Mar;22(3):948-960. doi: 10.1007/s10461-017-1772-z.

Estimating HIV Medication Adherence and Persistence: Two Instruments for Clinical and Research Use.

Author information

1
Division of Infectious Diseases, The University of North Carolina, Campus Box 7215, Chapel Hill, NC, 27599, USA. wohl@med.unc.edu.
2
Department of Psychology and Neuroscience, The University of North Carolina, Chapel Hill, NC, USA.
3
Division of Infectious Diseases, The University of North Carolina, Campus Box 7215, Chapel Hill, NC, 27599, USA.
4
Psychology Department, Marquette University, Milwaukee, WI, USA.
5
Department of Biostatistics, The University of North Carolina, Chapel Hill, NC, USA.
6
The University of North Carolina Center for AIDS Research, Chapel Hill, NC, USA.

Abstract

Antiretroviral therapy (ART) requires lifelong daily oral therapy. While patient characteristics associated with suboptimal ART adherence and persistence have been described in cohorts of HIV-infected persons, these factors are poor predictors of individual medication taking behaviors. We aimed to create and test instruments for the estimation of future ART adherence and persistence for clinical and research applications. Following formative work, a battery of 148 items broadly related to HIV infection and treatment was developed and administered to 181 HIV-infected patients. ART adherence and persistence were assessed using electronic monitoring for 3 months. Perceived confidence in medication taking and self-reported barriers to adherence were strongest in predicting non-adherence over time. Barriers to adherence (e.g., affordability, scheduling) were the strongest predictors of non-adherence, as well as 3- and 7-day non-persistence. A ten-item battery for prediction of these outcomes ( www.med.unc.edu/ncaidstraining/adherence/for-providers ) and a 30-item battery reflective of underlying psychological constructs can help identify and study individuals at risk for suboptimal ART adherence and persistence.

KEYWORDS:

Adherence; HIV; Item response theory; Measurement; Prediction

PMID:
28447269
DOI:
10.1007/s10461-017-1772-z

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