A measurement model of medication adherence to highly active antiretroviral therapy and its relation to viral load in HIV-positive adults

• Published in: AIDS patient care and STDs Vol. 20; no. 10; p. 701
• Main Authors: Llabre, Maria M, Weaver, Kathryn E, Durán, Ron E, Antoni, Michael H, McPherson-Baker, Shvawn, Schneiderman, Neil
• Format: Journal Article
• Language: English
• Published: United States 01-10-2006
• Subjects: Adolescent; Adult; Aged; Antiretroviral Therapy, Highly Active; Cognitive Behavioral Therapy; Drug Monitoring - methods; Electronics; Female; HIV Seropositivity - drug therapy; HIV Seropositivity - therapy; HIV Seropositivity - virology; HIV-1 - physiology; Humans; Interviews as Topic; Male; Middle Aged; Models, Biological; Patient Compliance; Surveys and Questionnaires; Viral Load
• ISSN: 1087-2914
• DOI: 10.1089/apc.2006.20.701

This study compared a multiple method measurement model of highly active antiretroviral therapy (HAART) adherence with single-method models to determine optimal validity in predicting HIV viral load. Repeated measures of antiretroviral adherence were collected over a 15-month period using three different measurement methods: a self-report questionnaire, an adherence interview item, and electronic medication monitoring. The participants included HIV-positive men and women (n = 323) who were currently prescribed HAART. Single-factor models composed of multiple measurements over time were developed for each adherence method and HIV viral load. The three adherence methods were then combined in a second order factor measurement model. Structural equation modeling was used to test the models. Mean adherence, defined as percent of doses taken, was 92%, 90%, and 57% by self-report, interview, and electronic monitoring, respectively. Reliability of individual measurements of adherence was low. Four or seven assessments were needed to attain acceptable stability, depending on the method. The second-order factor model of adherence fit the data and explained 45% of the variability in HIV viral load. Models including only one method of assessing adherence explained between 20% and 24% of the variability. Models that included both self-report and electronic monitoring optimized predictive validity. Using at least two different methods of adherence measurement, each assessed at multiple times is recommended to derive reliable and valid measurement of medication adherence, which is predictive of biological outcomes such as HIV viral load.