Article

Development of an easy to use tool to assess HIV treatment readiness in adolescent clinical care settings

Public Health and Preventive Medicine, College of Osteopathic Medicine, Nova Southeastern University, Miami, FL, USA.
AIDS Care (Impact Factor: 1.6). 11/2011; 23(11):1492-9. DOI: 10.1080/09540121.2011.565020
Source: PubMed

ABSTRACT

Optimal management of HIV disease requires high levels of lifelong adherence once a patient initiates highly active antiretroviral therapy (HAART). Because suboptimal adherence to HAART is associated with adverse consequences, many providers are hesitant to prescribe HAART for patients whom they perceive as not being ready to initiate treatment. Accurately predicting HIV treatment readiness is challenging. Despite the importance of this construct, few reliable and valid instruments to assess HIV treatment readiness have been developed; none of these have been validated with adolescents and young adults, who comprise an increasing proportion of new HIV cases diagnosed. As a first step to achieve this goal, we developed the HIV Treatment-Readiness Measure (HTRM) for administration by way of audio computer-assisted self-interview (ACASI) and conducted a study to examine its internal consistency, test-retest reliability, acceptability, and preliminary factor structure. We recruited 201 adolescents and young adults living with HIV from 15 adolescent medicine clinics that were part of the Adolescent Trials Network for HIV Interventions. Youth completed the initial assessment and two weeks later the retest assessment. The refined HTRM had high internal consistency (α = 0.84). Test-retest reliability using both sum scores and mean scores were high. The HTRM was also highly acceptable and feasible to use in routine clinical practice. In exploratory factor analysis we found that a five-factor solution was the best fit; each of the subscales (Disclosure, Psychosocial Issues, Connection with Care, HIV Medication Beliefs, and Alcohol and Drugs) had good to acceptable alphas and eigenvalues greater than 2.0. Our findings support conducting a future study to examine the tool's predictive validity.

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