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Objectives: HIV-positive adolescents have low-ART adherence, with consequent increased risks of mortality, morbidity, and viral resistance. Despite high rates of violence against children in the Africa region, no known studies have tested impacts on HIV-positive adolescents. We examine associations of ART adherence with adolescent violence victimization by caregivers, teachers, peers, community members, and healthcare providers. Design and methods: HIV-positive adolescents were interviewed (n = 1060), and clinic biomarker data collected. We sampled all 10-19-year olds ever ART-initiated within 53 clinics in 180 South African communities (90.1% reached). Analyses examined associations between nonadherence and nine violence types using sequential multivariate logistic regressions. Interactive and additive effects were tested with regression and marginal effects. Results: Past-week self-reported ART nonadherence was 36%. Nonadherence correlated strongly with virologic failure (OR 2.3, CI 1.4-3.8) and symptomatic pulmonary tuberculosis (OR 1.49, CI 1.18-2.05). Four violence types were independently associated with nonadherence: physical abuse by caregivers (OR 1.5, CI 1.1-2.1); witnessing domestic violence (OR 1.8, CI 1.22-2.66); teacher violence (OR 1.51, CI 1.16-1.96,) and verbal victimization by healthcare staff (OR 2.15, CI 1.59-2.93). Past-week nonadherence rose from 25% with no violence to 73.5% with four types of violence exposure. Conclusion: Violence exposures at home, school, and clinic are major and cumulating risks for adolescent antiretroviral nonadherence. Prevention, mitigation, and protection services may be essential for the health and survival of HIV-positive adolescents.
We conducted a cross-sectional survey of ALHIV and community controls in South Africa. The study took place in the Eastern Cape, a province with the lowest per-capita GDP nationally, and very limited social service access [32]. Within a health sub-district constituting urban, rural, and peri-urban settlements, all 53 facilities providing adolescent antiretroviral therapy (ART; hospitals, primary care clinics, and community health centres) were visited and included in the study. In each clinic, paper and computerized clinical files were reviewed to identify every patient aged 10–19 who had ever initiated ART, regardless of current healthcare attendance. To prevent sampling bias towards those attending healthcare, adolescents were not interviewed in clinics, but were traced to 180 communities and interviewed in their homes and schools. It was important to avoid risk of stigma or identification of HIV-positive status from participation in the research. Consequently, the study was presented as focusing on general adolescent use of health and social services, and as an additional stigma avoidance strategy, we also interviewed 467 adolescents who were co-resident or living in neighbouring households. Ethical approval was given by IRBs at the Universities of Cape Town (CSSR 2013/4) and Oxford (SSD/CUREC2/12-21), the Provincial Departments of Health and Education and participating health facilities. All participants and their primary caregivers provided written informed consent for interviews and accessing clinical records. Consent procedures were also read aloud in case of low literacy. No financial incentives were used, but participants received a small gift pack, snacks, and a certificate of participation. Confidentiality was maintained except in cases of disclosure of risk of harm. Where participants reported on-going or prior abuse or violence, referrals were made to relevant child protection, health services, or police (n = 112 referrals). A registered child protection social worker oversaw referrals and subsequent follow-up. Adolescents completed confidential 90-min tablet-based questionnaires, designed in collaboration with a Teen Advisory Group to be enjoyable and nonstigmatizing. Measures were translated and back-translated into Xhosa and English and completed in the language of participants’ choice. Audio-CASI was used for sensitive items. Researchers trained in working with vulnerable adolescents provided support for questionnaire completion, depending on adolescents’ literacy, and cognitive needs. Research tools were prepiloted with 25 HIV-positive adolescents in the Eastern Cape. In order to mitigate risk of social desirability bias, self-reported nonadherence was validated against two clinical outcomes that may be associated with nonadherence: clinic-based records of virologic failure [33] and a combination of clinic records and self-reported symptomatic tuberculosis (TB) [34]. The study was developed in collaboration with the South African National Departments of Health, Social Development and Basic Education and National AIDS Council, UNICEF, PEPFAR-USAID, and NGOs including Pediatric Adolescent Treatment for Africa. ART nonadherence was measured using the standardized self-report Patient Medication Adherence Questionnaire, combined with measures developed in Botswana by Lowenthal et al.[35,36]. After piloting, vignettes were added to reduce social desirability bias, for example, ‘Even if Lindiwe tries her best sometimes unexpected things get in the way and prevent her from taking her pills… this is not her fault.’ Past-week nonadherence was defined as ART medication adherence below 95% over the preceding 7 days (always including both a weekend and weekdays) [37]. Two validation measures of self-reported nonadherence were applied. Virologic failure was measured using clinical records and defined as viral load greater than 1000 copies/ml [38]. All viral load measures taken in the year of interview and the prior year were recorded. Concurrent symptomatic pulmonary TB was measured as clinic report of TB diagnosis without subsequent treatment in the past year or self-reported WHO diagnostic criteria for symptomatic TB, validated against sputum specimens [39,40]. To maximize precision for case identification, we combined criteria for highest positive predictive value (chronic cough and weight loss with sensitivity 72.9%, specificity 85%, PPV 11.4) and highest negative predictive value (NPV; any cough, drenching night sweats, and weight loss with sensitivity 75%, specificity 82.4%, NPV 99.2) amongst HIV-positive participants. Ten potential violence factors were measured and coded as dichotomies of exposure/no exposure. Past-year physical abuse victimization by caregivers at home past-year verbal abuse victimization by caregivers at home and past-week witnessing domestic violence between adults in the home were measured using UNICEF Measures for National-level Monitoring of Orphans and Vulnerable Children [41]. Contact sexual violence by any perpetrator was measured using three items from the Juvenile Victimization Questionnaire and defined as any lifetime contact sexual abuse or forced sex [42]. Past-year physical violence from teachers in school was measured as being hit by a teacher ‘sometimes’/‘always.’ Past-year physical violence from peers and past-year verbal violence from peers were measured using the Social and Health Assessment peer victimization scale [43]. Past-year physical violence victimization in community settings was measured as being physically attacked in the community or being robbed and past-year witnessing of violence in community settings was measured as any of past-year witnessing of shootings or stabbings, using the Child Exposure to Community Violence checklist [44]. Past-year verbal violence in the clinic setting was measured as adolescent self-report of being shouted at angrily by clinic staff ‘sometimes’/‘always’. Nine potential confounders were identified using quantitative and qualitative literature review of factors associated with adherence amongst adult, pediatric, and adolescent populations included socio-economic factors of age, sex, urban/rural location, and living in formal or informal housing, using items based on the 2011 Census [45]. They also included family factors of maternal orphanhood and paternal orphanhood, and HIV-related factors of mode of infection (vertical/ horizontal), time on ART treatment (in years), and travel time to clinical care (dichotomized as >1 h) [46]. Analyses were conducted in six stages in SPSS 21.0 and STATA 14. First, associations of self-reported nonadherence were tested in multivariate logistic regressions, against validation measures of virologic failure and symptomatic TB, controlling for potential confounders. Second, known characteristics (sex, age, and location) of excluded and included participants were compared to check for potential differences. Violence variables were excluded if numbers were too small for analysis. Third, sociodemographic characteristics were reported and potential associations between violence and ART nonadherence were assessed following a sequential regression approach recommended by Hosmer and Lemeshow [47]. Three logistic regression models were run: with all violence victimization factors and potential confounders entered simultaneously, with all variables significant at 0.1 or below, and with only variables significant at 0.05 or below. Fourth, we tested all potential two-way interactive effects between violence factors significant in Stage 3, using logistic regression applying Hochberg’s multiple hypothesis step-up method to reduce false discovery rate. Fifth, we tested potential moderation effects of sex and age on associations between violence factors significant in Stage 3 and nonadherence, using interaction terms in the final regression model. Sixth, to test potential cumulative effects of multiple types of violence exposure on ART nonadherence, marginal effects models were run with all potential combinations of significant violence factors and summarized with a marginal effects model using a multiple-violence score of 0–4 types of violence.
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