title: Predictors of poor adherence among people on antiretroviral treatment in Cape Town, South Africa: a case-control study.
abstract: A case-control study was conducted to describe the frequency with which structural- and individual-level barriers to adherence are experienced by people receiving antiretroviral (ARV) treatment and to determine predictors of non-adherence. Three hundred adherent and 300 non-adherent patients from 6 clinics in Cape Town completed the LifeWindows Information-Motivation-Behavioral Skills ART Adherence Questionnaire, the Substance Abuse and Mental Illness Symptoms Screener and the Structural Barriers to Clinic Attendance (SBCA) and Medication-taking (SBMT) scales. Overall, information-related barriers were reported most frequently followed by motivation and behaviour skill defects. Structural barriers were reported least frequently. Logistic regression analyses revealed that gender, behaviour skill deficit scores, SBCA scores and SBMT scores predicted non-adherence. Despite the experience of structural barriers being reported least frequently, structural barriers to medication-taking had the greatest impact on adherence (OR: 2.32, 95% CI: 1.73 to 3.12), followed by structural barriers to clinic attendance (OR: 2.06, 95% CI: 1.58 to 2.69) and behaviour skill deficits (OR: 1.34, 95% CI: 1.05 to 1.71). Our data indicate the need for policy directed at the creation of a health-enabling environment that would enhance the likelihood of adherence among antiretroviral therapy users. Specifically, patient empowerment strategies aimed at increasing treatment literacy and management skills should be strengthened. Attempts to reduce structural barriers to antiretroviral treatment adherence should be expanded to include increased access to mental health care services and nutrition support.
authors.affiliation: a Health Systems Research Unit , Medical Research Council of South Africa , Cape Town , South Africa.
authors.forename: Sarah
authors.initials: S
authors.lastname: Dewing
authors.forename: Cathy
authors.initials: C
authors.lastname: Mathews
authors.forename: Mark
authors.initials: M
authors.lastname: Lurie
authors.forename: Ashraf
authors.initials: A
authors.lastname: Kagee
authors.forename: Trishanta
authors.initials: T
authors.lastname: Padayachee
authors.forename: Carl
authors.initials: C
authors.lastname: Lombard
mesh_terms: D000328:Adult; D044966:Anti-Retroviral Agents / Q000627:therapeutic use*; D016022:Case-Control Studies; D003376:Counseling / Q000706:statistics & numerical data*; D005260:Female; D015658:HIV Infections / Q000188:drug therapy* / Q000453:epidemiology* / Q000523:psychology; D006301:Health Services Needs and Demand / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D055118:Medication Adherence / Q000523:psychology; D001523:Mental Disorders / Q000453:epidemiology; D008875:Middle Aged; D009042:Motivation; D011203:Poverty / Q000706:statistics & numerical data*; D012307:Risk Factors; D013019:South Africa / Q000453:epidemiology; D019966:Substance-Related Disorders / Q000453:epidemiology; D011795:Surveys and Questionnaires; D014505:Urban Population / Q000706:statistics & numerical data*; D016903:Drug Monitoring
chemical_list: D044966:Anti-Retroviral Agents
keywords: antiretroviral adherence; predictors of adherence; structural barriers