Clinic and care: associations with adolescent antiretroviral therapy adherence in a prospective cohort in South Africa

AIDS, Volume 35, No. 8, Year 2021

Interpretation

Objective: Adolescent antiretroviral treatment (ART) adherence remains critically low. We lack research testing protective factors across both clinic and care environments. Design: A prospective cohort of adolescents living with HIV (sample n = 969, 55% girls, baseline mean age 13.6) in the Eastern Cape Province in South Africa were interviewed at baseline and 18-month follow-up (2014-2015, 2015-2016). We traced all adolescents ever initiated on treatment in 52 government health facilities (90% uptake, 93% 18-month retention, 1.2% mortality). Methods: Clinical records were collected; standardized questionnaires were administered by trained data collectors in adolescents’ language of choice. Probit within-between regressions and average adjusted probability calculations were used to examine associations of caregiving and clinic factors with adherence, controlling for household structure, socioeconomic and HIV factors. Results: Past-week ART adherence was 66% (baseline), 65% (follow-up), validated against viral load in subsample. Within-individual changes in three factors were associated with improved adherence: no physical and emotional violence (12.1 percentage points increase in adjusted probability of adherence, P < 0.001), improvement in perceived healthcare confidentiality (7.1 percentage points, P < 0.04) and shorter travel time to the clinic (13.7 percentage points, P < 0.02). In combination, improvement in violence prevention, travel time and confidentiality were associated with 81% probability of ART adherence, compared with 47% with a worsening in all three. Conclusion: Adolescents living with HIV need to be safe at home and feel safe from stigma in an accessible clinic. This will require active collaboration between health and child protection systems, and utilization of effective violence prevention interventions. The study took place in the Eastern Cape province of South Africa, characterized by high morbidity, low human development and poor infrastructure. We conducted standardized interviews and extracted clinical records for 1046 adolescents living with HIV at baseline (2014–2015), with 979 reinterviewed at 18-month follow-up (2016–2017). Nine hundred and sixty-nine had complete data on key variables. The study included both adolescents engaged in clinical care and those who were lost to follow-up in clinical care, and thus, it is the region's first large-scale community-traced cohort of this group. In a health district including rural, urban and peri-urban settlements, we identified all 52 community health centres, primary clinics and hospitals that provided ART to adolescents. In each facility, all patient files (paper and electronic) were reviewed to identify all those who had ever initiated ART and were aged 10–19 years. Throughout 180 communities, adolescents were interviewed at a location of their choice. At 18 months after baseline, all adolescents who had consented to be reapproached were asked for consent for follow-up. Reflecting high mobility, 18% of participants have moved households between study waves, and by follow-up participants lived in six provinces: Eastern Cape, Gauteng, KwaZulu-Natal, Free State, Western Cape and North-West. Ethical approvals were given by the University of Cape Town (CSSR 2013/4), Oxford University (CUREC2/12–21), provincial Departments of Health and Education, and healthcare facilities. All adolescents and their primary caregivers gave written informed consent at both time points in their language of choice (Xhosa or English), read aloud in cases of low literacy. The study did not provide financial incentives, but adolescents did receive a snack, a certificate of participation, and a small gift pack including soap and pencils. These were recommended by our adolescent advisory group [30] and provided regardless of interview completion. Clinical records were extracted in healthcare facilities (see Supplementary Materials Box S1), and trained local researchers supported participants in completing tablet-based questionnaires lasting 60–90 min. Adolescents chose their language of participation. Questionnaires were codesigned with an adolescent advisory group; the South African National Departments of Health, Social Development, Basic Education and National AIDS Council; UNICEF; PEPFAR-USAID, and local NGOs. Prepiloting was conducted locally with 25 adolescents living with HIV. To avoid stigma or unintended disclosure of HIV status, the research focus was presented as general adolescent social and health needs, and 456 neighbouring adolescents were also interviewed (not included in these analyses). Confidentiality was maintained except in cases of risk of harm. For rape, abuse, suicidality or untreated severe illness [e.g. symptomatic tuberculosis (TB)], researchers made immediate health and social service referrals with follow-up support (n = 157 referrals over 3 years for 104 adolescents). Full questionnaires are available at http://www.youngcarers.org.za/youthpulse. All variables in these analyses were measured and defined in the same way at baseline and follow-up. ART adherence was measured using adapted items from the Patient Medication Adherence Questionnaire and measures developed in Botswana [31,32]. ART adherence was defined as past 7 days adherence more than 95% (including weekdays and weekend), based on currently taking ART and not having missed any doses in the past seven days [33]. We validated self-reported adherence against viral loads available in clinical records, using the viral load measurement closest to the interview date. Eight percent of adolescents’ clinical records did not include any viral load measurements, and about 60% of adolescents with an available viral load had a measurement from the two years before or after the questionnaire date [34]. Thus, our validation focused on adolescents whose clinical records included viral load measurements within this period, excluding measurements in a 30-day range around ART initiation (n = 650 adolescents at baseline and n = 598 at follow-up). Clinic factors: Medication stock-outs were measured as past-year inability to access ART due to clinic stock-outs. Confidentiality was measured as feeling that their information would be kept safe and confidential at the clinic most or all of the time in the past year. Wait time in the clinic above 1 h and travel to the clinic above 1 h were measured as past-year experiences in respect to the main clinic the adolescent attends [27–29]. Caregiving factors: Past-year physical or emotional abuse victinization by caregivers or other adults were measured using UNICEF Measures for National-level Monitoring of Orphans and Vulnerable Children [35] (12 items) and defined as having experienced at least one type of violence, such as being hit with a hard item. Past-week witnessing domestic violence between adults in the home (physical or verbal) also used these UNICEF measures [35] (two items). Good parent/caregiver monitoring and supervision (nine items, e.g., having rules for when adolescents come home) and positive caregiving (six items, e.g. positive reinforcement) were measured over the past 2 months, using subscales of the Alabama Parenting Questionnaire [36], and defined as not having experienced any poor monitoring and supervision, and as always experiencing positive caregiving. Good communication between primary caregivers and adolescents was measured over the past 2 months using adapted Child-Parent Communication Apprehension Scale for use with young adults, asking about ease and openness of communication and defined as agreeing or strongly agreeing to all items (five items) [37]. All caregiving and clinic factors were dichotomized to facilitate interpretability. Household structure factors included orphanhood (maternal or paternal) measured using items adapted from the 2011 South African census [38]; number of changes of caregiver experienced; household size, and relationship of primary caregiver to child, that is biological parent or not. Socioeconomic factors included adolescent age, sex, urban/rural location and living in formal or informal housing, using census-based items [39]. Household poverty was measured as access to eight highest socially perceived necessities for children in the nationally representative South African Social Attitudes Survey (e.g. enough food) [40]. HIV-related factors were measured using clinical records, checked against self-report where possible, and included mode of HIV infection (vertical/horizontal) and recent HIV infection (<2 years before baseline). First, we validated self-reported ART adherence against undetectable viral load (<50 copies/ml) from clinical records using multivariable logistic regression, controlling for age, sex, rural/urban, orphanhood, informal housing, mode of infection and health status. Second, we examined frequencies of adherence, hypothesized explanatory and control variables. Third, we compared participants who were followed up and included in this analysis, and those who were not, to check for potential differences using t-tests for continuous variables and Chi-squared tests for dichotomous variables. Fourth, we examined associations of clinic and care factors with past-week adherence. We used a within-between regression model, also known as a hybrid model, which allows us to look at within-person variation as well as compute average adjusted probabilities of the outcome [41–43]. For each explanatory variable, we used a person's average value and time-specific deviation from this average [see Eq. (1)]. where Φ is the cumulative normal distribution, adherence is the time-varying dependent variable, β0 represents the overall intercept, xit is a time-varying explanatory variable for person i at time t,x¯i is the average of the explanatory variable for person i across both time points, β1 represents the average between-person effect and β2 represents the average within-person effect, vi0 – a random person-level intercept, assumed to be normally distributed, and εit – the residuals. This provides a ‘between-person’ coefficient (estimated by x¯i), the difference between individuals and a ‘within-person’ coefficient (estimated by xit−x¯i), which examines the changes within individual's levels of the explanatory variable over time. With two time points, the within-person estimate is equivalent to a first difference model [44]. The within-person estimate is the focus of our analyses as it allows to account for all time-invariant confounders [44]. Participant sex, ART initiation and mode of infection were modelled as time-invariant, while all other control variables were modelled as time-variant. Analyses were conducted in Stata 14.2 (code available at https://osf.io/znse9/). We used a probit model (xtprobit command) with robust clustered standard errors at the individual level. To aid interpretation of the relationships between the explanatory variables and adherence, we estimated average adjusted probabilities [45] of the clinic and caregiving factors that were statistically significant in the multivariable regression (P < 0.05), using margins and lincom commands [46].

AI Digest

Study Justification:

– Adolescent antiretroviral treatment (ART) adherence is critically low.
– Research is needed to identify protective factors in both clinic and care environments.
– This study aims to fill this research gap and provide insights into improving ART adherence among adolescents living with HIV.

Study Highlights:

– Prospective cohort study conducted in the Eastern Cape Province, South Africa.
– Sample size of 969 adolescents living with HIV.
– Data collected through interviews and clinical records.
– Factors associated with improved adherence: absence of physical and emotional violence, improved healthcare confidentiality, and shorter travel time to the clinic.
– Combination of these factors associated with 81% probability of ART adherence.

Study Recommendations:

– Adolescents living with HIV need to be safe at home and feel safe from stigma in an accessible clinic.
– Active collaboration between health and child protection systems is required.
– Utilization of effective violence prevention interventions is necessary.

Key Role Players:

– Health system officials and administrators.
– Child protection agencies and organizations.
– Healthcare providers and clinicians.
– Researchers and academics.
– Community leaders and advocates.

Cost Items for Planning Recommendations:

– Training and capacity building for healthcare providers and staff.
– Implementation of violence prevention interventions.
– Improvement of clinic infrastructure and accessibility.
– Development and dissemination of educational materials.
– Monitoring and evaluation of adherence programs.
– Collaboration and coordination efforts between health and child protection systems.
– Research and data collection activities.
– Community engagement and awareness campaigns.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong, but there are some areas for improvement. The study design is a prospective cohort, which is generally considered a strong design for assessing associations. The sample size is also relatively large (n=969). The study collected data through standardized questionnaires and clinical records, which adds to the reliability of the findings. The study also validated self-reported adherence against viral load measurements, which strengthens the measurement of the outcome. However, there are a few areas that could be improved. First, the abstract does not provide information on the representativeness of the sample, which could affect the generalizability of the findings. Second, the abstract does not mention any potential limitations of the study, such as selection bias or confounding factors. It would be helpful to include this information to provide a more comprehensive assessment of the evidence. Finally, the abstract does not provide any information on the statistical methods used for the analysis, which makes it difficult to evaluate the robustness of the findings. Including this information would enhance the transparency and credibility of the study.

Abstract

The study took place in the Eastern Cape province of South Africa, characterized by high morbidity, low human development and poor infrastructure. We conducted standardized interviews and extracted clinical records for 1046 adolescents living with HIV at baseline (2014–2015), with 979 reinterviewed at 18-month follow-up (2016–2017). Nine hundred and sixty-nine had complete data on key variables. The study included both adolescents engaged in clinical care and those who were lost to follow-up in clinical care, and thus, it is the region's first large-scale community-traced cohort of this group. In a health district including rural, urban and peri-urban settlements, we identified all 52 community health centres, primary clinics and hospitals that provided ART to adolescents. In each facility, all patient files (paper and electronic) were reviewed to identify all those who had ever initiated ART and were aged 10–19 years. Throughout 180 communities, adolescents were interviewed at a location of their choice. At 18 months after baseline, all adolescents who had consented to be reapproached were asked for consent for follow-up. Reflecting high mobility, 18% of participants have moved households between study waves, and by follow-up participants lived in six provinces: Eastern Cape, Gauteng, KwaZulu-Natal, Free State, Western Cape and North-West. Ethical approvals were given by the University of Cape Town (CSSR 2013/4), Oxford University (CUREC2/12–21), provincial Departments of Health and Education, and healthcare facilities. All adolescents and their primary caregivers gave written informed consent at both time points in their language of choice (Xhosa or English), read aloud in cases of low literacy. The study did not provide financial incentives, but adolescents did receive a snack, a certificate of participation, and a small gift pack including soap and pencils. These were recommended by our adolescent advisory group [30] and provided regardless of interview completion. Clinical records were extracted in healthcare facilities (see Supplementary Materials Box S1), and trained local researchers supported participants in completing tablet-based questionnaires lasting 60–90 min. Adolescents chose their language of participation. Questionnaires were codesigned with an adolescent advisory group; the South African National Departments of Health, Social Development, Basic Education and National AIDS Council; UNICEF; PEPFAR-USAID, and local NGOs. Prepiloting was conducted locally with 25 adolescents living with HIV. To avoid stigma or unintended disclosure of HIV status, the research focus was presented as general adolescent social and health needs, and 456 neighbouring adolescents were also interviewed (not included in these analyses). Confidentiality was maintained except in cases of risk of harm. For rape, abuse, suicidality or untreated severe illness [e.g. symptomatic tuberculosis (TB)], researchers made immediate health and social service referrals with follow-up support (n = 157 referrals over 3 years for 104 adolescents). Full questionnaires are available at http://www.youngcarers.org.za/youthpulse. All variables in these analyses were measured and defined in the same way at baseline and follow-up. ART adherence was measured using adapted items from the Patient Medication Adherence Questionnaire and measures developed in Botswana [31,32]. ART adherence was defined as past 7 days adherence more than 95% (including weekdays and weekend), based on currently taking ART and not having missed any doses in the past seven days [33]. We validated self-reported adherence against viral loads available in clinical records, using the viral load measurement closest to the interview date. Eight percent of adolescents’ clinical records did not include any viral load measurements, and about 60% of adolescents with an available viral load had a measurement from the two years before or after the questionnaire date [34]. Thus, our validation focused on adolescents whose clinical records included viral load measurements within this period, excluding measurements in a 30-day range around ART initiation (n = 650 adolescents at baseline and n = 598 at follow-up). Clinic factors: Medication stock-outs were measured as past-year inability to access ART due to clinic stock-outs. Confidentiality was measured as feeling that their information would be kept safe and confidential at the clinic most or all of the time in the past year. Wait time in the clinic above 1 h and travel to the clinic above 1 h were measured as past-year experiences in respect to the main clinic the adolescent attends [27–29]. Caregiving factors: Past-year physical or emotional abuse victinization by caregivers or other adults were measured using UNICEF Measures for National-level Monitoring of Orphans and Vulnerable Children [35] (12 items) and defined as having experienced at least one type of violence, such as being hit with a hard item. Past-week witnessing domestic violence between adults in the home (physical or verbal) also used these UNICEF measures [35] (two items). Good parent/caregiver monitoring and supervision (nine items, e.g., having rules for when adolescents come home) and positive caregiving (six items, e.g. positive reinforcement) were measured over the past 2 months, using subscales of the Alabama Parenting Questionnaire [36], and defined as not having experienced any poor monitoring and supervision, and as always experiencing positive caregiving. Good communication between primary caregivers and adolescents was measured over the past 2 months using adapted Child-Parent Communication Apprehension Scale for use with young adults, asking about ease and openness of communication and defined as agreeing or strongly agreeing to all items (five items) [37]. All caregiving and clinic factors were dichotomized to facilitate interpretability. Household structure factors included orphanhood (maternal or paternal) measured using items adapted from the 2011 South African census [38]; number of changes of caregiver experienced; household size, and relationship of primary caregiver to child, that is biological parent or not. Socioeconomic factors included adolescent age, sex, urban/rural location and living in formal or informal housing, using census-based items [39]. Household poverty was measured as access to eight highest socially perceived necessities for children in the nationally representative South African Social Attitudes Survey (e.g. enough food) [40]. HIV-related factors were measured using clinical records, checked against self-report where possible, and included mode of HIV infection (vertical/horizontal) and recent HIV infection (<2 years before baseline). First, we validated self-reported ART adherence against undetectable viral load (<50 copies/ml) from clinical records using multivariable logistic regression, controlling for age, sex, rural/urban, orphanhood, informal housing, mode of infection and health status. Second, we examined frequencies of adherence, hypothesized explanatory and control variables. Third, we compared participants who were followed up and included in this analysis, and those who were not, to check for potential differences using t-tests for continuous variables and Chi-squared tests for dichotomous variables. Fourth, we examined associations of clinic and care factors with past-week adherence. We used a within-between regression model, also known as a hybrid model, which allows us to look at within-person variation as well as compute average adjusted probabilities of the outcome [41–43]. For each explanatory variable, we used a person's average value and time-specific deviation from this average [see Eq. (1)]. where Φ is the cumulative normal distribution, adherence is the time-varying dependent variable, β0 represents the overall intercept, xit is a time-varying explanatory variable for person i at time t,x¯i is the average of the explanatory variable for person i across both time points, β1 represents the average between-person effect and β2 represents the average within-person effect, vi0 – a random person-level intercept, assumed to be normally distributed, and εit – the residuals. This provides a ‘between-person’ coefficient (estimated by x¯i), the difference between individuals and a ‘within-person’ coefficient (estimated by xit−x¯i), which examines the changes within individual's levels of the explanatory variable over time. With two time points, the within-person estimate is equivalent to a first difference model [44]. The within-person estimate is the focus of our analyses as it allows to account for all time-invariant confounders [44]. Participant sex, ART initiation and mode of infection were modelled as time-invariant, while all other control variables were modelled as time-variant. Analyses were conducted in Stata 14.2 (code available at https://osf.io/znse9/). We used a probit model (xtprobit command) with robust clustered standard errors at the individual level. To aid interpretation of the relationships between the explanatory variables and adherence, we estimated average adjusted probabilities [45] of the clinic and caregiving factors that were statistically significant in the multivariable regression (P < 0.05), using margins and lincom commands [46].

Materials

https://efashare.b-cdn.net/materials/78dd1789562e583ce6080fb9f83fc59e4216a78ee95a71b8b7ec0f95e0a9253b/aids-35-1263-s001.docx

Innovations

Based on the information provided, here are some potential innovations that could improve access to maternal health:

1. Mobile Clinics: Implementing mobile clinics that can travel to remote areas or underserved communities to provide maternal health services. This would help overcome geographical barriers and ensure that pregnant women have access to necessary care.

2. Telemedicine: Using telemedicine technologies to provide virtual consultations and follow-up care for pregnant women. This would be particularly beneficial for women in rural areas who may have limited access to healthcare facilities.

3. Community Health Workers: Training and deploying community health workers who can provide basic maternal health services, education, and support in their communities. This would help bridge the gap between healthcare facilities and pregnant women, especially in areas with limited healthcare infrastructure.

4. Health Information Systems: Implementing robust health information systems that can track and monitor maternal health indicators, identify areas of improvement, and ensure continuity of care. This would help healthcare providers make informed decisions and improve the overall quality of maternal health services.

5. Public-Private Partnerships: Collaborating with private healthcare providers and organizations to expand access to maternal health services. This could involve subsidizing services, establishing referral networks, or leveraging private sector expertise and resources to improve maternal health outcomes.

6. Maternal Health Education: Developing and implementing comprehensive maternal health education programs that target both healthcare providers and pregnant women. This would help raise awareness about the importance of prenatal care, childbirth preparedness, and postnatal care, ultimately improving maternal and neonatal health outcomes.

7. Transportation Support: Providing transportation support for pregnant women to overcome barriers related to travel time and distance. This could involve organizing community transportation services or partnering with existing transportation providers to ensure that pregnant women can easily access healthcare facilities.

8. Maternal Health Vouchers: Introducing maternal health vouchers that can be used to cover the cost of prenatal care, delivery, and postnatal care. This would help reduce financial barriers and ensure that all pregnant women can afford essential maternal health services.

9. Maternal Health Hotlines: Establishing dedicated hotlines or helplines where pregnant women can seek information, ask questions, and receive guidance related to maternal health. This would provide a convenient and accessible way for women to access support and advice.

10. Quality Improvement Initiatives: Implementing quality improvement initiatives in healthcare facilities to ensure that maternal health services are delivered in a safe, effective, and patient-centered manner. This could involve regular audits, staff training, and the use of evidence-based guidelines and protocols.

These are just a few potential innovations that could be considered to improve access to maternal health. It’s important to assess the specific needs and context of the target population to determine which innovations would be most effective and feasible to implement.

AI Innovations Description

Based on the information provided, the study identified several factors associated with improved adherence to antiretroviral therapy (ART) among adolescents living with HIV in South Africa. These factors include:

1. No physical and emotional violence: Adolescents who did not experience physical or emotional violence had a 12.1 percentage points increase in the adjusted probability of adherence.

2. Improved perceived healthcare confidentiality: Adolescents who felt that their information would be kept safe and confidential at the clinic had a 7.1 percentage points increase in the adjusted probability of adherence.

3. Shorter travel time to the clinic: Adolescents who had a travel time to the clinic of less than 1 hour had a 13.7 percentage points increase in the adjusted probability of adherence.

The combination of improvement in these three factors was associated with an 81% probability of ART adherence, compared to 47% probability with a worsening in all three factors.

Based on these findings, a recommendation to improve access to maternal health could be to focus on the following:

1. Violence prevention: Implement interventions to prevent physical and emotional violence against pregnant women and new mothers. This could include community-based programs, education campaigns, and support services for victims of violence.

2. Enhance healthcare confidentiality: Ensure that healthcare facilities prioritize the confidentiality of patient information, especially for sensitive issues such as maternal health. This can be achieved through staff training, strict privacy policies, and secure electronic health record systems.

3. Improve transportation infrastructure: Invest in improving transportation infrastructure, particularly in rural areas, to reduce travel time and make it easier for pregnant women to access healthcare facilities. This could involve building or upgrading roads, providing public transportation options, and establishing satellite clinics in underserved areas.

By addressing these recommendations, it is possible to enhance access to maternal health services and improve the overall well-being of pregnant women and new mothers.

AI Innovations Methodology

Based on the provided information, here are some potential recommendations for improving access to maternal health:

1. Increase the availability and accessibility of maternal health clinics: This can be achieved by establishing more clinics in underserved areas, particularly in rural and peri-urban settlements. Additionally, efforts should be made to ensure that these clinics are well-equipped and staffed with trained healthcare professionals.

2. Improve transportation infrastructure: Long travel times to clinics can be a barrier to accessing maternal health services. Investing in transportation infrastructure, such as roads and public transportation, can help reduce travel time and make it easier for pregnant women to reach healthcare facilities.

3. Enhance confidentiality and privacy in healthcare settings: Many women may hesitate to seek maternal health services due to concerns about privacy and confidentiality. Implementing measures to ensure that personal health information is kept confidential and providing private spaces for consultations can help alleviate these concerns and encourage more women to seek care.

4. Strengthen violence prevention interventions: The study found that experiencing physical and emotional violence was associated with lower adherence to antiretroviral therapy among adolescents living with HIV. Implementing violence prevention interventions, both within the home and in healthcare settings, can help create a safe environment for pregnant women and improve their access to maternal health services.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define key indicators: Identify specific indicators that can measure the impact of the recommendations, such as the number of maternal health clinics established, average travel time to clinics, rates of confidentiality breaches, and rates of violence incidents.

2. Collect baseline data: Gather data on the current state of maternal health access, including the number and location of existing clinics, average travel time to clinics, and any available data on confidentiality breaches and violence incidents.

3. Simulate the impact of each recommendation: Use modeling techniques to estimate the potential impact of each recommendation on the identified indicators. This could involve analyzing data on population distribution, transportation infrastructure, and healthcare resources to determine the potential changes in access to maternal health services.

4. Analyze the results: Evaluate the simulated impact of the recommendations on the identified indicators. Compare the results to the baseline data to assess the potential improvements in access to maternal health services.

5. Refine and iterate: Based on the analysis, refine the recommendations and simulation methodology as needed. Repeat the simulation process to further assess the potential impact of the refined recommendations.

By following this methodology, policymakers and healthcare providers can gain insights into the potential effects of different innovations and interventions on improving access to maternal health. This information can inform decision-making and resource allocation to prioritize the most effective strategies.

Author

Dima Health

Statistics:

Citations: 5

Identifiers:

DOI: 10.1097/QAD.0000000000002882

ISSN: 02699370

Research Areas:

Community Interventions, Food Security, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Violence and Injury

Study Countries:

Botswana, Multi-Countries, South Africa

Study Design:

Cohort Study, Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Female