Improving HIV testing, linkage, and retention in care among South African men through U = U messaging: A study protocol for two sequential hybrid type 1 effectiveness-implementation randomized controlled trials

Abstract

Background

Increasing HIV testing and treatment coverage among people living with HIV (PLHIV) is essential for achieving global HIV epidemic control. However, compared to women, cis-gender heterosexual men living with HIV are significantly less likely to know their HIV status, initiate anti-retroviral therapy (ART) and achieve viral suppression. This is particularly true in South Africa, where men are also at increased risk of mortality resulting from AIDS-related illnesses. While there is growing knowledge of Treatment as Prevention or the concept Undetectable = Untransmittable (U = U) among PLHIV in Western and high-income countries, the reach and penetration of the U = U message in sub-Saharan Africa remains limited, and few studies have evaluated the impact of accessible and relatable U = U messages on ART initiation and adherence. To address these gaps, rigorous evaluations of interventions that incorporate U = U messages are needed, especially among men in high prevalence settings.

Methods

Building on our U = U messages that we previously developed for men using behavioral economics insights and a human-centered design, we will conduct two sequential hybrid type 1 effectiveness-implementation trials to evaluate the impact of U = U messages on men’s uptake of community-based HIV testing and ART initiation (Trial 1), and retention in care and achievement of viral suppression (Trial 2). For trial 1, a cluster randomized trial will be implemented with HIV testing service site-days (each day at one testing site) randomized to U = U or standard-of-care (SoC) messages inviting men to test for HIV. For trial 2, an individual-level randomized control trial will be implemented, with men initiating ART at six government clinics randomized to receive U = U counselling or SoC treatment adherence messaging. We will incorporate a multi-method evaluation to inform future implementation of U = U messaging interventions. The study will be conducted in the Buffalo City Metro Health District of the Eastern Cape Province and in the Cape Town Metro Health District in the Western Cape Province in South Africa.

Discussion

These trials are the first to rigorously evaluate the impact of U = U messaging on HIV testing uptake, ART initiation and achievement of viral suppression among African men. If effective, these messaging interventions can shape global HIV testing, treatment and adherence counselling guidelines and practices.

Background

Increasing HIV testing and treatment coverage among people living with HIV (PLHIV) is essential for achieving global HIV epidemic control [1]. Compared to women, cis-gender heterosexual men living with HIV (MLHIV) are significantly less likely to know their HIV status, initiate anti-retroviral therapy (ART) or achieve viral suppression [2, 3]. Moreover, new HIV infections among women are driven, in part, by gaps in testing and treatment among men [4–6]. In South Africa specifically, 79% of women vs. 55% of men reported that they had accessed HIV testing services (HTS) in the past 12 months; [7] gaps were even wider for accessing care in rural KwaZulu- Natal [8, 9] Along the continuum of care for HIV-positive individuals in South Africa, women demonstrate higher engagement compared to men [10]. South African men who do initiate ART present with more progressed disease and lower CD4 counts than women, have higher rates of loss-to-follow up (LTFU), and are at increased risk for not re-initiating treatment after disengagement from care [9, 11, 12]. As demonstrated in multiple studies across different regions of South Africa, these gaps in care seeking and engagement have led to higher mortality rates for MLHIV compared to women, both prior to ART initiation and while on ART [8, 10, 13, 14]. Ultimately, increasing men’s uptake of HIV testing and treatment initiation must be prioritized to both achieve viral suppression and improve HIV-related health outcomes among men, and to accelerate the decline in HIV incidence among women.

Following landmark studies showing the benefits of Treatment as Prevention (TasP), the Undetectable Equals Untransmittable (U = U) Campaign was launched in 2016 to disseminate scientific evidence that PLHIV who take ART and have an undetectable viral load (<200 copies/mL) cannot sexually transmit HIV [15–20]. This has been further borne out by the recent review which confirms that sexual transmission of HIV is unlikely from an individual whose HIV viral load is <1000 copies /ml [21, 22]. Informed by behavioral economics principles [23–26] and using a human-centered design process [27–31], our team developed U = U messaging for men and conducted a pilot randomized trial of these peer-delivered messages on HIV testing uptake and HIV positive yield among men in Cape Town, South Africa [32]. The U = U messages sought to reduce fear of testing HIV-positive by emphasizing the various health benefits of ART, including the ability to protect sex partners even during condomless sex. The pilot data showed that when presented as part of community-based HIV testing services (HTS), peer-delivered U = U messaging increased the odds of HIV testing uptake by 60% compared to standard messaging about the availability of free HIV testing [32]. We subsequently conducted participatory prototyping to further refine U = U messages to improve ART initiation and early retention in care.

Particularly for men, the U = U message can accelerate progress towards the UNAIDS 95-95-95 targets by reducing anxiety associated with HIV testing (1st 95), encouraging ART initiation (2nd 95), and reducing fear of transmitting HIV to sexual partners by promoting treatment adherence to achieve viral suppression (3rd 95) [33, 34]. While there is growing knowledge of TasP/U = U among PLHIV in Western and high-income countries, the reach and penetration of the U = U message in high prevalent countries has been limited [35–47] and few studies have evaluated the impact of accessible and relatable U = U messages on HIV testing and ART initiation and adherence in the region [48–50]. To address these gaps, rigorous evaluations of interventions that incorporate U = U messages are needed, especially among cis-gendered heterosexual men in high prevalence settings.

Study aims

Building upon this work, we will conduct two sequential hybrid type 1 effectiveness-implementation randomized trials [51, 52] to compare the impact of U = U messaging versus standard of care on men’s uptake of testing, initiation of ART, and achievement of viral suppression. Our study aims to 1) evaluate the impact of U = U messaging on men’s uptake of HTS and ART initiation; 2) evaluate the impact of U = U messaging on retention in care and viral suppression among MLHIV who initiate ART; and 3) conduct a multi-method evaluation to inform future implementation of U = U messaging interventions. We hypothesize that, compared to standard of care messaging and counselling, U = U messaging will increase HTS uptake by men, increase the number of men initiating ART at 30 days, increase viral suppression at 6 months, and increase retention in care at 12 months. We will also characterize intervention implementation outcomes and identify key, multi-level contextual factors that may block or facilitate implementation of a U = U intervention within HIV service delivery.

Methods

Study setting

We will conduct the study in the Cape Town Metro (CPT; Western Cape Province) and the Buffalo City Metro (BCM; Eastern Cape Province) health districts, South Africa (Fig 1)–two settings with a high HIV prevalence and where our team has existing strong community engagement and health facility partnerships. Of note, the Eastern Cape Province is a historically under-resourced and under-researched province.

[Figure omitted. See PDF.]

In 2022, the estimated adult HIV prevalence in the Eastern Cape Province was 19.4% and in the Western Cape Provinces it was 11.2% [53]. That same year, an estimated 92.6% of individuals living with HIV in the Eastern Cape knew their status, 74.9% were on ART, but only 62.6% were virally suppressed (i.e., <1000c/ml) [54]. In comparison, in the Western Cape, an estimated 93.7% of PLHIV knew their status, 70.3% were on ART, but only 62.4% were virally suppressed (i.e., <1000c/ml) [53, 54]. These statistics are well below the UNAIDS global target for viral suppression of 95%by the year 2025.

Using aggregate South African National Department of Health clinic-level HIV programmatic data, we identified three clinic catchment areas per study district (N = 6) with high HIV prevalence. Study participants for Aim 1 will be recruited from communities within the catchment areas of six large government HIV treatment clinics located in the Kilpfontein and Gugulethu communities of Cape Town (n = 3), and the Mdantsane, Duncan Village and Dimbaza communities of Buffalo City Metro (n = 3). Study participants for Aim 2 will be recruited from within these same six ART clinics. Residents from these communities are primarily black and Xhosa-speaking. Black South Africans living in peri-urban settings (e.g., Kilpfontein, Gugulethu, Mdantsane and Duncan Village) have among the highest rates of HIV infection in South Africa, while those living in rural settings (e.g., Dimbaza) have among the poorest access to health clinics. Our peri-urban selected communities are densely populated, with a high number of residents living in informal housing; Gugulethu is one of the oldest but fastest-growing township communities in Cape Town, while Mdantsane is one of the largest townships in the country. For Aim 3, we will gather quantitative implementation process measures from recruitment and refusal logs, participant sociodemographic data, tracking tools, and clinic and testing site characteristics, as well as using validated tools during implementation of Trial 1 and 2. We will also conduct qualitative interviews with key stakeholders to inform targets and mechanisms for implementation strategies. Recruitment for Aim 3 will occur through long-standing research collaborations and strong networks and relationships in the region; eligible participants will be sought through meeting announcements, flyers, and email outreach.

Ethics approval and consent to participate

The protocol, informed consent form and all translations, participant education and recruitment materials have been approved by the ethical review bodies responsible for oversight of research and have been reviewed and approved by the University of Cape Town, Research Ethics Committee (Approval Number: 556/2021) with respect to scientific content and compliance with applicable research and human subjects’ regulations. IRB approvals have also been granted by University of Pennsylvania via IRB reliance on the University of Cape Town. Eastern Cape Provincial Department of Health approval (Approval Number: EC_202204_002) has been obtained to conduct this study in Buffalo City Metropolitan Health District. Western Cape Provincial Department of Health approval (Approval Number: 202209_022) has been obtained to conduct this study in Cape Town. Subsequent to initial review and approval, the responsible Ethics Committees will review the protocol for renewal once every 12 months. The protocol, informed consent forms and all participant materials, and amendments thereof were or will be reviewed and approved by the ethical review bodies responsible for oversight of research. Informed consent will be obtained from all the participants prior to being enrolled in the study. For participants below age 16 years Ministerial waiver of parent/guardian informed consent was reviewed and approved by the University of Cape Town, Research Ethics Committee. The Investigators will submit safety and progress reports to the Ethics Committees at least annually, and within 3 months of study termination or completion. These reports will include the total number of participants enrolled in the study, the number of participants who completed the study, all changes in the research activity, and all unanticipated problems involving risks to human subjects or others.

Trial 1 (T1): Uptake of HIV testing & linkage-to-care.

T1 overview and study flow. To evaluate the impact of U = U messaging on men’s uptake of HIV and ART initiation, we will leverage our well-established mobile HIV testing vehicles (i.e., mobile Tutu Tester Trucks) and pop-up tents in the study communities [55–60]. We will conduct a hybrid type 1 effectiveness-implementation randomized controlled trial, with randomization at the ‘site-day’ level (Fig 2) [61]. A site-day is defined as one day at one testing site. HTS site-days (N = 320) will be randomized to U = U or Standard-of-Care (SoC) messaging to invite men (N = 28,880) to test for HIV. This study design allows us to evaluate the impact of U = U messaging on HIV testing uptake and on ART initiation.

[Figure omitted. See PDF.]

T1 cluster randomization and placement of testing services. Based on the clinic catchment area, and in consultation with local community leaders, mobile testing units or temporary testing tents (collectively referred to as community-based HIV testing services; CB-HTS) will be located at high foot-traffic sites (e.g., taxi ranks, entrance/exits to markets, shopping malls and supermarkets) in each clinic catchment area (i.e.,16 unique testing sites). Each site will be assigned a single intervention (SoC or U = U) on each day that the mobile testing units or temporary testing tents are located there. The sequence of interventions for each site was determined randomly, using a blocking scheme that ensures that the number of SoC and U = U days was balanced within each site every 4 or 6 days. Separate randomization schemes were developed for each site so that no sites consistently received the interventions in the same order. Randomization sequence will be determined prior to study launch and revealed to the CB-HTS team the night before each site visit. Western Cape, Eastern Cape Rural and Eastern Cape Urban each had their own research staff who visited the sites and were thus considered as three separate strata. To minimize the potential for contamination (e.g., an individual receiving an invitation card one day and revisiting the site to test the following day), no site will be visited on consecutive calendar days.

T1 participant recruitment and data acquisition. Following procedures developed in our pilot trial, [61] trained male peers will approach, invite and provide invitation cards for free HIV testing services (Fig 3) to a total of 28,880 adolescents and men aged ≥15 years who happen to be in the immediate vicinity (±200m) of testing sites. Male peers will deliver the scripted U = U message and U = U invitation card (Fig 3) on intervention days, and the SoC HIV testing message script along with the SoC invitation card on control days; the SoC invitation script is approximately the same length as the U = U script. Invitation cards will be pre-printed with a unique participant identification code (PID). The male peers will write the date, time of distribution and their initials on each invitation card as they are handed out. All men presenting to a HIV testing site will be asked to provide their invitation card to testing site staff. Eligible men presenting a study invitation card for HIV testing will be invited to join the study and asked to provide written informed consent and personal contact details. Regardless of the invitation card a man receives, he will be able to present for testing at any time that day or in the future- i.e., there is no time limitation to when a man receives an invitation card and when he can present for testing.

[Figure omitted. See PDF.]

Using a process successfully implemented during the pilot trial, a site receptionist will record the invitation card’s unique PID, and the date and time of presentation. Reasons for non-enrollment will be recorded. The following inclusion criteria will be applied 1) male; 2) aged ≥15 years; 3) presentation of a study-issued invitation card; and 4) provision of informed consent. Consenting participants will receive a unique study ID number (UID),and be asked to complete a baseline questionnaire administered by study staff prior to being directed to an HIV testing counsellor for a rapid HIV test.

Per South African National HIV testing guidelines, all individuals seeking HTS (i.e., study and non-study participants) will be consented by a certified HIV testing counsellor to receive standard pre-test counselling and an HIV rapid test. Study participants who receive an HIV negative test result, regardless of treatment assignment, will receive standard post-test counselling; and will be offered HIV prevention services (Tutu Testers in Western Cape) or a referral for HIV prevention services at local government clinics (Eastern Cape). Participants in the U = U intervention arm with an HIV-positive test result will receive U = U post-test counselling about ART initiation (Table 1).

[Figure omitted. See PDF.]

Participants in the SoC condition who receive an HIV-positive test result will receive standard (guidelines-based) post-test counselling about ART initiation. Community members (male or female) who passively present to any of our testing venues, or men who do not present with an invitation or do not provide consent will receive standard testing per South African national guidelines [62] including standard pre- and post-test counselling.

T1 outcomes and data analysis plan. The primary outcome will be the intention to treat, which we defined as ART initiation within 30 days of receiving a positive HIV result. ART initiation will be established through participant self-report (via phone calls) and from the National Health Laboratory Service (NHLS) or clinic records where available. In the event of any discrepancies or disagreement between self-report, lab records, or clinic reviews, priority will be given to the information documented in the lab records to define the primary outcome. NHLS tracks lab results including HIV testing, viral load (VL) and CD4. As a proxy for ART initiation, we are identifying CD4 or viral load results to identify when baseline bloods were taken prior to ART start, or to identify people already on ART (prior VL or CD4). The NHLS laboratory system allows us to see provincial level data. Therefore, by having access to NHLS data, we will be able to track participants regardless of their migration status.

Generalized estimating equations (GEE) with a logistic link function and an independent working correlation structure will be used to estimate the odds of ART initiation following U = U versus SoC messaging and will be averaged across sites. The GEE method takes into account clustering by site. A significance level of 0.05 will be employed and calendar quarter will be controlled for to account for seasonal variability in behaviour.

Secondary outcomes will include HIV testing uptake, first-time testing, and test-positivity among those who receive the invitation cards as well as ART initiation among those who test positive for HIV. For this, mixed effects models will be used to estimate: 1) the difference in HIV testing uptake comparing U = U to SoC messaging exposure, and 2) between-site and within-site HIV-testing uptake variability. By ‘between-site’ variability we mean the random variation in HIV testing uptake among different sites, due to intrinsic differences in the populations at these sites. For example, men who are unemployed may have more time available to test than those who are employed; different rates of employment among men sampled at different sites could thus lead to between-site variation in HIV testing uptake. Variability within-site is a reflection of local conditions at each site. For example, at any site, potential participants might be more likely to take the time to test on a pleasant day than on a rainy day; changing weather is potentially one source of within-site variability.

Similar as for the primary outcome analyses, GEE and working correlation structure will also be used for the secondary outcomes. To better identify where in the HIV testing-linkage to care sequence U = U may specifically have an impact, we will estimate the odds ratio and 95% CI for U = U versus SoC for each subsequent outcome conditional on results for the previous outcome (i.e., the outcome of testing positive given the behaviour of presenting for testing, and the behaviour of ART initiation given the outcome of an HIV positive result). Participant groups will be characterized at each step of the sequence to assess how U = U messaging might be influencing specific groups of individuals to test or link to care. Causal methods (potential outcomes) will be used to assess if individuals who test positive following U = U versus SoC messaging are more likely to initiate ART.

T1 sample size calculations and statistical power. A sample size of 28,880 invitation cards distributed (i.e.,14,440 per intervention message) gives us 84% power to detect a risk difference in our primary outcome (yield, or ART initiations as a percent of invitations distributed) of 0.156%, and a risk ratio of 2.57. In other words, we can detect a difference in yield of 0.1% (1 ART initiation per 1000 invitation cards) for SoC versus 0.257% (2–3 ART initiations per 1000 invitation cards) for the U = U intervention. Our sample size calculations are informed by pilot data [61], experience in the field, and recent HIV incidence.

For the U = U intervention arm, we estimated that 15% would present for testing, 3.5% of those who test would test HIV-positive, and 49% of those receiving a positive test result would initiate ART, for a yield of 0.257%. For the SoC arm, we estimated that 10% would present for testing, 2.5% of those who test would test HIV-positive and 40% of those testing positive would initiate ART, for an overall yield of ART initiation among those invited to test of 0.10%. In order to address clustering by site, sample size calculation assumed a within-site-day intraclass correlation (ICC) of 0.01 for participants sampled on the same day at a single site, and a between-site-day ICC of 0.009 for participants sampled on two consecutive sampling days at a site. A discrete-time decay correlation structure using an exponential decay function of the time ‘j’ between site days allowed the correlation between participants sampled at longer intervals apart to decrease over time. Power calculations were conducted by uploading a design matrix generated in R(V4.2.2) to Shiny CRT [63]. To achieve this sample size, we will distribute 90 invitation cards per site day for a total of 320 site days (160 for U = U intervention and 160 for SoC).

Trial 2 (T2): Retention in care and viral suppression.

T2 overview and study flow. To evaluate the impact of U = U messaging on retention in care and viral load (VL) suppression among HIV-positive men who initiate ART, we will conduct a hybrid type 1 effectiveness-implementation randomized controlled trial. Randomization will be stratified by the 6 study clinics, to account for differences in baseline viral loads of the catchment area populations initiating ART within each clinic. Individual-level randomization will be used with random block sizes of 4 to 8. The study staff counsellors will recruit men who are either newly initiating or re-initiating ART at study clinics in Cape Town (n = 3) and Buffalo City Metro (n = 3). Inclusion criteria for trial 2 are as follows: 1) male 2) aged ≥15 years 3) newly initiating ART or re-initiating ART after 6 months of being lost-to-care; 4) live in Buffalo City or Cape Town Metro Health Districts; and 5) provision of written informed consent. Participants (N = 1100) will be individually randomized to receive either U = U messaging (intervention group; n = 550) or SoC messaging (control group; n = 550) as part of ART initiation counselling and during routine HIV care and treatment. Our trial design allows evaluation of both shorter-term impact and longer-term durability of the U = U messaging for ART adherence and treatment retention.

T2 participant recruitment and data acquisition. All participants will receive standard ART initiation and adherence counselling from a DoH clinic nurse per South African National Guidelines (Fig 4) [62]. Thereafter, study staff counsellors will either (1) deliver U = U initiation messaging, or (2) reinforce SoC messaging through a guidelines-based script of comparable length (Fig 4). Additionally, participants will also receive a small business-sized card either re-emphasizing the U = U or the SoC message [64].

[Figure omitted. See PDF.]

At enrolment, participants will be informed that they have the option to receive monthly SMS messages (Fig 5). A mid-month U = U or Attention Matched Control one-way text message will be sent to participants opting to receive SMS messages (Fig 5). Monthly text messaging is not part of the SOC protocol in South Africa, thus our decision to employ an attention matched control message for the SoC participant group. SMS paradata will be collected to track message delivery and receipt.

[Figure omitted. See PDF.]

Study staff counsellors will in addition verbally deliver U = U or reinforce SoC adherence messaging (Table 2) to participants during routine medication refill visits, which are scheduled monthly. Paradata from SMS messages and number of clinic visits attended will be recorded to enable mediation analysis [65, 66]. In accordance with South African ART clinical and adherence guidelines [62, 67], clinic nurses provide patients on ART with feedback based on VL test results. Study participants in the U = U condition with a suppressed VL (<50 copies/mL) will receive Basic U = U messaging, while those with an unsuppressed VL (≥50 copies/mL) will receive Enhanced U = U messaging (Table 2). Participants allocated to SoC will receive guidelines-based reinforced SoC adherence messaging based on their VL [68].

[Figure omitted. See PDF.]

T2 outcomes and data analysis plan. The primary outcome will be the proportion of MLHIV who are virally suppressed at 6 months (impact) and will be analysed using logistic regression with clinic fixed effects. The secondary outcome will be the proportion of MLHIV retained care at 12 months (durability) and will be analysed using logistic regression with clinic fixed effects with outcomes as (1) the number of clinic visits attended prior to six months, and (2) presentation for VL testing at 12 months. VL testing is conducted at 6 months, 12 months and annually thereafter by the Department of Health in accordance with South African national HIV care and treatment guidelines. Should a VL not be recorded in a participant’s medical record, we will consult the SA-NHLS laboratory information system to determine if and when VL testing was performed and record the participant’s VL should it be available. At the 6- and 12-month mark, each participant’s clinic-based medical records will be abstracted for: 1) ART refill and clinic attendance history, and 2) VL results.

All participants lost to follow-up at 6 months will be contacted by study staff using the contact information provided at study enrolment to assess self-reported treatment engagement and invited to return to the clinic to complete a study questionnaire. At 12 months, all participants will also be asked to complete an RedCap administered endline questionnaire in the same manner as the baseline questionnaire. A causal mediation analysis will be conducted to explore direct and indirect effects of the U = U intervention on VL suppression with number of visits as the mediating variable. Pre-specified subgroups for the analyses of the primary and secondary outcomes (the proportion of MLHIV retained in care at 12 months) are those participants: (1) initiating ART for the first time vs. re-initiating ART and (2) Eastern Cape versus Western Cape. For secondary analyses the primary analysis will be repeated using as outcomes:

Sample size calculations and statistical power. Trial 2 is an individually randomized trial. A sample size of 1100 is powered to detect an 8% difference in the primary outcome. For a two-sided Type I error rate of 0.05, and using a two-sample proportions test as the basis of the calculation, we have 80% power to discern between 70% (U = U intervention) versus 62% (SoC intervention) viral suppression at 6 months.

Implementation assessment.

Overview and study flow. We will use the RE-AIM and Consolidated Framework for Implementation Research (CFIR) frameworks, and informed by behavioural economics [69–74], and behavioral design [75] to identify implementation barriers and facilitators of the U = U interventions through structured surveys and qualitative interviews. Perceptions and intervention mechanisms will be explored to inform how the U = U interventions could be implemented and scaled in the future. RE-AIM will inform the identification, collection, and analysis of quantitative survey indicators related to the U = U interventions over the course of the two sequential trials. CFIR will guide a qualitative exploration of the conditions and contexts shaping successful implementation through interviews with key stakeholders (i.e., participants, research/clinic staff, health department managers, policy makers).

Participant recruitment and data acquisition. We will recruit and consent HTS providers (n = 20), ART nurses (n = 24), clinic operation staff (n = 12) and clinic service managers (n = 12) representing both the Cape Town and Buffalo City Metro health districts (n = 68 total); this sample size is sufficient to generate stakeholder preferences for provide a signal about implementation outcomes within and across study sites and districts for both trials, without putting undue burden on clinic or testing site staff.

Qualitative interviews. We will also purposively recruit, consent and interview 40–60 individuals from seven key stakeholder groups. Key stakeholder groups will include: 1) MLHIV who attend the testing sites Including those who test positive but do not initiate (trial 1) or clinics (trial 2) where our trials are conducted 2) health care providers (i.e., nurses or physicians) at the clinics where the retention and viral suppression trial is conducted 3) lay health workers and counsellors 4) clinic leads 5) district, provincial and national departments of health National Department of Health (NDOH) 6) PEPFAR implementing partner leads and 7) South Africa HIV Task Force members. Recruitment will occur through long-standing research collaborations and strong networks and relationships throughout South Africa; eligible participants will be sought through meeting announcements, flyers, and email outreach. The trial 1 interview guide will incorporate results from the Aim 1 trial, presented narratively and graphically. The trial 2 interview guide will incorporate both Aim 1 and Aim 2 trial results, also presented narratively and graphically. Key themes covered in the interview guide will include perceptions of the U = U message, recommendations for implementation of U = U within and South African Department of Health guidelines. Interviews will be conducted by one of the study PI’s or project manager currently pursuing doctoral training.

To describe intervention effectiveness and inform future implementation efforts, we will gather quantitative implementation process measures from recruitment and refusal logs, participant sociodemographic data, tracking tools, and clinic and testing site characteristics. These data will be collected throughout the implementation of trials 1 and 2. To identify key, multi-level contextual factors that may block or facilitate implementation of a U = U intervention within HIV service delivery, we will conduct 1) in-depth qualitative interviews with key stakeholders to inform targets and mechanisms for implementation strategies, and 2) validated quantitative implementation measures. Data will be collected at the mid-point of recruitment for each trial at each site.

Data analysis plan. Passively and actively collected process indicators informed by the RE-AIM framework will be synthesized and summarized iteratively over the course of the two trials. Descriptive statistics and comparisons by study site, provider type, and trial will be used to assess implementation success, interpret trial results, and identify implementation targets and mechanisms. Verbatim transcripts of semi-structured interviews will be entered into NVivo qualitative analysis software (QSR international, Burlington MA) for data management and analysis. Two separate qualitative analyses will be conducted. First, a hybrid inductive-deductive thematic analysis [76] will be conducted using both a priori codes related to CFIR domains and constructs, as well as de novo codes that emerge from the data.

Two team members will code the first three interviews by consensus, then the next three interviews independently and review them together to ensure consensus. Thereafter, all interview transcripts will be coded by two team members independently, with double-coding of 20% of interviews to ensure inter-rater reliability. Outstanding coding questions and disagreements will be resolved by consensus of the team. We will qualitatively analyze themes across interview rounds and stakeholder types to identify key opportunities and challenges for implementation of the U = U interventions. Second, the NUDGE framework [75, 77, 78] will be employed to uncover specific barriers to implementation of evidence-based interventions through the application of behavioral insights to rich contextual data such as in-depth interviews. Behavioral barriers to intervention adoption, adaptation, fidelity, and maintenance identified through this process will inform future implementation strategies and policy recommendations.

Data management

Participant identification

All eligible study participants that provide informed consent will be assigned a Participant Identification Number (PIN) by REDCap. This PIN composition will allow us to identify participants at the community and clinic level, thus ensuring convenient integration of various datasets to carry-out various level-based analysis approaches. Participants’ allocated PIN will be used for the duration of the study at each data collection point. Results from other data sources such as the South African electronic TB register (ETR.net) and District Health Information Systems (DHIS), as well as laboratory databases and clinic registers will be back captured onto REDCap, therefore making REDCap the primary data collection and storage platform for this study. A secure link-log (linking participant identifiers such as names, date of births, etc. and the PIN) database will be developed and stored in a separate REDCap database accessible only to the Principal Investigators (PIs) and those study staff granted access upon approval by the PIs.

Data storage

All study databases will be hosted on secure cloud-based platforms. Datasets will be merged using primary identifiers and stored in a secure, password-protected, web-based database which will only be accessible to authorized project staff. Paper records of participants will be kept in lockable filing cabinets. Paper records, excluding informed consent forms, will only contain PINs. Qualitative data including audio files and password-protected transcripts will be stored on a secure, access-controlled cloud-based database (Sharepoint). As per study protocol, All hard copies of data, electronic files, and databases will be stored securely for up to five years after the completion of the study or as required by the institutional review boards and prevalent South African legislation. This will be communicated to all eligible participants as part of the consenting process.

Data quality

Data quality will be assured by automated data quality checks and skip patterns in REDCap, field-based data quality clerks and office-based data administrators. Quality checks will be performed daily, with inconsistencies rectified using our data query resolution platform. Scheduled and unscheduled quality inspections will be performed on a randomly selected 10% of participants.

Data and safety monitoring

All research staff will be trained to identify, probe for and report adverse events (AEs) and social harms (SHs). Occurrence of AEs and SHs, will be collected at every visit. All AEs and SHs reported outside of research visits/activities will also be documented and reported. An AE list will be compiled and reviewed by the Data Safety and Monitoring Board (DSMB) which is set up be set up for this study and has ultimate ability to terminate the trial should interventions prove to have unacceptable risk. All DSMB members will have no direct association with this study or the study sponsors.

Ethical considerations

Consenting process

Staff will read all eligible participants a brief description of the study. Interested participants will then be read aloud the IRB-approved study consent form in their preferred language, which will provide specific information about HIV infection, the consequences and treatment of HIV, and study risks and benefits, and then will be invited to participate in the study. Those interested in the study will be consented in a safe, private space in or near the study clinic, enrolled and randomized; reasons for ineligibility or refusal will be recorded.

For adolescent boys 15–17 years old, a Ministerial waiver of parent/guardian permission was reviewed and approved by the University of Cape Town, Research Ethics Committee. This is in line with the South African National Department of Health’s 2015 publication, ‘Ethics in Health Research’, which states that ‘in particular circumstances, e.i. for reasons of sensitivity, like discussion about sexual activities, substance abuse etc., it may be desirable and ethically justifiable for minors (especially older minors i.e. 16 years and older) to choose independently i.e. without parental assistance, whether to participate in research’ [79].

Given well-established research into barriers to HIV prevention, which include parental influence, permission and household taboos around sexuality, it was deemed problematic to require potential participants aged 15–17 years to seek parental consent to participate in the study. For those participants who wish to involve a parent or guardian, the study is committed to facilitating this process. The Informed consent form for male participants has an optional signature line for a parent/guardian to sign, if the participant prefers this option. While national legal and ethical frameworks recommend acquiring parental consent when conducting research with minors, this study qualified for a waiver of this requirement, given the potential for harm that a young person might experience should they disclose their interest in participating in a study about sexual health to family members (given well-established taboos about discussing sexuality and sexual health in households), or the possibility that a youth may feel obstructed from participating due to this requirement, leading to unfairness.

Protections against risk

The risk of loss of privacy will be controlled using standard data collection protocols, trained staff with regular supervision and unique participant ID numbers on all data (including specimens) rather than participant names. Research staff will take an oath of confidentiality. Psychological stress will be reduced for HIV testing that a participant may choose as a result of study intervention (though the testing itself is not a study activity) through information and education and the use of trained staff. Participants who wish to disclose their test results to key individuals in their life will be offered help and counselling to do so by clinic staff. Furthermore, a toll-free telephone/text hotline will be set up for all participants that encounter such social harms to receive support and/or advice.

Alternative treatments and procedures

Participants from the target population invited to participate will be able to decline participation, with no consequence to them.

Confidentiality

Confidentiality of information collected is of fundamental importance. The research team will be trained to adhere to strict confidentiality guidelines and will fully protect the confidentiality of participants possible.

Sensitive questions

Participants do not have to answer any question that they do not want to and can stop answering the questions at any time. Additionally, skip patterns will be used to ensure to only ask more detailed questions to participants for whom these questions are relevant. Qualitative participants will not be pressured to disclose personal details they are not comfortable sharing.

Communication with participants

No active follow-up activities are required for Aim 1; however, should individuals referred for ART initiation not be identified within one of these three data sources within 31 days of receiving their HIV positive test result, study staff will work to actively contact, trace, and link these individuals to HIV care and treatment.

For Aim 2, to ensure follow-up of participants for the purpose of data collection/verification activities, we will employ two follow-up methods that we have successfully used in previous studies:

Method #1) Participants will be asked to provide detailed personal contact information, including their phone number(s) and home addresses for themselves, a family member, or a friend/neighbour. If a participant has a personal cell phone, the cell number will be verified by calling the phone in front of the participant. Method #2) A green sticker will be discretely placed in a participant’s medical file. This green sticker will alert clinic ART nurses that the patient is a participant in our study. When a study participant returns to the clinic for routine ART refills or VL testing, clinic pharmacists or ART nurses will be asked to refer the study participant to a RC for study activities, including booster and VL result report-back messaging.

Retention.

To observe the impact of U = U messaging on viral suppression and retention in care, no additional active follow-up activities or retention planning other than those described will be conducted. If a participant misses a clinic visit at months 6 or 12, RCs will make up to three contact attempts via phone to invite the participant to return to the clinic. If phone follow-up is not successful, research staff will work with clinic-based community tracers to contact the participant. Community tracers will not be told about the participants’ Involvement in our study.

Given that we want to observe the impact of our U = U messaging on ART adherence, viral suppression and retention in care, no additional active follow-up activities, or retention planning, other than those described, will be conducted. Should a participant be missed upon clinic attendance at months 6 or 12, RCs will make up to three attempts to make contact via phone and invite a participant to return to the clinic and complete a study questionnaire. Should follow-up by phone not be successful, research staff will work with clinic-based community tracers to contact the participant. To ensure our participants’ confidentiality, community tracers will never be told of an individual’s participation in our study. Community tracers will only know to communicate that the clinic is trying to follow up with them and to please return to the clinic.

Dissemination

The results of the study will be analysed for publication in scientific journals and presentation at relevant scientific conferences. All presentations, abstracts, or manuscripts will be submitted to the study PIs for review and approval prior to submission and no professional writers will be used. The study’s results be communicated to key stakeholder groups, such as the South African local, provincial and the national health departments. The study’s results will also be presented to study participants, community members, and clinic staff through town hall style meetings and 1-pager flyers. Key interim results, (HIV testing, linkage, and retention in care among men), will be shared with provincial and district stakeholders on a bi-annually basis. The lessons learned from implementation will also be shared with them.

Discussion

These trials are the first to rigorously evaluate the impact of U = U messaging on HIV testing uptake, ART initiation and achievement of viral suppression. Our intervention and trial design make three important contributions to the HIV prevention literature. First, we bring human-centered design and behavioral economics insights to the design of U = U messaging for men in South Africa. Previous research on U = U messaging has used conventional health communication and health behavior change theories to inform message development, with limited efforts to develop U = U messages that speak to men in Sub-Saharan Africa in particular. We collaborated with a human-centered design firm in South Africa, Matchboxology [31, 80], to understand how HIV and ART are perceived by men living with and/or affected by HIV, and to co-design messages that specifically resonated with men’s lived experience, aspirations, and preferences. Following our promising pilot study showing the potential of the U = U message to increase men’s uptake of HIV testing, our proposed study will be among the first to evaluate U = U messages at scale.

Second, our study examines the effect of U = U messages across the HIV care continuum: Most RCTs of behavioral interventions examine one specific behavior or outcome; for behavioral research on HIV, this is typically one step of the HIV care continuum. Our study is novel in testing whether U = U messaging can motivate MLHIV to test for HIV, start ART, adhere to ART, and achieve viral suppression (the most common rationale for U = U messages); as well as whether it can motivate men who don’t know their HIV status to seek HIV testing services. Our study will be among the first to test the effect of U = U messages across the HIV cascade in two sequential RCTs.

Third, we bring behavioral economics insights to both our intervention design and our identification of implementation targets. Building on prior work by our team, we adopt a behavioral economics lens both for the design of our U = U interventions for the two trials, and in our implementation inquiry. We apply the NUDGE framework [77, 78], an innovative behavioral diagnosis and design approach developed by members of our team, to identify specific barriers to implementation for U = U interventions based on stakeholder interviews. Our approach recognizes that providers, clinic managers, and policy makers are subject to the same biases and heuristic thinking in decision-making and in resource and attention allocation that PLHIV are in their decisions about testing, ART initiation, and retention. As a component of our preparations for the AIM 2 trial, we will evaluate the current utilization and integration of U = U messages within the clinics. This assessment aims to gauge the extent to which these messages are already in use or integrated into existing practices. Furthermore, we will regularly conduct landscape assessments to explore the nature of U = U messaging within the communities. This will involve observing and documenting the various forms of messaging and considering their potential influence on the study outcomes.

By conducting our study in two different provinces, including a province (Eastern Cape) where very little behavioral research on HIV interventions has been conducted, our study will produce generalizable knowledge about the impact of delivering theory-based U = U messaging at multiple points along the HIV care continuum for men in diverse communities with high burden of HIV. The inclusion of the Eastern Cape Province is a strength since community and health system voices from this part of the country are seldom heard. Eastern Cape’s ‘s resource-poor environment (compared to more typical study sites in Cape Town, Johannesburg or Durban) will provide a new and unique environment in which to understand implementation facilitators and barriers. We will also learn about implementation barriers that may limit the reach and adoption of successful interventions in clinical practice. If shown to be effective for South African men, our intervention will inform the implementation of HIV testing and ART adherence counselling guidelines in South Africa and globally.

Supporting information

S1 Appendix. Informed consent form.

https://doi.org/10.1371/journal.pone.0309905.s001

(DOCX)

References

1. 1. PCBSS_Global_AIDS_Strategy_2021–2026_EN.pdf [Internet]. [cited 2023 Aug 14]. Available from: https://www.unaids.org/sites/default/files/PCBSS_Global_AIDS_Strategy_2021—2026_EN.pdf

2. 2. Addressing a blind spot in the response to HIV—Reaching out to men and boys | UNAIDS [Internet]. [cited 2023 Aug 14]. Available from: https://www.unaids.org/en/resources/documents/2017/blind_spot

3. 3. 2020 Global AIDS Update ⁠—Seizing the moment ⁠—Tackling entrenched inequalities to end epidemics | UNAIDS [Internet]. [cited 2023 Aug 14]. Available from: https://www.unaids.org/en/resources/documents/2020/global-aids-report

4. 4. Vandormael A, Cuadros D, Kim HY, Bärnighausen T, Tanser F. Vandormael A, Cuadros D, et al. The state of the HIV epidemic in rural KwaZulu-Natal, South Africa: a novel application of disease metrics to assess trajectories and highlight areas for intervention. Int J Epidemiol. 2020 Apr 1;49(2):666–675. pmid:31930292; PMCID: PMC7266544. Int J Epidemiol. 2020 Apr 1;49(2):666–75.

* View Article

* PubMed/NCBI

* Google Scholar

5. 5. Vandormael A, Akullian A, Siedner M, de Oliveira T, Bärnighausen T, Tanser F. Vandormael A, et al. Declines in HIV incidence among men and women in a South African population-based cohort. Nat Commun. 2019 Dec 2;10(1):5482. pmid:31792217; PMCID: PMC6889466. Nat Commun. 2019 Dec 2;10(1):5482.

* View Article

* PubMed/NCBI

* Google Scholar

6. 6. Nakigozi G, Chang L, Reynolds S, Nalugoda F, Kigozi G, Quinn T, Gray R, Kisakye A, Ndyanabo A, Ssekubugu R, Serwadda D, Wawer M, Kagaayi J, Grabowski M. Rapidly declining HIV incidence among men and women in Rakai, Uganda. Conference on Retroviruses and Opportunistic Infections (CROI); 2020 Mar 8; Boston. [Internet]. [cited 2023 Aug 16]. Available from: https://www.healio.com/news/infectious-disease/20200312/hiv-incidence-declines-among-men-women-in-rakai-uganda

* View Article

* Google Scholar

7. 7. Pulerwitz J, Gottert A, Kahn K, Haberland N, Julien A, Selin A, et al. Gender Norms and HIV Testing/Treatment Uptake: Evidence from a Large Population-Based Sample in South Africa. AIDS Behav. 2019 Sep;23(Suppl 2):162–171. pmid:31359218; PMCID: PMC6773668. AIDS and behavior [Internet]. 2019 Sep [cited 2023 Nov 21];23(Suppl 2). Available from: https://pubmed.ncbi.nlm.nih.gov/31359218/

* View Article

* PubMed/NCBI

* Google Scholar

8. 8. Bor J, Rosen S, Chimbindi N, Haber N, Herbst K, Mutevedzi T, et al. Mass HIV Treatment and Sex Disparities in Life Expectancy: Demographic Surveillance in Rural South Africa. PLoS Med. 2015 Nov 24;12(11):e1001905; discussion e1001905. pmid:26599699; PMCID: PMC4658174. [Internet]. [cited 2023 Nov 21]. Available from: https://pubmed.ncbi.nlm.nih.gov/26599699/

* View Article

* PubMed/NCBI

* Google Scholar

9. 9. Cornell M, Schomaker M, Garone DB, Giddy J, Hoffmann CJ, Lessells R, et al. Gender differences in survival among adult patients starting antiretroviral therapy in South Africa: a multicentre cohort study. PLoS Med. 2012;9(9):e1001304. Epub 2012 Sep 4. pmid:22973181; PMCID: PMC3433409. PLoS medicine [Internet]. 2012 [cited 2023 Nov 21];9(9). Available from: https://pubmed.ncbi.nlm.nih.gov/22973181/

* View Article

* PubMed/NCBI

* Google Scholar

10. 10. Osler M, Cornell M, Ford N, Hilderbrand K, Goemaere E, Boulle A. Osler M, et al. Population-wide differentials in HIV service access and outcomes in the Western Cape for men as compared to women, South Africa: 2008 to 2018: a cohort analysis. J Int AIDS Soc. 2020 Jun;23 Suppl 2:e25530. PMCID: PMC7319137. J Intern AIDS Soc [Internet]. 2020 Jun [cited 2023 Aug 14];23(S2). Available from: https://onlinelibrary.wiley.com/doi/10.1002/jia2.25530 pmid:32589367

* View Article

* PubMed/NCBI

* Google Scholar

11. 11. Davey DJ, Kehoe K, Serrao C, Prins M, Mkhize N, Hlophe K, et al. Same-day antiretroviral therapy is associated with increased loss to follow-up in South African public health facilities: a prospective cohort study of patients diagnosed with HIV. J Int AIDS Soc. 2020 Jun;23(6):e25529. pmid:32510186; PMCID: PMC7277782. Journal of the International AIDS Society [Internet]. 2020 Jun [cited 2023 Nov 21];23(6). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7277782/

* View Article

* PubMed/NCBI

* Google Scholar

12. 12. Kranzer K, Lewis JJ, Ford N, Zeinecker J, Orrell C, Lawn SD, Bekker LG, Wood R. Treatment interruption in a primary care antiretroviral therapy program in South Africa: cohort analysis of trends and risk factors. J Acquir Immune Defic Syndr. 2010 Nov;55(3):e17–23. pmid:20827216; PMCID: PMC3024539. [Internet]. [cited 2023 Nov 21]. Available from: https://pubmed.ncbi.nlm.nih.gov/20827216/

* View Article

* PubMed/NCBI

* Google Scholar

13. 13. Beckham SW, Beyrer C, Luckow P, Doherty M, Negussie EK, Baral SD. Marked sex differences in all-cause mortality on antiretroviral therapy in low- and middle-income countries: a systematic review and meta-analysis. J Int AIDS Soc. 2016 Nov 8;19(1):21106. pmid:27834182; PMCID: PMC5103676. Journal of the International AIDS Society [Internet]. 2016 Nov 8 [cited 2023 Nov 21];19(1). Available from: https://pubmed.ncbi.nlm.nih.gov/27834182/

* View Article

* PubMed/NCBI

* Google Scholar

14. 14. Plazy M, Dray-Spira R, Orne-Gliemann J, Dabis F, Newell ML. Continuum in HIV care from entry to ART initiation in rural KwaZulu-Natal, South Africa. Trop Med Int Health. 2014 Jun;19(6):680–689. Epub 2014 Mar 21. pmid:24654990. [Internet]. [cited 2023 Nov 21]. Available from: https://pubmed.ncbi.nlm.nih.gov/24654990/

* View Article

* PubMed/NCBI

* Google Scholar

15. 15. Rodger AJ, Cambiano V, Bruun T, Vernazza P, Collins S, van Lunzen J, et al. Sexual Activity Without Condoms and Risk of HIV Transmission in Serodifferent Couples When the HIV-Positive Partner Is Using Suppressive Antiretroviral Therapy. JAMA. 2016 Jul 12;316(2):171–81. pmid:27404185

* View Article

* PubMed/NCBI

* Google Scholar

16. 16. Cohen MS, Chen YQ, McCauley M, Gamble T, Hosseinipour MC, Kumarasamy N, et al. Antiretroviral Therapy for the Prevention of HIV-1 Transmission. N Engl J Med. 2016 Sep 1;375(9):830–9. pmid:27424812

* View Article

* PubMed/NCBI

* Google Scholar

17. 17. Bavinton BR, Pinto AN, Phanuphak N, Grinsztejn B, Prestage GP, Zablotska-Manos IB, et al. Viral suppression and HIV transmission in serodiscordant male couples: an international, prospective, observational, cohort study. Lancet HIV. 2018 Aug;5(8):e438–47. pmid:30025681

* View Article

* PubMed/NCBI

* Google Scholar

18. 18. Rodger AJ, Cambiano V, Bruun T, Vernazza P, Collins S, Degen O, et al. Risk of HIV transmission through condomless sex in serodifferent gay couples with the HIV-positive partner taking suppressive antiretroviral therapy (PARTNER): final results of a multicentre, prospective, observational study. Lancet. 2019 Jun 15;393(10189):2428–38. pmid:31056293

* View Article

* PubMed/NCBI

* Google Scholar

19. 19. Prevention-Access-Campaign-Consensus-Statement.pdf [Internet]. [cited 2023 Aug 15]. Available from: https://www.pwatoronto.org/wp-content/uploads/2017/10/2017-Prevention-Access-Campaign-Consensus-Statement.pdf

20. 20. Eisinger RW, Dieffenbach CW, Fauci AS. Eisinger RW, Dieffenbach CW, Fauci AS. HIV Viral Load and Transmissibility of HIV Infection: Undetectable Equals Untransmittable. JAMA. 2019 Feb 5;321(5):451–452. pmid:30629090. JAMA. 2019 Feb 1;321(5):451–2.

* View Article

* PubMed/NCBI

* Google Scholar

21. 21. Broyles LN, Luo R, Boeras D, Vojnov L. Broyles LN, Luo R, et al. The risk of sexual transmission of HIV in individuals with low-level HIV viraemia: a systematic review. Lancet. 2023 Aug 5;402(10400):464–471. Epub 2023 Jul 22. pmid:37490935; PMCID: PMC10415671. Lancet. 2023 Aug 5;402(10400):464–71.

* View Article

* PubMed/NCBI

* Google Scholar

22. 22. Bekker LG, Smith P, Ntusi NAB. Bekker LG, Smith P, Ntusi NAB. HIV is sexually untransmittable when viral load is undetectable. Lancet. 2023 Aug 5;402(10400):428–429. Epub 2023 Jul 22. pmid:37490934. Lancet. 2023 Aug 5;402(10400):428–9.

* View Article

* PubMed/NCBI

* Google Scholar

23. 23. NUDGE: Improving Decisions About Health, Wealth, and Happiness [Internet]. [cited 2023 Aug 15]. Available from: https://www.researchgate.net/publication/235413094_NUDGE_Improving_Decisions_About_Health_Wealth_and_Happiness

24. 24. Millar MG, Millar K. Millar MG, Millar K. Negative affective consequences of thinking about disease detection behaviors. Health Psychol. 1995 Mar;14(2):141–6. pmid:7789349. Health Psychol. 1995 Mar;14(2):141–6.

* View Article

* PubMed/NCBI

* Google Scholar

25. 25. Rice T. Rice T. The behavioral economics of health and health care. Annu Rev Public Health. 2013;34:431–47. Epub 2013 Jan 7. pmid:23297657. Annu Rev Public Health. 2013;34:431–47.

* View Article

* PubMed/NCBI

* Google Scholar

26. 26. Arndt J, Goldenberg JL. Arndt J, Goldenberg JL. Where Health and Death Intersect: Insights from a Terror Management Health Model. Curr Dir Psychol Sci. 2017;26(2):126–131. Epub 2017 Apr 6. pmid:28924332; PMCID: PMC5600513. Curr Dir Psychol Sci. 2017;26(2):126–31.

* View Article

* PubMed/NCBI

* Google Scholar

27. 27. Catalani C, Green E, Owiti P, Keny A, Diero L, Yeung A, et al. A clinical decision support system for integrating tuberculosis and HIV care in Kenya: a human-centered design approach. PLoS One. 2014 Aug 29;9(8):e103205. pmid:25170939; PMCID: PMC4149343. PLoS One. 2014;9(8):e103205.

* View Article

* PubMed/NCBI

* Google Scholar

28. 28. Harte R, Glynn L, Rodríguez-Molinero A, Baker PM, Scharf T, Quinlan LR, et al. A Human-Centered Design Methodology to Enhance the Usability, Human Factors, and User Experience of Connected Health Systems: A Three-Phase Methodology. JMIR Hum Factors. 2017 Mar 16;4(1):e8. pmid:28302594; PMCID: PMC5374275. JMIR Hum Factors. 2017 Mar 16;4(1):e8.

* View Article

* PubMed/NCBI

* Google Scholar

29. 29. Beres LK, Simbeza S, Holmes CB, Mwamba C, Mukamba N, Sharma A, et al. Human-Centered Design Lessons for Implementation Science: Improving the Implementation of a Patient-Centered Care Intervention. J Acquir Immune Defic Syndr. 2019 Dec;82 Suppl 3(3):S230–S243. Erratum in: J Acquir Immune Defic Syndr. 2020 May 1;84(1):e10. pmid:31764259; PMCID: PMC6880397. J Acquir Immune Defic Syndr. 2019 Dec;82 Suppl 3(3):S230–43.

* View Article

* PubMed/NCBI

* Google Scholar

30. 30. Bazzano AN, Martin J, Hicks E, Faughnan M, Murphy L. Bazzano AN, et al. Human-centred design in global health: A scoping review of applications and contexts. PLoS One. 2017 Nov 1;12(11):e0186744. pmid:29091935; PMCID: PMC5665524. PLoS One. 2017;12(11):e0186744.

* View Article

* PubMed/NCBI

* Google Scholar

31. 31. Matheson GO, Pacione C, Shultz RK, Klügl M. Matheson GO, Pacione C, Shultz RK, et al. Leveraging human-centered design in chronic disease prevention. Am J Prev Med. 2015 Apr;48(4):472–9. Epub 2015 Feb 18. pmid:25700655. Am J Prev Med. 2015 Apr;48(4):472–9.

* View Article

* PubMed/NCBI

* Google Scholar

32. 32. Smith PJ, Joseph Davey DL, Schmucker L, Bruns C, Bekker LG, Medina-Marino A, et al. Participatory Prototyping of a Tailored Undetectable Equals Untransmittable Message to Increase HIV Testing Among Men in Western Cape, South Africa. AIDS Patient Care STDS. 2021 Nov;35(11):428–434. pmid:34739334. AIDS Patient Care STDS. 2021 Nov;35(11):428–34.

* View Article

* PubMed/NCBI

* Google Scholar

33. 33. Prevention Access Campaign–The revolution in living and loving with HIV [Internet]. [cited 2023 Aug 15]. Available from: https://preventionaccess.org/

34. 34. Calabrese SK, Mayer KH. Calabrese SK, Mayer KH. Providers should discuss U = U with all patients living with HIV. Lancet HIV. 2019 Apr;6(4):e211–e213. pmid:30772420. Lancet HIV. 2019 Apr;6(4):e211–3.

* View Article

* PubMed/NCBI

* Google Scholar

35. 35. Siegel K, Meunier É. Siegel K, Meunier É. Awareness and Perceived Effectiveness of HIV Treatment as Prevention Among Men Who Have Sex with Men in New York City. AIDS Behav. 2019 Jul;23(7):1974–1983. pmid:30697639. AIDS Behav. 2019 Jul;23(7):1974–83.

* View Article

* PubMed/NCBI

* Google Scholar

36. 36. Card KG, Armstrong HL, Lachowsky NJ, Cui Z, Sereda P, Carter MA, et al. Belief in Treatment as Prevention and Its Relationship to HIV Status and Behavioral Risk. J Acquir Immune Defic Syndr. 2018 Jan 1;77(1):8–16. pmid:28991882; PMCID: PMC5753790. J Acquir Immune Defic Syndr. 2018 Jan 1;77(1):8–16.

* View Article

* PubMed/NCBI

* Google Scholar

37. 37. Carter A, Lachowsky N, Rich A, Forrest JI, Sereda P, Cui Z, et al. Gay and bisexual men’s awareness and knowledge of treatment as prevention: findings from the Momentum Health Study in Vancouver, Canada. J Int AIDS Soc. 2015 Aug 11;18(1):20039. pmid:26268817; PMCID: PMC4534712. J Int AIDS Soc. 2015;18(1):20039.

* View Article

* PubMed/NCBI

* Google Scholar

38. 38. Rendina HJ, Cienfuegos-Szalay J, Talan A, Jones SS, Jimenez RH. Rendina HJ, et al. Growing Acceptability of Undetectable = Untransmittable but Widespread Misunderstanding of Transmission Risk: Findings From a Very Large Sample of Sexual Minority Men in the United States. J Acquir Immune Defic Syndr. 2020 Mar 1;83(3):215–222. pmid:31809309; PMCID: PMC7341443. J Acquir Immune Defic Syndr. 2020 Mar 1;83(3):215–22.

* View Article

* PubMed/NCBI

* Google Scholar

39. 39. Paschen-Wolff MM, Campbell ANC, Tross S, Castro M, Berg H, Braunstein S, et al. HIV Treatment Knowledge in the Context of “Treatment as Prevention” (TasP). AIDS Behav. 2020 Oct;24(10):2984–2994. pmid:32246359; PMCID: PMC7483279. AIDS Behav. 2020 Oct;24(10):2984–94.

* View Article

* PubMed/NCBI

* Google Scholar

40. 40. Ngure K, Ongolly F, Dolla A, Awour M, Mugwanya KK, Irungu E, et al. “I just believe there is a risk” understanding of undetectable equals untransmissible (U = U) among health providers and HIV-negative partners in serodiscordant relationships in Kenya. J Int AIDS Soc. 2020 Mar;23(3):e25466. pmid:32144888; PMCID: PMC7060133. Journal of the International AIDS Society. 2020;23(3):e25466.

* View Article

* PubMed/NCBI

* Google Scholar

41. 41. Holt M, Lea T, Schmidt HM, Murphy D, Rosengarten M, Crawford D, et al. Increasing Belief in the Effectiveness of HIV Treatment as Prevention: Results of Repeated, National Surveys of Australian Gay and Bisexual Men, 2013–15. AIDS Behav. 2016 Jul;20(7):1564–71. pmid:26803613. AIDS and Behavior. 2016 Jul 1;20.

* View Article

* PubMed/NCBI

* Google Scholar

42. 42. Making the invisible, visible: a cross-sectional study of late presentation to HIV/AIDS services among men who have sex with men from a large urban center of Brazil | BMC Public Health | Full Text [Internet]. [cited 2023 Aug 15]. Available from: https://bmcpublichealth.biomedcentral.com/articles/10.1186/1471-2458-14-1313

43. 43. Ndyabakira A, Chamie G, Emperador D, Marson K, Kamya M, Havlir D, et al. Men’s Beliefs About the Likelihood of Serodiscordance in Couples with an HIV-Positive Partner: Survey Evidence from Rural Uganda. AIDS Behav. 2020 Mar;24(3):967–974. pmid:31073946. AIDS and Behavior. 2020 Mar 1;24.

* View Article

* PubMed/NCBI

* Google Scholar

44. 44. Prati G, Zani B, Pietrantoni L, Scudiero D, Perone P, Cosmaro L, et al. PEP and TasP Awareness among Italian MSM, PLWHA, and High-Risk Heterosexuals and Demographic, Behavioral, and Social Correlates. PLoS One. 2016 Jun 13;11(6):e0157339. pmid:27294777; PMCID: PMC4905673. PLoS One. 2016;11(6):e0157339.

* View Article

* PubMed/NCBI

* Google Scholar

45. 45. Couffignal C, Papot E, Etienne A, Legac S, Laouénan C, Beres D, et al. Treatment as prevention (TasP) and perceived sexual changes in behavior among HIV-positive persons: a French survey in infectious diseases departments in Paris. AIDS Care. 2020 Jul;32(7):811–817. Epub 2019 Aug 21. pmid:31431047. AIDS Care. 2020 Jul 2;32(7):811–7.

* View Article

* PubMed/NCBI

* Google Scholar

46. 46. Newman CE, de Wit J, Persson A, Holt M, Slavin S, Kidd MR, et al. Understanding Concerns About Treatment-as-Prevention Among People with HIV who are not Using Antiretroviral Therapy. AIDS Behav. 2015 May;19(5):821–31. pmid:25432878. AIDS Behav. 2015 May;19(5):821–31.

* View Article

* PubMed/NCBI

* Google Scholar

47. 47. Bavinton BR, Holt M, Grulich AE, Brown G, Zablotska IB, Prestage GP. Bavinton BR, et al. Willingness to Act upon Beliefs about “Treatment as Prevention” among Australian Gay and Bisexual Men. PLoS One. 2016 Jan 7;11(1):e0145847. pmid:26741143; PMCID: PMC4704706. PLOS ONE. 2016 Jan 7;11(1):e0145847.

* View Article

* PubMed/NCBI

* Google Scholar

48. 48. Bor J, Fischer C, Modi M, Richman B, Kinker C, King R, et al. Changing Knowledge and Attitudes Towards HIV Treatment-as-Prevention and “Undetectable  =  Untransmittable”: A Systematic Review. AIDS Behav. 2021 Dec;25(12):4209–4224. Epub 2021 May 25. pmid:34036459; PMCID: PMC8147591. AIDS Behav. 2021;25(12):4209–24.

* View Article

* PubMed/NCBI

* Google Scholar

49. 49. Kalichman SC, Cherry C, Kalichman MO, Amaral CM, White D, Pope H, et al. Integrated behavioral intervention to improve HIV/AIDS treatment adherence and reduce HIV transmission. Am J Public Health. 2011 Mar;101(3):531–8. Epub 2011 Jan 13. pmid:21233431; PMCID: PMC3036694. Am J Public Health. 2011 Mar;101(3):531–8.

* View Article

* PubMed/NCBI

* Google Scholar

50. 50. Kalichman SC, Cherry C, Kalichman MO, Eaton LA, Kohler J, Montero C, et al. Mobile Health Intervention to Reduce HIV Transmission: A Randomized Trial of Behaviorally Enhanced HIV Treatment as Prevention (B-TasP). J Acquir Immune Defic Syndr. 2018 May 1;78(1):34–42. pmid:29406429; PMCID: PMC5889341. J Acquir Immune Defic Syndr. 2018 May 1;78(1):34–42.

* View Article

* PubMed/NCBI

* Google Scholar

51. 51. Curran GM, Bauer M, Mittman B, Pyne JM, Stetler C. Curran GM, Bauer M, et al. Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact. Med Care. 2012 Mar;50(3):217–26. pmid:22310560; PMCID: PMC3731143. Med Care. 2012 Mar;50(3):217–26.

* View Article

* PubMed/NCBI

* Google Scholar

52. 52. Curran GM, Landes SJ, McBain SA, Pyne JM, Smith JD, Fernandez ME, et al. Reflections on 10 years of effectiveness-implementation hybrid studies. Front Health Serv. 2022 Dec 8;2:1053496. pmid:36925811; PMCID: PMC10012680. Front Health Serv. 2022;2:1053496.

* View Article

* PubMed/NCBI

* Google Scholar

53. 53. Johnson LF, Dorrington RE, Moolla H. Johnson LF, Dorrington RE, Moolla H. Progress towards the 2020 targets for HIV diagnosis and antiretroviral treatment in South Africa. South Afr J HIV Med. 2017 Jul 27;18(1):694. pmid:29568630; PMCID: PMC5843157. South Afr J HIV Med. 2017 Jul 27;18(1):694.

* View Article

* PubMed/NCBI

* Google Scholar

54. 54. Johnson L, Dorrington R. Thembisa version 4.6: A model for evaluating the impact of HIV/AIDS in South Africa.

55. 55. Medina-Marino A, Bezuidenhout D, Ngwepe P, Bezuidenhout C, Facente SN, Mabandla S, et al. Acceptability and feasibility of leveraging community-based HIV counselling and testing platforms for same-day oral PrEP initiation among adolescent girls and young women in Eastern Cape, South Africa. J Int AIDS Soc. 2022 Jul;25(7):e25968. pmid:35872602; PMCID: PMC9309460. J Int AIDS Soc. 2022 Jul;25(7):e25968.

* View Article

* PubMed/NCBI

* Google Scholar

56. 56. van Schaik N, Kranzer K, Wood R, Bekker LG. van Schaik N, Kranzer K, et al. Earlier HIV diagnosis—are mobile services the answer? S Afr Med J. 2010 Oct 1;100(10):671–4. pmid:21080998. S Afr Med J. 2010 Oct 1;100(10):671–4.

* View Article

* PubMed/NCBI

* Google Scholar

57. 57. Govindasamy D, Kranzer K, van Schaik N, Noubary F, Wood R, Walensky RP, et al. Linkage to HIV, TB and non-communicable disease care from a mobile testing unit in Cape Town, South Africa. PLoS One. 2013 Nov 13;8(11):e80017. pmid:24236170; PMCID: PMC3827432. PLoS One. 2013 Nov 13;8(11):e80017.

* View Article

* PubMed/NCBI

* Google Scholar

58. 58. Medina-Marino A, Daniels J, Bezuidenhout D, Peters R, Farirai T, Slabbert J, et al. Outcomes from a multimodal, at-scale community-based HIV counselling and testing programme in twelve high HIV burden districts in South Africa. J Int AIDS Soc. 2021 Mar;24(3):e25678. pmid:33709542; PMCID: PMC7952633. J Int AIDS Soc. 2021 Mar;24(3):e25678.

* View Article

* PubMed/NCBI

* Google Scholar

59. 59. Medina-Marino A, Bezuidenhout D, Hosek S, Barnabas RV, Atujuna M, Bezuidenhout C, et al. The Community PrEP Study: a randomized control trial leveraging community-based platforms to improve access and adherence to pre-exposure prophylaxis to prevent HIV among adolescent girls and young women in South Africa-study protocol. Trials. 2021 Jul 26;22(1):489. pmid:34311754; PMCID: PMC8314507. Trials. 2021 Jul 26;22(1):489.

* View Article

* PubMed/NCBI

* Google Scholar

60. 60. Smith PJ, Daniels J, Bekker LG, Medina-Marino A. Smith PJ, Daniels J, Bekker LG, et al. What motivated men to start PrEP? A cross-section of men starting PrEP in Buffalo city municipality, South Africa. BMC Public Health. 2023 Mar 2;23(1):418. pmid:36864381; PMCID: PMC9979577. BMC Public Health. 2023 Mar 2;23:418.

* View Article

* PubMed/NCBI

* Google Scholar

61. 61. Smith P, Buttenheim A, Schmucker L, Bekker LG, Thirumurthy H, Davey DLJ. Smith P, et al. Undetectable  =  Untransmittable (U  =  U) Messaging Increases Uptake of HIV Testing Among Men: Results from a Pilot Cluster Randomized Trial. AIDS Behav. 2021 Oct;25(10):3128–3136. Epub 2021 May 31. pmid:34057659; PMCID: PMC8165342. AIDS Behav. 2021;25(10):3128–36.

* View Article

* PubMed/NCBI

* Google Scholar

62. 62. South African National Department of Health. HIV Testing Services: Policy 2016 [Internet]. Pretoria, South Africa; 2016 Jul [cited 2020 Dec 29]. Available from: https://sahivsoc.org/Files/HTS%20Policy%2028%20July%20final%20copy.pdf

* View Article

* Google Scholar

63. 63. Hemming K, Kasza J, Hooper R, Forbes A, Taljaard M. Hemming K, Kasza J, et al. A tutorial on sample size calculation for multiple-period cluster randomized parallel, cross-over and stepped-wedge trials using the Shiny CRT Calculator. Int J Epidemiol. 2020 Jun 1;49(3):979–995. pmid:32087011; PMCID: PMC7394950. Int J Epidemiol. 2020 Jun 1;49(3):979–95.

* View Article

* PubMed/NCBI

* Google Scholar

64. 64. Stein A, Ramaseshan B. Towards the identification of customer experience touch point elements. Journal of Retailing and Consumer Services. 2016 May 1;30:8–19.

* View Article

* Google Scholar

65. 65. Bauermeister JA, Golinkoff JM, Muessig KE, Horvath KJ, Hightow-Weidman LB. Bauermeister JA, Golinkoff JM et al. Addressing engagement in technology-based behavioural HIV interventions through paradata metrics. Curr Opin HIV AIDS. 2017 Sep;12(5):442–446. pmid:28617711; PMCID: PMC5637536. Curr Opin HIV AIDS. 2017 Sep;12(5):442–6.

* View Article

* PubMed/NCBI

* Google Scholar

66. 66. Lynch KG, Cary M, Gallop R, Ten Have TR. Lynch KG, Cary M, et al. Causal Mediation Analyses for Randomized Trials. Health Serv Outcomes Res Methodol. 2008;8(2):57–76. pmid:19484136; PMCID: PMC2688317. Health Serv Outcomes Res Methodol. 2008;8(2):57–76.

* View Article

* PubMed/NCBI

* Google Scholar

67. 67. National Consolidated Guidelines 30062020 signed PRINT v7.pdf [Internet]. [cited 2023 Aug 15]. Available from: https://knowledgehub.health.gov.za/system/files/elibdownloads/2020-07/National%20Consolidated%20Guidelines%2030062020%20signed%20PRINT%20v7.pdf

68. 68. National Department of Health. Adherence Guidelines for HIV, TB and NCDs [Internet]. Republic of South Africa National Department of Health; 2016 [cited 2021 Apr 17]. Available from: https://www.nacosa.org.za/wp-content/uploads/2018/05/SOP-Adherence-counselling-A5-booklet-19-03-2017.pdf

69. 69. Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Damschroder LJ, et al. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009 Aug 7;4:50. pmid:19664226; PMCID: PMC2736161. Implement Sci. 2009 Aug 7;4:50.

* View Article

* PubMed/NCBI

* Google Scholar

70. 70. King DK, Shoup JA, Raebel MA, Anderson CB, Wagner NM, Ritzwoller DP, et al. Planning for Implementation Success Using RE-AIM and CFIR Frameworks: A Qualitative Study. Front Public Health. 2020 Mar 3;8:59. pmid:32195217; PMCID: PMC7063029. Front Public Health. 2020;8:59.

* View Article

* PubMed/NCBI

* Google Scholar

71. 71. Glasgow RE, Estabrooks PE. Glasgow RE, Estabrooks PE. Pragmatic Applications of RE-AIM for Health Care Initiatives in Community and Clinical Settings. Prev Chronic Dis. 2018 Jan 4;15:E02. pmid:29300695; PMCID: PMC5757385. Prev Chronic Dis. 2018 Jan 4;15:E02.

* View Article

* PubMed/NCBI

* Google Scholar

72. 72. Glasgow RE, Harden SM, Gaglio B, Rabin B, Smith ML, Porter GC, et al. RE-AIM Planning and Evaluation Framework: Adapting to New Science and Practice With a 20-Year Review. Front Public Health. 2019 Mar 29;7:64. pmid:30984733; PMCID: PMC6450067. Front Public Health. 2019;7:64.

* View Article

* PubMed/NCBI

* Google Scholar

73. 73. Damschroder LJ, Reardon CM, Widerquist MAO, Lowery J. Damschroder LJ Reardon CM, Widerquist MAO, et al. The updated Consolidated Framework for Implementation Research based on user feedback. Implement Sci. 2022 Oct 29;17(1):75. pmid:36309746; PMCID: PMC9617234. Implementation Science. 2022 Oct 29;17(1):75.

* View Article

* PubMed/NCBI

* Google Scholar

74. 74. Beidas RS, Buttenheim AM, Mandell DS. Beidas RS, Buttenheim AM, Mandell DS. Transforming Mental Health Care Delivery Through Implementation Science and Behavioral Economics. JAMA Psychiatry. 2021 Sep 1;78(9):941–942. pmid:34076686; PMCID: PMC8744069. JAMA Psychiatry. 2021 Sep 1;78(9):941–2.

* View Article

* PubMed/NCBI

* Google Scholar

75. 75. Mandimika C, Bokolo S, ChettyMakkan C, Long L, Mistri P, Schmucker L, et al. The NUDGE Handbook: A practical guide to behavioural design based on the NUDGE framework. Version 2. June 2023. Indlela Behavioural Insights Unit. Available at https://indlela.org/nudge-handbookTimelines.

* View Article

* Google Scholar

76. 76. Swain J. A Hybrid Approach to Thematic Analysis in Qualitative Research: Using a Practical Example. 2018.

* View Article

* Google Scholar

77. 77. Brewer JD, Shinnick J, Román K, Santos MP, Paz-Soldan VA, Buttenheim AM. Brewer JD, et al Behavioral Insights Into Micronutrient Powder Use for Childhood Anemia in Arequipa, Peru. Glob Health Sci Pract. 2020 Dec 23;8(4):721–731. pmid:33361238; PMCID: PMC7784068. Glob Health Sci Pract. 2020 Dec 23;8(4):721–31.

* View Article

* PubMed/NCBI

* Google Scholar

78. 78. Stewart RE, Beidas RS, Last BS, Hoskins K, Byeon YV, Williams NJ, et al. Applying NUDGE to Inform Design of EBP Implementation Strategies in Community Mental Health Settings. Adm Policy Ment Health. 2021 Jan;48(1):131–142. pmid:32430590; PMCID: PMC8092115. Adm Policy Ment Health. 2021 Jan;48(1):131–42.

* View Article

* PubMed/NCBI

* Google Scholar

79. 79. NHREC-DoH-2015-Ethics-in-Health-Research-Guidelines-1.pdf [Internet]. [cited 2023 Nov 21]. Available from: https://www.health.gov.za/wp-content/uploads/2022/05/NHREC-DoH-2015-Ethics-in-Health-Research-Guidelines-1.pdf

80. 80. Matchboxology [Internet]. [cited 2023 Aug 15]. Available from: https://matchboxology.com/.

Citation: Medina-Marino A, Sibanda N, Putt M, Joseph Davey D, Smith P, Thirumurthy H, et al. (2024) Improving HIV testing, linkage, and retention in care among South African men through U = U messaging: A study protocol for two sequential hybrid type 1 effectiveness-implementation randomized controlled trials. PLoS ONE 19(11): e0309905. https://doi.org/10.1371/journal.pone.0309905

About the Authors:

Andrew Medina-Marino

Roles: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing

E-mail: [email protected] (AMM); [email protected] (AB)

Affiliations: Desmond Tutu HIV Centre, University of Cape Town, Cape Town, South Africa, Desmond Tutu Health Foundation, Cape Town, South Africa, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America

ORICD: https://orcid.org/0000-0002-2691-982X

Nkosiyapha Sibanda

Roles: Investigation, Project administration, Supervision, Writing – original draft, Writing – review & editing

Affiliations: Desmond Tutu HIV Centre, University of Cape Town, Cape Town, South Africa, Desmond Tutu Health Foundation, Cape Town, South Africa

Mary Putt

Roles: Conceptualization, Data curation, Formal analysis, Methodology, Supervision, Writing – original draft, Writing – review & editing

Affiliation: Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America

Dvora Joseph Davey

Roles: Conceptualization, Formal analysis, Investigation, Methodology, Supervision, Writing – review & editing

Affiliations: Desmond Tutu HIV Centre, University of Cape Town, Cape Town, South Africa, Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States of America, Division of Infectious Diseases, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America, Division of Epidemiology & Biostatistics, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa

Phillip Smith

Roles: Conceptualization, Investigation, Project administration, Supervision, Writing – review & editing

Affiliations: Desmond Tutu HIV Centre, University of Cape Town, Cape Town, South Africa, Desmond Tutu Health Foundation, Cape Town, South Africa

Harsha Thirumurthy

Roles: Conceptualization, Funding acquisition, Methodology, Writing – review & editing

Affiliations: Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America, Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA, United States of America

Linda-Gail Bekker

Roles: Conceptualization, Funding acquisition, Resources, Writing – review & editing

Affiliations: Desmond Tutu HIV Centre, University of Cape Town, Cape Town, South Africa, Desmond Tutu Health Foundation, Cape Town, South Africa

Alison Buttenheim

Roles: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Supervision, Writing – original draft, Writing – review & editing

E-mail: [email protected] (AMM); [email protected] (AB)

Affiliations: Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA, United States of America, Department of Family and Community Health, School of Nursing, University of Pennsylvania, Philadelphia PA, United States of America

[/RAW_REF_TEXT]

[/RAW_REF_TEXT]

[/RAW_REF_TEXT]

[/RAW_REF_TEXT]

[/RAW_REF_TEXT]

[/RAW_REF_TEXT]

[/RAW_REF_TEXT]

[/RAW_REF_TEXT]

[/RAW_REF_TEXT]

[/RAW_REF_TEXT]

[/RAW_REF_TEXT]

[/RAW_REF_TEXT]

References

1. PCBSS_Global_AIDS_Strategy_2021–2026_EN.pdf [Internet]. [cited 2023 Aug 14]. Available from: https://www.unaids.org/sites/default/files/PCBSS_Global_AIDS_Strategy_2021—2026_EN.pdf

2. Addressing a blind spot in the response to HIV—Reaching out to men and boys | UNAIDS [Internet]. [cited 2023 Aug 14]. Available from: https://www.unaids.org/en/resources/documents/2017/blind_spot

3. 2020 Global AIDS Update ⁠—Seizing the moment ⁠—Tackling entrenched inequalities to end epidemics | UNAIDS [Internet]. [cited 2023 Aug 14]. Available from: https://www.unaids.org/en/resources/documents/2020/global-aids-report

4. Vandormael A, Cuadros D, Kim HY, Bärnighausen T, Tanser F. Vandormael A, Cuadros D, et al. The state of the HIV epidemic in rural KwaZulu-Natal, South Africa: a novel application of disease metrics to assess trajectories and highlight areas for intervention. Int J Epidemiol. 2020 Apr 1;49(2):666–675. pmid:31930292; PMCID: PMC7266544. Int J Epidemiol. 2020 Apr 1;49(2):666–75.

5. Vandormael A, Akullian A, Siedner M, de Oliveira T, Bärnighausen T, Tanser F. Vandormael A, et al. Declines in HIV incidence among men and women in a South African population-based cohort. Nat Commun. 2019 Dec 2;10(1):5482. pmid:31792217; PMCID: PMC6889466. Nat Commun. 2019 Dec 2;10(1):5482.

6. Nakigozi G, Chang L, Reynolds S, Nalugoda F, Kigozi G, Quinn T, Gray R, Kisakye A, Ndyanabo A, Ssekubugu R, Serwadda D, Wawer M, Kagaayi J, Grabowski M. Rapidly declining HIV incidence among men and women in Rakai, Uganda. Conference on Retroviruses and Opportunistic Infections (CROI); 2020 Mar 8; Boston. [Internet]. [cited 2023 Aug 16]. Available from: https://www.healio.com/news/infectious-disease/20200312/hiv-incidence-declines-among-men-women-in-rakai-uganda

7. Pulerwitz J, Gottert A, Kahn K, Haberland N, Julien A, Selin A, et al. Gender Norms and HIV Testing/Treatment Uptake: Evidence from a Large Population-Based Sample in South Africa. AIDS Behav. 2019 Sep;23(Suppl 2):162–171. pmid:31359218; PMCID: PMC6773668. AIDS and behavior [Internet]. 2019 Sep [cited 2023 Nov 21];23(Suppl 2). Available from: https://pubmed.ncbi.nlm.nih.gov/31359218/

8. Bor J, Rosen S, Chimbindi N, Haber N, Herbst K, Mutevedzi T, et al. Mass HIV Treatment and Sex Disparities in Life Expectancy: Demographic Surveillance in Rural South Africa. PLoS Med. 2015 Nov 24;12(11):e1001905; discussion e1001905. pmid:26599699; PMCID: PMC4658174. [Internet]. [cited 2023 Nov 21]. Available from: https://pubmed.ncbi.nlm.nih.gov/26599699/

9. Cornell M, Schomaker M, Garone DB, Giddy J, Hoffmann CJ, Lessells R, et al. Gender differences in survival among adult patients starting antiretroviral therapy in South Africa: a multicentre cohort study. PLoS Med. 2012;9(9):e1001304. Epub 2012 Sep 4. pmid:22973181; PMCID: PMC3433409. PLoS medicine [Internet]. 2012 [cited 2023 Nov 21];9(9). Available from: https://pubmed.ncbi.nlm.nih.gov/22973181/

10. Osler M, Cornell M, Ford N, Hilderbrand K, Goemaere E, Boulle A. Osler M, et al. Population-wide differentials in HIV service access and outcomes in the Western Cape for men as compared to women, South Africa: 2008 to 2018: a cohort analysis. J Int AIDS Soc. 2020 Jun;23 Suppl 2:e25530. PMCID: PMC7319137. J Intern AIDS Soc [Internet]. 2020 Jun [cited 2023 Aug 14];23(S2). Available from: https://onlinelibrary.wiley.com/doi/10.1002/jia2.25530 pmid:32589367

11. Davey DJ, Kehoe K, Serrao C, Prins M, Mkhize N, Hlophe K, et al. Same-day antiretroviral therapy is associated with increased loss to follow-up in South African public health facilities: a prospective cohort study of patients diagnosed with HIV. J Int AIDS Soc. 2020 Jun;23(6):e25529. pmid:32510186; PMCID: PMC7277782. Journal of the International AIDS Society [Internet]. 2020 Jun [cited 2023 Nov 21];23(6). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7277782/

12. Kranzer K, Lewis JJ, Ford N, Zeinecker J, Orrell C, Lawn SD, Bekker LG, Wood R. Treatment interruption in a primary care antiretroviral therapy program in South Africa: cohort analysis of trends and risk factors. J Acquir Immune Defic Syndr. 2010 Nov;55(3):e17–23. pmid:20827216; PMCID: PMC3024539. [Internet]. [cited 2023 Nov 21]. Available from: https://pubmed.ncbi.nlm.nih.gov/20827216/

13. Beckham SW, Beyrer C, Luckow P, Doherty M, Negussie EK, Baral SD. Marked sex differences in all-cause mortality on antiretroviral therapy in low- and middle-income countries: a systematic review and meta-analysis. J Int AIDS Soc. 2016 Nov 8;19(1):21106. pmid:27834182; PMCID: PMC5103676. Journal of the International AIDS Society [Internet]. 2016 Nov 8 [cited 2023 Nov 21];19(1). Available from: https://pubmed.ncbi.nlm.nih.gov/27834182/

14. Plazy M, Dray-Spira R, Orne-Gliemann J, Dabis F, Newell ML. Continuum in HIV care from entry to ART initiation in rural KwaZulu-Natal, South Africa. Trop Med Int Health. 2014 Jun;19(6):680–689. Epub 2014 Mar 21. pmid:24654990. [Internet]. [cited 2023 Nov 21]. Available from: https://pubmed.ncbi.nlm.nih.gov/24654990/

15. Rodger AJ, Cambiano V, Bruun T, Vernazza P, Collins S, van Lunzen J, et al. Sexual Activity Without Condoms and Risk of HIV Transmission in Serodifferent Couples When the HIV-Positive Partner Is Using Suppressive Antiretroviral Therapy. JAMA. 2016 Jul 12;316(2):171–81. pmid:27404185

16. Cohen MS, Chen YQ, McCauley M, Gamble T, Hosseinipour MC, Kumarasamy N, et al. Antiretroviral Therapy for the Prevention of HIV-1 Transmission. N Engl J Med. 2016 Sep 1;375(9):830–9. pmid:27424812

17. Bavinton BR, Pinto AN, Phanuphak N, Grinsztejn B, Prestage GP, Zablotska-Manos IB, et al. Viral suppression and HIV transmission in serodiscordant male couples: an international, prospective, observational, cohort study. Lancet HIV. 2018 Aug;5(8):e438–47. pmid:30025681

18. Rodger AJ, Cambiano V, Bruun T, Vernazza P, Collins S, Degen O, et al. Risk of HIV transmission through condomless sex in serodifferent gay couples with the HIV-positive partner taking suppressive antiretroviral therapy (PARTNER): final results of a multicentre, prospective, observational study. Lancet. 2019 Jun 15;393(10189):2428–38. pmid:31056293

19. Prevention-Access-Campaign-Consensus-Statement.pdf [Internet]. [cited 2023 Aug 15]. Available from: https://www.pwatoronto.org/wp-content/uploads/2017/10/2017-Prevention-Access-Campaign-Consensus-Statement.pdf

20. Eisinger RW, Dieffenbach CW, Fauci AS. Eisinger RW, Dieffenbach CW, Fauci AS. HIV Viral Load and Transmissibility of HIV Infection: Undetectable Equals Untransmittable. JAMA. 2019 Feb 5;321(5):451–452. pmid:30629090. JAMA. 2019 Feb 1;321(5):451–2.

21. Broyles LN, Luo R, Boeras D, Vojnov L. Broyles LN, Luo R, et al. The risk of sexual transmission of HIV in individuals with low-level HIV viraemia: a systematic review. Lancet. 2023 Aug 5;402(10400):464–471. Epub 2023 Jul 22. pmid:37490935; PMCID: PMC10415671. Lancet. 2023 Aug 5;402(10400):464–71.

22. Bekker LG, Smith P, Ntusi NAB. Bekker LG, Smith P, Ntusi NAB. HIV is sexually untransmittable when viral load is undetectable. Lancet. 2023 Aug 5;402(10400):428–429. Epub 2023 Jul 22. pmid:37490934. Lancet. 2023 Aug 5;402(10400):428–9.

23. NUDGE: Improving Decisions About Health, Wealth, and Happiness [Internet]. [cited 2023 Aug 15]. Available from: https://www.researchgate.net/publication/235413094_NUDGE_Improving_Decisions_About_Health_Wealth_and_Happiness

24. Millar MG, Millar K. Millar MG, Millar K. Negative affective consequences of thinking about disease detection behaviors. Health Psychol. 1995 Mar;14(2):141–6. pmid:7789349. Health Psychol. 1995 Mar;14(2):141–6.

25. Rice T. Rice T. The behavioral economics of health and health care. Annu Rev Public Health. 2013;34:431–47. Epub 2013 Jan 7. pmid:23297657. Annu Rev Public Health. 2013;34:431–47.

26. Arndt J, Goldenberg JL. Arndt J, Goldenberg JL. Where Health and Death Intersect: Insights from a Terror Management Health Model. Curr Dir Psychol Sci. 2017;26(2):126–131. Epub 2017 Apr 6. pmid:28924332; PMCID: PMC5600513. Curr Dir Psychol Sci. 2017;26(2):126–31.

27. Catalani C, Green E, Owiti P, Keny A, Diero L, Yeung A, et al. A clinical decision support system for integrating tuberculosis and HIV care in Kenya: a human-centered design approach. PLoS One. 2014 Aug 29;9(8):e103205. pmid:25170939; PMCID: PMC4149343. PLoS One. 2014;9(8):e103205.

28. Harte R, Glynn L, Rodríguez-Molinero A, Baker PM, Scharf T, Quinlan LR, et al. A Human-Centered Design Methodology to Enhance the Usability, Human Factors, and User Experience of Connected Health Systems: A Three-Phase Methodology. JMIR Hum Factors. 2017 Mar 16;4(1):e8. pmid:28302594; PMCID: PMC5374275. JMIR Hum Factors. 2017 Mar 16;4(1):e8.

29. Beres LK, Simbeza S, Holmes CB, Mwamba C, Mukamba N, Sharma A, et al. Human-Centered Design Lessons for Implementation Science: Improving the Implementation of a Patient-Centered Care Intervention. J Acquir Immune Defic Syndr. 2019 Dec;82 Suppl 3(3):S230–S243. Erratum in: J Acquir Immune Defic Syndr. 2020 May 1;84(1):e10. pmid:31764259; PMCID: PMC6880397. J Acquir Immune Defic Syndr. 2019 Dec;82 Suppl 3(3):S230–43.

30. Bazzano AN, Martin J, Hicks E, Faughnan M, Murphy L. Bazzano AN, et al. Human-centred design in global health: A scoping review of applications and contexts. PLoS One. 2017 Nov 1;12(11):e0186744. pmid:29091935; PMCID: PMC5665524. PLoS One. 2017;12(11):e0186744.

31. Matheson GO, Pacione C, Shultz RK, Klügl M. Matheson GO, Pacione C, Shultz RK, et al. Leveraging human-centered design in chronic disease prevention. Am J Prev Med. 2015 Apr;48(4):472–9. Epub 2015 Feb 18. pmid:25700655. Am J Prev Med. 2015 Apr;48(4):472–9.

32. Smith PJ, Joseph Davey DL, Schmucker L, Bruns C, Bekker LG, Medina-Marino A, et al. Participatory Prototyping of a Tailored Undetectable Equals Untransmittable Message to Increase HIV Testing Among Men in Western Cape, South Africa. AIDS Patient Care STDS. 2021 Nov;35(11):428–434. pmid:34739334. AIDS Patient Care STDS. 2021 Nov;35(11):428–34.

33. Prevention Access Campaign–The revolution in living and loving with HIV [Internet]. [cited 2023 Aug 15]. Available from: https://preventionaccess.org/

34. Calabrese SK, Mayer KH. Calabrese SK, Mayer KH. Providers should discuss U = U with all patients living with HIV. Lancet HIV. 2019 Apr;6(4):e211–e213. pmid:30772420. Lancet HIV. 2019 Apr;6(4):e211–3.

35. Siegel K, Meunier É. Siegel K, Meunier É. Awareness and Perceived Effectiveness of HIV Treatment as Prevention Among Men Who Have Sex with Men in New York City. AIDS Behav. 2019 Jul;23(7):1974–1983. pmid:30697639. AIDS Behav. 2019 Jul;23(7):1974–83.

36. Card KG, Armstrong HL, Lachowsky NJ, Cui Z, Sereda P, Carter MA, et al. Belief in Treatment as Prevention and Its Relationship to HIV Status and Behavioral Risk. J Acquir Immune Defic Syndr. 2018 Jan 1;77(1):8–16. pmid:28991882; PMCID: PMC5753790. J Acquir Immune Defic Syndr. 2018 Jan 1;77(1):8–16.

37. Carter A, Lachowsky N, Rich A, Forrest JI, Sereda P, Cui Z, et al. Gay and bisexual men’s awareness and knowledge of treatment as prevention: findings from the Momentum Health Study in Vancouver, Canada. J Int AIDS Soc. 2015 Aug 11;18(1):20039. pmid:26268817; PMCID: PMC4534712. J Int AIDS Soc. 2015;18(1):20039.

38. Rendina HJ, Cienfuegos-Szalay J, Talan A, Jones SS, Jimenez RH. Rendina HJ, et al. Growing Acceptability of Undetectable = Untransmittable but Widespread Misunderstanding of Transmission Risk: Findings From a Very Large Sample of Sexual Minority Men in the United States. J Acquir Immune Defic Syndr. 2020 Mar 1;83(3):215–222. pmid:31809309; PMCID: PMC7341443. J Acquir Immune Defic Syndr. 2020 Mar 1;83(3):215–22.

39. Paschen-Wolff MM, Campbell ANC, Tross S, Castro M, Berg H, Braunstein S, et al. HIV Treatment Knowledge in the Context of “Treatment as Prevention” (TasP). AIDS Behav. 2020 Oct;24(10):2984–2994. pmid:32246359; PMCID: PMC7483279. AIDS Behav. 2020 Oct;24(10):2984–94.

40. Ngure K, Ongolly F, Dolla A, Awour M, Mugwanya KK, Irungu E, et al. “I just believe there is a risk” understanding of undetectable equals untransmissible (U = U) among health providers and HIV-negative partners in serodiscordant relationships in Kenya. J Int AIDS Soc. 2020 Mar;23(3):e25466. pmid:32144888; PMCID: PMC7060133. Journal of the International AIDS Society. 2020;23(3):e25466.

41. Holt M, Lea T, Schmidt HM, Murphy D, Rosengarten M, Crawford D, et al. Increasing Belief in the Effectiveness of HIV Treatment as Prevention: Results of Repeated, National Surveys of Australian Gay and Bisexual Men, 2013–15. AIDS Behav. 2016 Jul;20(7):1564–71. pmid:26803613. AIDS and Behavior. 2016 Jul 1;20.

42. Making the invisible, visible: a cross-sectional study of late presentation to HIV/AIDS services among men who have sex with men from a large urban center of Brazil | BMC Public Health | Full Text [Internet]. [cited 2023 Aug 15]. Available from: https://bmcpublichealth.biomedcentral.com/articles/10.1186/1471-2458-14-1313

43. Ndyabakira A, Chamie G, Emperador D, Marson K, Kamya M, Havlir D, et al. Men’s Beliefs About the Likelihood of Serodiscordance in Couples with an HIV-Positive Partner: Survey Evidence from Rural Uganda. AIDS Behav. 2020 Mar;24(3):967–974. pmid:31073946. AIDS and Behavior. 2020 Mar 1;24.

44. Prati G, Zani B, Pietrantoni L, Scudiero D, Perone P, Cosmaro L, et al. PEP and TasP Awareness among Italian MSM, PLWHA, and High-Risk Heterosexuals and Demographic, Behavioral, and Social Correlates. PLoS One. 2016 Jun 13;11(6):e0157339. pmid:27294777; PMCID: PMC4905673. PLoS One. 2016;11(6):e0157339.

45. Couffignal C, Papot E, Etienne A, Legac S, Laouénan C, Beres D, et al. Treatment as prevention (TasP) and perceived sexual changes in behavior among HIV-positive persons: a French survey in infectious diseases departments in Paris. AIDS Care. 2020 Jul;32(7):811–817. Epub 2019 Aug 21. pmid:31431047. AIDS Care. 2020 Jul 2;32(7):811–7.

46. Newman CE, de Wit J, Persson A, Holt M, Slavin S, Kidd MR, et al. Understanding Concerns About Treatment-as-Prevention Among People with HIV who are not Using Antiretroviral Therapy. AIDS Behav. 2015 May;19(5):821–31. pmid:25432878. AIDS Behav. 2015 May;19(5):821–31.

47. Bavinton BR, Holt M, Grulich AE, Brown G, Zablotska IB, Prestage GP. Bavinton BR, et al. Willingness to Act upon Beliefs about “Treatment as Prevention” among Australian Gay and Bisexual Men. PLoS One. 2016 Jan 7;11(1):e0145847. pmid:26741143; PMCID: PMC4704706. PLOS ONE. 2016 Jan 7;11(1):e0145847.

48. Bor J, Fischer C, Modi M, Richman B, Kinker C, King R, et al. Changing Knowledge and Attitudes Towards HIV Treatment-as-Prevention and “Undetectable  =  Untransmittable”: A Systematic Review. AIDS Behav. 2021 Dec;25(12):4209–4224. Epub 2021 May 25. pmid:34036459; PMCID: PMC8147591. AIDS Behav. 2021;25(12):4209–24.

49. Kalichman SC, Cherry C, Kalichman MO, Amaral CM, White D, Pope H, et al. Integrated behavioral intervention to improve HIV/AIDS treatment adherence and reduce HIV transmission. Am J Public Health. 2011 Mar;101(3):531–8. Epub 2011 Jan 13. pmid:21233431; PMCID: PMC3036694. Am J Public Health. 2011 Mar;101(3):531–8.

50. Kalichman SC, Cherry C, Kalichman MO, Eaton LA, Kohler J, Montero C, et al. Mobile Health Intervention to Reduce HIV Transmission: A Randomized Trial of Behaviorally Enhanced HIV Treatment as Prevention (B-TasP). J Acquir Immune Defic Syndr. 2018 May 1;78(1):34–42. pmid:29406429; PMCID: PMC5889341. J Acquir Immune Defic Syndr. 2018 May 1;78(1):34–42.

51. Curran GM, Bauer M, Mittman B, Pyne JM, Stetler C. Curran GM, Bauer M, et al. Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact. Med Care. 2012 Mar;50(3):217–26. pmid:22310560; PMCID: PMC3731143. Med Care. 2012 Mar;50(3):217–26.

52. Curran GM, Landes SJ, McBain SA, Pyne JM, Smith JD, Fernandez ME, et al. Reflections on 10 years of effectiveness-implementation hybrid studies. Front Health Serv. 2022 Dec 8;2:1053496. pmid:36925811; PMCID: PMC10012680. Front Health Serv. 2022;2:1053496.

53. Johnson LF, Dorrington RE, Moolla H. Johnson LF, Dorrington RE, Moolla H. Progress towards the 2020 targets for HIV diagnosis and antiretroviral treatment in South Africa. South Afr J HIV Med. 2017 Jul 27;18(1):694. pmid:29568630; PMCID: PMC5843157. South Afr J HIV Med. 2017 Jul 27;18(1):694.

54. Johnson L, Dorrington R. Thembisa version 4.6: A model for evaluating the impact of HIV/AIDS in South Africa.

55. Medina-Marino A, Bezuidenhout D, Ngwepe P, Bezuidenhout C, Facente SN, Mabandla S, et al. Acceptability and feasibility of leveraging community-based HIV counselling and testing platforms for same-day oral PrEP initiation among adolescent girls and young women in Eastern Cape, South Africa. J Int AIDS Soc. 2022 Jul;25(7):e25968. pmid:35872602; PMCID: PMC9309460. J Int AIDS Soc. 2022 Jul;25(7):e25968.

56. van Schaik N, Kranzer K, Wood R, Bekker LG. van Schaik N, Kranzer K, et al. Earlier HIV diagnosis—are mobile services the answer? S Afr Med J. 2010 Oct 1;100(10):671–4. pmid:21080998. S Afr Med J. 2010 Oct 1;100(10):671–4.

57. Govindasamy D, Kranzer K, van Schaik N, Noubary F, Wood R, Walensky RP, et al. Linkage to HIV, TB and non-communicable disease care from a mobile testing unit in Cape Town, South Africa. PLoS One. 2013 Nov 13;8(11):e80017. pmid:24236170; PMCID: PMC3827432. PLoS One. 2013 Nov 13;8(11):e80017.

58. Medina-Marino A, Daniels J, Bezuidenhout D, Peters R, Farirai T, Slabbert J, et al. Outcomes from a multimodal, at-scale community-based HIV counselling and testing programme in twelve high HIV burden districts in South Africa. J Int AIDS Soc. 2021 Mar;24(3):e25678. pmid:33709542; PMCID: PMC7952633. J Int AIDS Soc. 2021 Mar;24(3):e25678.

59. Medina-Marino A, Bezuidenhout D, Hosek S, Barnabas RV, Atujuna M, Bezuidenhout C, et al. The Community PrEP Study: a randomized control trial leveraging community-based platforms to improve access and adherence to pre-exposure prophylaxis to prevent HIV among adolescent girls and young women in South Africa-study protocol. Trials. 2021 Jul 26;22(1):489. pmid:34311754; PMCID: PMC8314507. Trials. 2021 Jul 26;22(1):489.

60. Smith PJ, Daniels J, Bekker LG, Medina-Marino A. Smith PJ, Daniels J, Bekker LG, et al. What motivated men to start PrEP? A cross-section of men starting PrEP in Buffalo city municipality, South Africa. BMC Public Health. 2023 Mar 2;23(1):418. pmid:36864381; PMCID: PMC9979577. BMC Public Health. 2023 Mar 2;23:418.

61. Smith P, Buttenheim A, Schmucker L, Bekker LG, Thirumurthy H, Davey DLJ. Smith P, et al. Undetectable  =  Untransmittable (U  =  U) Messaging Increases Uptake of HIV Testing Among Men: Results from a Pilot Cluster Randomized Trial. AIDS Behav. 2021 Oct;25(10):3128–3136. Epub 2021 May 31. pmid:34057659; PMCID: PMC8165342. AIDS Behav. 2021;25(10):3128–36.

62. South African National Department of Health. HIV Testing Services: Policy 2016 [Internet]. Pretoria, South Africa; 2016 Jul [cited 2020 Dec 29]. Available from: https://sahivsoc.org/Files/HTS%20Policy%2028%20July%20final%20copy.pdf

63. Hemming K, Kasza J, Hooper R, Forbes A, Taljaard M. Hemming K, Kasza J, et al. A tutorial on sample size calculation for multiple-period cluster randomized parallel, cross-over and stepped-wedge trials using the Shiny CRT Calculator. Int J Epidemiol. 2020 Jun 1;49(3):979–995. pmid:32087011; PMCID: PMC7394950. Int J Epidemiol. 2020 Jun 1;49(3):979–95.

64. Stein A, Ramaseshan B. Towards the identification of customer experience touch point elements. Journal of Retailing and Consumer Services. 2016 May 1;30:8–19.

65. Bauermeister JA, Golinkoff JM, Muessig KE, Horvath KJ, Hightow-Weidman LB. Bauermeister JA, Golinkoff JM et al. Addressing engagement in technology-based behavioural HIV interventions through paradata metrics. Curr Opin HIV AIDS. 2017 Sep;12(5):442–446. pmid:28617711; PMCID: PMC5637536. Curr Opin HIV AIDS. 2017 Sep;12(5):442–6.

66. Lynch KG, Cary M, Gallop R, Ten Have TR. Lynch KG, Cary M, et al. Causal Mediation Analyses for Randomized Trials. Health Serv Outcomes Res Methodol. 2008;8(2):57–76. pmid:19484136; PMCID: PMC2688317. Health Serv Outcomes Res Methodol. 2008;8(2):57–76.

67. National Consolidated Guidelines 30062020 signed PRINT v7.pdf [Internet]. [cited 2023 Aug 15]. Available from: https://knowledgehub.health.gov.za/system/files/elibdownloads/2020-07/National%20Consolidated%20Guidelines%2030062020%20signed%20PRINT%20v7.pdf

68. National Department of Health. Adherence Guidelines for HIV, TB and NCDs [Internet]. Republic of South Africa National Department of Health; 2016 [cited 2021 Apr 17]. Available from: https://www.nacosa.org.za/wp-content/uploads/2018/05/SOP-Adherence-counselling-A5-booklet-19-03-2017.pdf

69. Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Damschroder LJ, et al. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009 Aug 7;4:50. pmid:19664226; PMCID: PMC2736161. Implement Sci. 2009 Aug 7;4:50.

70. King DK, Shoup JA, Raebel MA, Anderson CB, Wagner NM, Ritzwoller DP, et al. Planning for Implementation Success Using RE-AIM and CFIR Frameworks: A Qualitative Study. Front Public Health. 2020 Mar 3;8:59. pmid:32195217; PMCID: PMC7063029. Front Public Health. 2020;8:59.

71. Glasgow RE, Estabrooks PE. Glasgow RE, Estabrooks PE. Pragmatic Applications of RE-AIM for Health Care Initiatives in Community and Clinical Settings. Prev Chronic Dis. 2018 Jan 4;15:E02. pmid:29300695; PMCID: PMC5757385. Prev Chronic Dis. 2018 Jan 4;15:E02.

72. Glasgow RE, Harden SM, Gaglio B, Rabin B, Smith ML, Porter GC, et al. RE-AIM Planning and Evaluation Framework: Adapting to New Science and Practice With a 20-Year Review. Front Public Health. 2019 Mar 29;7:64. pmid:30984733; PMCID: PMC6450067. Front Public Health. 2019;7:64.

73. Damschroder LJ, Reardon CM, Widerquist MAO, Lowery J. Damschroder LJ Reardon CM, Widerquist MAO, et al. The updated Consolidated Framework for Implementation Research based on user feedback. Implement Sci. 2022 Oct 29;17(1):75. pmid:36309746; PMCID: PMC9617234. Implementation Science. 2022 Oct 29;17(1):75.

74. Beidas RS, Buttenheim AM, Mandell DS. Beidas RS, Buttenheim AM, Mandell DS. Transforming Mental Health Care Delivery Through Implementation Science and Behavioral Economics. JAMA Psychiatry. 2021 Sep 1;78(9):941–942. pmid:34076686; PMCID: PMC8744069. JAMA Psychiatry. 2021 Sep 1;78(9):941–2.

75. Mandimika C, Bokolo S, ChettyMakkan C, Long L, Mistri P, Schmucker L, et al. The NUDGE Handbook: A practical guide to behavioural design based on the NUDGE framework. Version 2. June 2023. Indlela Behavioural Insights Unit. Available at https://indlela.org/nudge-handbookTimelines.

76. Swain J. A Hybrid Approach to Thematic Analysis in Qualitative Research: Using a Practical Example. 2018.

77. Brewer JD, Shinnick J, Román K, Santos MP, Paz-Soldan VA, Buttenheim AM. Brewer JD, et al Behavioral Insights Into Micronutrient Powder Use for Childhood Anemia in Arequipa, Peru. Glob Health Sci Pract. 2020 Dec 23;8(4):721–731. pmid:33361238; PMCID: PMC7784068. Glob Health Sci Pract. 2020 Dec 23;8(4):721–31.

78. Stewart RE, Beidas RS, Last BS, Hoskins K, Byeon YV, Williams NJ, et al. Applying NUDGE to Inform Design of EBP Implementation Strategies in Community Mental Health Settings. Adm Policy Ment Health. 2021 Jan;48(1):131–142. pmid:32430590; PMCID: PMC8092115. Adm Policy Ment Health. 2021 Jan;48(1):131–42.

79. NHREC-DoH-2015-Ethics-in-Health-Research-Guidelines-1.pdf [Internet]. [cited 2023 Nov 21]. Available from: https://www.health.gov.za/wp-content/uploads/2022/05/NHREC-DoH-2015-Ethics-in-Health-Research-Guidelines-1.pdf

80. Matchboxology [Internet]. [cited 2023 Aug 15]. Available from: https://matchboxology.com/.