Implementation and Effects of Nishauri on HIV Treatment Outcomes Among Men

Introduction Background Globally, men are 27% less likely than women to seek HIV testing and often present to care at later stages of illness. In sub-Saharan Africa, men's participation in HIV care is further constrained by cultural expectations that prioritize economic provision and emotional suppression. Kenya continues to face significant challenges in the fight against HIV/AIDS, with an estimated 1.3 million people living with HIV. Despite advances in antiretroviral therapy (ART) and HIV care services, men experience persistent barriers to accessing and engaging with care. Masculine norms around strength, stoicism, and self-reliance often discourage men from seeking health services, including HIV testing and treatment, contributing to lower engagement and adherence among men living with HIV. The lack of male-targeted interventions compounds these challenges, making it critical to develop and evaluate strategies that effectively engage men in care to achieve the UNAIDS 95-95-95 targets by 2030.

Mobile health (mHealth) interventions have emerged as promising tools for improving healthcare delivery and patient engagement, particularly in resource-constrained settings. By leveraging mobile devices to deliver health-related information and services, mHealth strategies help bridge critical gaps in access, communication, and continuity of care. Evidence from low- and middle-income countries (LMICs) suggests that mHealth interventions can enhance antiretroviral therapy (ART) adherence, retention in care, and health literacy among people living with HIV.

Globally, tools such as SMS reminders and mobile applications have demonstrated significant potential to improve clinical outcomes, including ART adherence, retention, and viral suppression. In sub-Saharan Africa, where healthcare access is often limited, mHealth approaches have been effective in reducing loss to follow-up and improving engagement in care. For instance, studies in Uganda and South Africa show that mobile reminders and SMS-based counseling significantly improve adherence and retention among HIV-positive individuals. These tools facilitate behavior change through personalized messaging, medication reminders, and educational content. Critically, gender-sensitive and culturally adapted mHealth interventions are more effective among men, as they address stigma and align health-seeking behaviors with socially accepted masculine norms. However, there remains limited evidence on the implementation outcomes, service outcomes, and long-term sustainability of mHealth interventions specifically tailored for men in HIV care in Kenya.

While mHealth technologies have shown promise in improving HIV care outcomes, their adoption and sustained use face significant challenges. These include digital literacy gaps, inconsistent device ownership, limited infrastructure, and concerns around data privacy and confidentiality. In Kenya, mobile phone ownership and digital access vary by gender, education level, and socioeconomic status, with individuals who own smartphones and have higher education levels being more likely to engage with mHealth services. Moreover, the integration of mHealth tools into routine HIV care remains limited, particularly in rural, high-prevalence settings like Homa Bay County. Although urban and educated populations may benefit more readily from these tools, long-term adoption, utilization, and sustainability, especially among men living with HIV, are still poorly understood. These structural and behavioral challenges underscore the need to examine how mHealth can be more equitably implemented across diverse populations.

Despite their potential, many mHealth interventions are not adequately aligned with the gendered and socio-cultural realities that shape care-seeking behaviors, particularly among men. Programs often lack meaningful involvement of healthcare providers and fail to tailor their content or delivery to address male-specific barriers or local norms. Discreet and convenient by design, mHealth tools may still fall short if they do not resonate with prevailing masculine identities or reframe care-seeking in ways that affirm strength and responsibility. In high-burden regions like Homa Bay County, where HIV prevalence stands at 16.2%, men often disengage from care due to stigma and perceived threats to masculinity. Addressing these critical gaps in implementation, cultural alignment, and gender responsiveness is essential for developing effective, sustainable mHealth solutions that can improve HIV treatment outcomes for men.

About Nishauri mHealth Intervention The Nishauri mHealth intervention is a client-centered digital platform developed by Palladium, in collaboration with Kenya's Ministry of Health and funded by PEPFAR through the CDC, to enhance HIV care and treatment outcomes. Designed for people living with HIV in Kenya, Nishauri supports key aspects of HIV care management, including appointment scheduling, ART referrals, and ongoing patient engagement. Its core functionalities include automated appointment and medication adherence reminders, tailored health education messages, two-way communication between patients and healthcare providers, and behavior-change communication strategies to support retention in care. HIV patients using Nishauri can access their treatment engagement information and schedule or reschedule appointments through the application.

Nishauri is interoperable with national health information systems such as the Kenya Electronic Medical Records (KenyaEMR) and the Ushauri platform, allowing for real-time data exchange and continuity of care during patient transfers. While technologically aligned with these systems, minor discrepancies in language semantics have led to some inconsistencies in data entry identifiers. Despite its national scale-up and integration into comprehensive care clinics, the uptake and utilization of Nishauri remain low and highly variable across facilities, providers, and patient populations. This variability hints at challenges with its implementation and effectiveness among men living with HIV - a population that faces unique sociocultural barriers to care. Existing research often overlooks the role of gender norms and contextual factors in influencing men's engagement with digital health interventions. Addressing this gap is essential for designing scalable, culturally relevant mHealth solutions that promote sustained engagement and improved clinical outcomes among men.

This Study We will use a mixed-methods- explanatory sequential, cluster randomized stepped wedge design to evaluate both implementation and preliminary effects of Nishauri mHealth intervention among men living with HIV in Homa Bay County. We will leverage a partnership with the Palladium Group to access backend usage data from the Nishauri app, providing detailed insights into how different app functions are used in real-world settings. We will also explore how masculine norms influence men's engagement with the intervention.

Methods Study Design This study will use an explanatory sequential mixed methods design, incorporating a cluster randomized stepped-wedge approach across four health facilities in Homa Bay County. Quantitative data will be collected through structured surveys, chart reviews, and app analytics to assess implementation outcomes (e.g., acceptability, uptake, retention, viral load suppression) at baseline and six months post-intervention. Each facility will serve as its own control prior to intervention rollout, which will occur sequentially in a randomized order over a six-month period. This mixed methods design will enable both within- and between-facility comparisons, offering a nuanced understanding of how implementation processes and gendered experiences shape the intervention's effectiveness.

Study Setting The study will be conducted in 4 sub-County HIV Comprehensive Care Clinics (CCC) in Homa Bay County, Kenya- Mbita, Ogongo, Ndhiwa and Pala. Homa Bay County was chosen for its highest HIV prevalence, 16.2% \[4\] in Kenya making it suitable to assess the implementation process and outcomes of an mHealth intervention for enhancing HIV care. The county covers an area of about 3,154 square kilometers \[26,27\]. As of the 2019 Kenya National Census, it had an estimated population of approximately 1.1 million people \[27\]. There are approximately 160 health facilities providing HIV comprehensive care services across the county. ART uptake is at 96% while VLS prevalence is at 83.8% among people living with HIV, with significant disparities between men and women \[4,24,28\].

Participants and Recruitment The primary study population will comprise men living with HIV who initiated care and treatment in 2016 or later, following the updated national HIV treatment guidelines. Eligible participants must be between 18 and 55 years of age, have initiated HIV care from 2016 onwards, own a smartphone or tablet, and be able and willing to provide written informed consent. Men with severe comorbidities or chronic co-infections (e.g., cancer or hypertension) that may affect adoption or use of mHealth interventions will be excluded.

A small sample of healthcare providers (e.g., nurses, adherence counselors, peer educators) and Nishauri app developers will also participate in focus group discussions (FGDs).

The CCCs will be randomized in sequence using a computer-generated order for phased implementation of the intervention, transitioning from standard care to the mHealth intervention arm. Participant recruitment in each CCC will proceed according to probability proportional to size sampling until the required sample size of 347 participants is reached (316 calculated, with an added 10% to account for attrition). For the qualitative component, 5-6 FGDs will be conducted: 2-3 with men living with HIV, 2 with healthcare providers, and 1 with app developers. FGD sampling will be stratified by factors such as age, ART adherence, missed clinic visits, and role within the health system, and data collection will continue until thematic saturation is achieved.

Recruitment will occur during routine clinic visits. Trained study staff or peer educators will introduce the study to clients, provide study information, and collect contact information from those expressing interest. Screening for eligibility will take place in private, either in-clinic or at a location convenient and confidential for the participant. Those eligible will then undergo informed consent and complete a baseline survey, which will be used as a point of comparison for future evaluation of the intervention's effects.

To preserve the integrity of the data, most FGD participants will be different from those in the quantitative survey arm to reduce contamination, social desirability bias, and respondent fatigue. However, a limited number of individuals who participated in the quantitative arm may be included in FGDs to help explain emerging patterns in the data, as this study employs an explanatory mixed methods approach. Healthcare providers and app developers will also be purposively sampled to ensure representation of different implementation perspectives across the system.

Retention strategy Participants will be reminded a week to their scheduled visit appointment by a text message. For each missed visit, study staff will attempt to reach the participant through a phone call or text message to reschedule the visit as soon as possible. In an event this doesn't work, the study staff will arrange to visit and meet the participant face-to-face and conduct the follow up survey. Study staff will also call those who relocate out of the study area to arrange for data collection as soon as possible in an appropriate, safe and private location.

Baseline and 6-month follow up surveys Quantitative data collection and storage Quantitative data will be collected at two main time points- baseline and six-month follow