Background: In many low- and middle-income countries (LMICs), heart disease and stroke are the leading causes of death as cardiovascular risk factors such as diabetes and hypertension rapidly increase. The Cambodian nongovernmental organization, MoPoTsyo, trains local residents with diabetes to be peer educators (PEs) to deliver chronic disease self-management training and medications to 14,000 people with hypertension and/or diabetes in Cambodia. We collaborated with MoPoTsyo to develop a mobile-based messaging intervention (mobile health; mHealth) to link MoPoTsyo’s database, PEs, pharmacies, clinics, and people living with diabetes and/or hypertension to improve adherence to evidence-based treatment guidelines. Objective: This study aimed to understand the facilitators and barriers to chronic disease management and the acceptability, appropriateness, and feasibility of mHealth to support chronic disease management and strengthen community-clinical linkages to existing services. Methods: We conducted an exploratory qualitative study using semistructured interviews and focus groups with PEs and people living with diabetes and/or hypertension. Interviews were recorded and conducted in Khmer script, transcribed and translated into the English language, and uploaded into Atlas.ti for analysis. We used a thematic analysis to identify key facilitators and barriers to disease management and opportunities for mHealth content and format. The information-motivation-behavioral model was used to guide data collection, analysis, and message development. Results: We conducted six focus groups (N=59) and 11 interviews in one urban municipality and five rural operating districts from three provinces in October 2016. PE network participants desired mHealth to address barriers to chronic disease management through reminders about medications, laboratory tests and doctor’s consultations, education on how to incorporate self-management into their daily lives, and support for obstacles to disease management. Participants preferred mobile-based voice messages to arrive at dinnertime for improved phone access and family support. They desired voice messages over texts to communicate trust and increase accessibility for persons with limited literacy, vision, and smartphone access. PEs shared similar views and perceived mHealth as acceptable and feasible for supporting their work. We developed 34 educational, supportive, and reminder mHealth messages based on these findings. Conclusions: These mHealth messages are currently being tested in a cluster randomized controlled trial (#1R21TW010160) to improve diabetes and hypertension control in Cambodia. This study has implications for practice and policies in Cambodia and other LMICs and low-resource US settings that are working to engage PEs and build community-clinical linkages to facilitate chronic disease management.

Background: The burden of non-communicable diseases (NCDs) is increasing in low- and middle-income countries (LMICs) where NCDs cause 4:5 deaths, disproportionately affect poorer populations, and carry a large economic burden. Digital interventions can improve NCD management for these hard-to-reach populations with inadequate health systems and high cell-phone coverage; however, there is limited research on whether digital health is reaching this potential. We conducted a process evaluation to understand challenges and successes from a digital health intervention trial to support Cambodians living with NCDs in a peer educator (PE) program. Methods: MoPoTsyo, a Cambodian non-governmental organization (NGO), trains people living with diabetes and/or hypertension as PEs to provide self-management education, support, and healthcare linkages for better care management among underserved populations. We partnered with MoPoTsyo and InSTEDD in 2016–2018 to test tailored and targeted mHealth mobile voice messages and eHealth tablets to facilitate NCD management and clinical-community linkages. This cluster randomized controlled trial (RCT) engaged 3,948 people and 75 PEs across rural and urban areas. Our mixed methods process evaluation was guided by RE-AIM to understand impact and real-world implications of digital health. Data included patient (20) and PE interviews (6), meeting notes, and administrative datasets. We triangulated and analyzed data using thematic analysis, and descriptive and complier average causal effects statistics (CACE). Results: Reach: intervention participants were more urban (66% vs. 44%), had more PE visits (39 vs. 29), and lower uncontrolled hypertension [12% and 7% vs. 23% and 16% uncontrolled systolic blood pressure (SBP) and diastolic blood pressure (DBP)]. Adoption: patients were sent mean [standard deviation (SD)] 30 [14] and received 14 [8] messages; 40% received no messages due to frequent phone number changes. Effectiveness: CACE found clinically but not statistically significant improvements in blood pressure and sugar for mHealth participants who received at least one message vs. no messages. Implementation: main barriers were limited cellular access and that mHealth/eHealth could not solve structural barriers to NCD control faced by people in poverty. Maintenance: had the intervention been universally effective, it could be paid for from additional revolving drug fund revenue, new agreements with mobile networks, or the government. Conclusions: Evidence for digital health to improve NCD outcomes in LMICs are limited. This study suggests digital health alone is insufficient in countries with low resource health systems and that high cell phone coverage did not translate to access. Adding digital health to an NCD peer network may not significantly benefit an already effective program; mHealth may be better for hard-to-reach populations not connected to other supports. As long as mHealth remains an individual-level intervention, it will not address social determinants of health that drive outcomes. Future digital health research and practice to improve NCD management in LMICs requires engaging government, NGOs, and technology providers to work together to address barriers.

Background: Artificial intelligence has provided new opportunities for human interactions with technology for the practice of medicine. Among the recent artificial intelligence innovations, personal voice assistants have been broadly adopted. This highlights their potential for health care–related applications such as behavioral counseling to promote healthy lifestyle habits and emotional well-being. However, the use of voice-based applications for behavioral therapy has not been previously evaluated. Objective: This study aimed to conduct a formative user evaluation of Lumen, a virtual voice-based coach developed as an Alexa skill that delivers evidence-based, problem-solving treatment for patients with mild to moderate depression and/or anxiety. Methods: A total of 26 participants completed 2 therapy sessions—an introductory (session 1) and a problem-solving (session 2)—with Lumen. Following each session with Lumen, participants completed user experience, task-related workload, and work alliance surveys. They also participated in semistructured interviews addressing the benefits, challenges and barriers to Lumen use, and design recommendations. We evaluated the differences in user experience, task load, and work alliance between sessions using 2-tailed paired t tests. Interview transcripts were coded using an inductive thematic analysis to characterize the participants’ perspectives regarding Lumen use. Results: Participants found Lumen to provide high pragmatic usability and favorable user experience, with marginal task load during interactions for both Lumen sessions. However, participants experienced a higher temporal workload during the problem-solving session, suggesting a feeling of being rushed during their communicative interactions. On the basis of the qualitative analysis, the following themes were identified: Lumen’s on-demand accessibility and the delivery of a complex problem-solving treatment task with a simplistic structure for achieving therapy goals; themes related to Lumen improvements included streamlining and improved personalization of conversations, slower pacing of conversations, and providing additional context during therapy sessions. Conclusions: On the basis of an in-depth formative evaluation, we found that Lumen supported the ability to conduct cognitively plausible interactions for the delivery of behavioral therapy. Several design suggestions identified from the study including reducing temporal and cognitive load during conversational interactions, developing more natural conversations, and expanding privacy and security features were incorporated in the revised version of Lumen. Although further research is needed, the promising findings from this study highlight the potential for using Lumen to deliver personalized and accessible mental health care, filling a gap in traditional mental health services.

We partnered with 3 social service organizations to identify hard-to-reach populations, barriers to reach, and strategies for improving recruitment and retention for Program to Encourage Active, Rewarding Lives (PEARLS), a home-based depression-care management program for elders. We conducted semistructured interviews with staff and former PEARLS participants. All interviews were transcribed verbatim and thematically analyzed. Veterans, African Americans, Filipino men, other immigrants and English-language learners, old-older adults, rural communities, and people with limited education were identified as hard to reach. The themes of trust, cultural appropriateness, meet them where they are, and framing and reframing, cut across barriers to participation in PEARLS and approaches for overcoming these barriers. Research findings will be used to inform technical assistance activities with PEARLS providers, changes to PEARLS program and training materials, and future PEARLS research activities.