Is Digital Healthcare Better Than None? The Digital Health Technology Dilemma in Low-Income Countries

Digital health technologies are crucial for achieving universal health coverage (UHC), especially in low- and middle-income countries (LMICs) with limited digital infrastructure. This study aimed to assess digital health capacity across multiple LMICs and evaluate its association with evidence-based practice (EBP) and patient-centered care (PCC). We analyzed Service Provision Assessment data collected over the past decade, spanning 5311 facilities and 20,880 pediatric visits across eight LMICs. Digital health capacity was measured using the WHO Classification of Digital Health Interventions (CDHI) across five domains: digital infrastructure, client engagement, healthcare providers, data services, and health system managers. EBP was assessed via ten binary items, while PCC was derived from eleven exit interview items using exploratory factor analysis. Multilevel regression models explored relationships between digital health capacity and both EBP and PCC. Overall digital health capacity was low (mean = 0.35), with notably low scores for digital infrastructure (0.02), healthcare providers (0.21), and health system managers (0.06). Digital health capacity was significantly associated with improved EBP (Coef. = 0.146, p < 0.001), particularly through digital infrastructure (Coef. = 0.183, p = 0.029), client engagement (Coef. = 0.205, p < 0.001), and provider capacity (Coef. = 0.142, p < 0.001). No significant effect emerged for PCC (Coef.=-0.013, p = 0.531). The level of digital health technology in LMICs is generally insufficient, particularly in terms of digital infrastructure, healthcare provider training and health system managers. Although the implementation of digital health technologies has the potential to improve the EBP, its effect on enhancing PCC is relatively limited.

BackgroundAn estimated 1 in 5 adolescents experience a mental health disorder each year; yet because of barriers to accessing and seeking care, most remain undiagnosed and untreated. Furthermore, the early emergence of psychopathology contributes to a lifelong course of challenges across a broad set of functional domains, so addressing this early in the life course is essential. With increasing digital connectivity, including in low- and middle-income countries, digital health technologies are considered promising for addressing mental health among adolescents and young people. In recent years, a growing number of digital health interventions, including more than 2 million web-based mental health apps, have been developed to address a range of mental health issues.ObjectiveThis review aims to synthesize the current evidence on digital health interventions targeting adolescents and young people with mental health conditions, aged between 10-24 years, with a focus on effectiveness, cost-effectiveness, and generalizability to low-resource settings (eg, low- and middle-income countries).MethodsWe searched MEDLINE, PubMed, PsycINFO, and Cochrane databases between January 2010 and June 2020 for systematic reviews and meta-analyses on digital mental health interventions targeting adolescents and young people aged between 10-24 years. Two authors independently screened the studies, extracted data, and assessed the quality of the reviews.ResultsIn this systematic overview, we included 18 systematic reviews and meta-analyses. We found evidence on the effectiveness of computerized cognitive behavioral therapy on anxiety and depression, whereas the effectiveness of other digital mental health interventions remains inconclusive. Interventions with an in-person element with a professional, peer, or parent were associated with greater effectiveness, adherence, and lower dropout than fully automatized or self-administered interventions. Despite the proposed utility of digital interventions for increasing accessibility of treatment across settings, no study has reported sample-specific metrics of social context (eg, socioeconomic background) or focused on low-resource settings.ConclusionsAlthough digital interventions for mental health can be effective for both supplementing and supplanting traditional mental health treatment, only a small proportion of existing digital platforms are evidence based. Furthermore, their cost-effectiveness and effectiveness, including in low- and middle-income countries, have been understudied. Widespread adoption and scale-up of digital mental health interventions, especially in settings with limited resources for health, will require more rigorous and consistent demonstrations of effectiveness and cost-effectiveness vis-à-vis the type of service provided, target population, and the current standard of care.

Has traditional medicine had its day? The need to redefine academic medicine

To paraphrase a classic, evaluating digital technologies in health is a bit like eating spinach - no one is against it in principle because it is good for you. However, no one would do it unless being asked to. In recent years, the sheer number of digital health technologies that potentially fulfil public health purposes has increased tremendously. The basis for evaluating such tools for public health purposes however has not met this pace, and in particular frameworks for the systematic development and evaluation of digital technologies in public health are rare. Existing frameworks for digital technologies focus on clinical aspects of digital health applications (e.g., NICE Evidence standards framework for digital health technologies), thus lacking both a population and prevention focus. Generic frameworks such as the Health Technology Assessment (HTA) methodology do not contain items specific to digital technologies and public health purposes. Here, we describe the process of developing a framework specific for the development and evaluation of digital public health technologies based on the core HTA model. We conduct a scoping review of frameworks for the development and the evaluation of technologies in public health and digital health, following PRISMA-SCR guidelines. The identified frameworks are then mapped onto the core HTA model to develop additional items specific for the development and the evaluation of digital technologies in public health. These additional items can be used to integrate the development and evaluation of digital technologies for public health purposes within the wider HTA context, making this process both transferable and scalable.

Digital health technologies can potentially reduce health disparities in cancer care. However, the benefits of digital health technology depend partly on users' digital health literacy, that is, "capabilities and resources required for individuals to use and benefit from digital health resources," which combines health and digital literacy. We examined issues for digital health technology implementation in cancer care regarding digital health literacy, via stakeholder consultation. Consumers, health care professionals, researchers, developers, nongovernment and government/policy stakeholders (N=51) participated in focus groups/interviews discussing barriers, enablers, needs and opportunities for digital health implementation in cancer care. Researchers applied framework analysis to identify themes of digital health literacy in the context of disparity and inclusion. Limited digital and traditional health literacy were identified as barriers to digital technology engagement, with a range of difficulties identified for older, younger and socio-economically or geographically disadvantaged groups. Digital health technology was a potential enabler of health care access and literacy, affording opportunities to increase reach and engagement. Education combined with targeted design and implementation were identified means of addressing health and digital literacy to effectively implement digital health in cancer care. Implementing digital health in cancer care must address the variability of digital health literacy in recipients, including groups living with disadvantage and older and younger people, in order to be effective. SO WHAT?: If cancer outcome disparity is to be reduced via digital health technologies, they must be implemented strategically to address digital health literacy needs. Health policy should reflect this approach.

Digital Health Solutions During COVID-19 in Low- and Middle-Income Countries: A Systematic Review of Current Evidence

BackgroundArtificial intelligence (AI) and digital health technological innovations from startup companies used in clinical practice can yield better health outcomes, reduce health care costs, and improve patients' experience. However, the integration, translation, and adoption of these technologies into clinical practice are plagued with many challenges and are lagging. Furthermore, explanations of the impediments to clinical translation are largely unknown and have not been systematically studied from the perspective of AI and digital health care startup founders and executives.ObjectiveThe aim of this paper is to describe the barriers to integrating early-stage technologies in clinical practice and health care systems from the perspectives of digital health and health care AI founders and executives.MethodsA stakeholder focus group workshop was conducted with a sample of 10 early-stage digital health and health care AI founders and executives. Digital health, health care AI, digital health–focused venture capitalists, and physician executives were represented. Using an inductive thematic analysis approach, transcripts were organized, queried, and analyzed for thematic convergence.ResultsWe identified the following four categories of barriers in the integration of early-stage digital health innovations into clinical practice and health care systems: (1) lack of knowledge of health system technology procurement protocols and best practices, (2) demanding regulatory and validation requirements, (3) challenges within the health system technology procurement process, and (4) disadvantages of early-stage digital health companies compared to large technology conglomerates. Recommendations from the study participants were also synthesized to create a road map to mitigate the barriers to integrating early-stage or novel digital health technologies in clinical practice.ConclusionsEarly-stage digital health and health care AI entrepreneurs identified numerous barriers to integrating digital health solutions into clinical practice. Mitigation initiatives should create opportunities for early-stage digital health technology companies and health care providers to interact, develop relationships, and use evidence-based research and best practices during health care technology procurement and evaluation processes.

Barriers and facilitators to digital health collaboration between academia and industry: a cross-cultural analysis

Designing digital health applications for climate change mitigation and adaptation.

Digital health technologies and health-care privatisation

Non- Communicable Diseases (NCDs) such as hypertension and diabetes have continued to impose a significant health burden in Low and Middle-Income Countries (LMICs), where treatment compliance remains critically low. Systemic barriers including limited healthcare infrastructure, inadequate follow-up mechanisms, and sociocultural factors have impeded patients’ ability to adhere to long-term treatment regimens. While mobile health (mHealth) and digital interventions have emerged as potential tools to enhance medication adherence, their effectiveness in LMICs remains uneven and context-dependent. This study aimed to assess the role of health system factors in promoting treatment compliance among patients with NCDs through mobile platforms in LMICs, with a particular focus on Kenya. A qualitative literature review was conducted using purposive sampling of 20 peer-reviewed articles published between 2020 and 2025. The studies were selected based on their focus on health system factors, treatment compliance, and digital or mobile health interventions in LMICs. Data were extracted and analyzed thematically to identify patterns across health system components, digital health strategies, and patient adherence outcomes. The review revealed that systemic barriers including shortages of healthcare personnel, poor digital infrastructure, low health literacy, and financial constraints consistently undermined treatment compliance in LMICs. However, digital tools such as SMS reminders, mHealth apps, and teleconsultations demonstrated improved patient adherence, especially when culturally adapted and integrated into community health frameworks. In Kenya and similar settings, mobile interventions linked with community health workers showed greater success in sustaining long-term engagement. Nonetheless, disparities persisted in digital access, gender equity, and scalability due to infrastructural limitations and weak policy integration. Mobile and digital health platforms offered a promising avenue for improving treatment compliance among NCD patients in LMICs. Their effectiveness was significantly influenced by the readiness of local health systems, sociocultural adaptability, and the extent of integration with human health resources. Despite their potential, many digital interventions remained fragmented, donor-driven, and unsustainable without supportive infrastructure and policy frameworks. To optimize the impact of mobile health (mHealth) interventions, policymakers should invest in digital infrastructure, integrate mHealth into national health systems, and prioritize the training and deployment of community health workers. Future research should include longitudinal and experimental designs to assess long-term outcomes and cost-effectiveness, and emphasize inclusive, culturally tailored approaches to improve equitable access to care.

BackgroundMaternal and child health (MCH) is a global health concern, especially impacting low- and middle-income countries (LMIC). Digital health technologies are creating opportunities to address the social determinants of MCH by facilitating access to information and providing other forms of support throughout the maternity journey. Previous reviews in different disciplines have synthesized digital health intervention outcomes in LMIC. However, contributions in this space are scattered across publications in different disciplines and lack coherence in what digital MCH means across fields.ObjectiveThis cross-disciplinary scoping review synthesized the existing published literature in 3 major disciplines on the use of digital health interventions for MCH in LMIC, with a particular focus on sub-Saharan Africa.MethodsWe conducted a scoping review using the 6-stage framework by Arksey and O’Malley across 3 disciplines, including public health, social sciences applied to health, and human-computer interaction research in health care. We searched the following databases: Scopus, PubMed, Google Scholar, ACM Digital Library, IEEE Xplore, Web of Science, and PLOS. A stakeholder consultation was undertaken to inform and validate the review.ResultsDuring the search, 284 peer-reviewed articles were identified. After removing 41 duplicates, 141 articles met our inclusion criteria: 34 from social sciences applied to health, 58 from public health, and 49 from human-computer interaction research in health care. These articles were then tagged (labeled) by 3 researchers using a custom data extraction framework to obtain the findings. First, the scope of digital MCH was found to target health education (eg, breastfeeding and child nutrition), care and follow-up of health service use (to support community health workers), maternal mental health, and nutritional and health outcomes. These interventions included mobile apps, SMS text messaging, voice messaging, web-based applications, social media, movies and videos, and wearable or sensor-based devices. Second, we highlight key challenges: little attention has been given to understanding the lived experiences of the communities; key role players (eg, fathers, grandparents, and other family members) are often excluded; and many studies are designed considering nuclear families that do not represent the family structures of the local cultures.ConclusionsDigital MCH has shown steady growth in Africa and other LMIC settings. Unfortunately, the role of the community was negligible, as these interventions often do not include communities early and inclusively enough in the design process. We highlight key opportunities and sociotechnical challenges for digital MCH in LMIC, such as more affordable mobile data; better access to smartphones and wearable technologies; and the rise of custom-developed, culturally appropriate apps that are more suited to low-literacy users. We also focus on barriers such as an overreliance on text-based communications and the difficulty of MCH research and design to inform and translate into policy.

BackgroundDigital technology is a means to uphold or violate human rights in various domains, including business, military, and health. Given the pervasiveness of mobile technology in low- and middle-income countries (LMICs), mobile health (mHealth) interventions present an opportunity to reach remote populations and enable them to exercise civil and political rights and economic, social, and cultural rights, such as the right to health and education. Simultaneously, the ubiquity of mobile phones involves processing sensitive data which can threaten rights, including the right to privacy and nondiscrimination. Digital health is often promoted as advancing human rights and health equity; however, digital rights are underexplored in the literature on mHealth in LMICs. As such, creating an understanding of the digital rights topics covered in the 2022 literature is important to avoid exacerbating existing inequities relating to digital health design, use, implementation, and access.ObjectiveThis scoping review aims to identify digital rights topics in the 2022 peer-reviewed literature on mHealth in LMICs.MethodsThe Arksey and O’Malley framework for scoping reviews guides this review. Searches were performed across 7 electronic databases (Web of Science, Scopus, Ovid, ACM Digital Library, IEEE Xplore, ProQuest, and PubMed). The screening processes were guided by the research question “What digital rights topics have been explored in the 2022 literature on mHealth in LMICs?” Only papers addressing mHealth in LMICs and digital rights topics were included. Data extraction will include publication title, year, and type; first author’s affiliation country; LMICs implicated; infrastructure challenges; study aims, design, limitations, and future work; health area; mHealth technology, functions, purpose or application, and target end users; human or digital right terms used; explicit rights topics cited; and implied rights topics. The results will be reported using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist.ResultsThis scoping review was registered in Open Science Framework (December 22, 2022). Title and abstract screening and full-text paper screening were completed in 2023. This resulted in 56 papers being included in the study. The target date for completing data extraction and publishing a case study of the initial findings is the end of 2023. The full scoping review findings are expected to be disseminated through various pathways benefiting academia, practice, and policy making by the end of 2024. These include journal papers, conference presentations, publicly available toolkits for research and practice, public webinars, and policy briefs with evidence-based policy recommendations emerging from this review.ConclusionsThe planned scoping review will identify digital rights topics in the 2022 literature at the intersection of mHealth and LMICs. Furthermore, it will highlight the importance of patient empowerment, data protection, and inclusion in mHealth research and related policies in LMICs.Trial RegistrationOpen Science Framework osf.io/7mz24; https://osf.io/7mz24International Registered Report Identifier (IRRID)DERR1-10.2196/49150

BackgroundAgainst intensifying global aging, digital technologies are pivotal in supporting older adults’ health management. However, older adults often encounter significant barriers within social learning environments. Bandura’s Social Learning Theory (SLT) offers a valuable framework for enhancing older adults’ capacity to utilize digital technologies in health management within social settings. This study extends SLT by developing a novel community-based perspective, aligning it more closely with the social learning needs of older adults in digital health management. This study also responds to calls for culturally adaptable digital health frameworks by examining how Bandura’s SLT operates within Macao’s unique socio-cultural context while exploring transferability to low- and middle-income countries.Methods20 older adults were interviewed in semi-structured focus groups during four community health events in Macao. Guided by the core constructs of SLT, five dimensions—self-efficacy, observational learning, outcome expectations, reinforcement mechanisms, and environmental support—were predefined. Deductive thematic coding was employed to map interview data onto these dimensions, ultimately constructing a theoretical model.ResultsThe findings reveal that the five SLT dimensions interactively influence older adults’ adoption of digital health technologies. Younger seniors (60s) exhibit stronger observational learning tendencies than older seniors (80s). Living situation impacts environmental support utilization, as those living alone (75%) demonstrate greater reliance on community resources. Key enabling factors include technological usability, social trust-building, optimized incentive mechanisms, emotional support, and improved physical environments. These results validate and expand the applicability of SLT in the digital health domain for older adults.ConclusionThis study develops an environmentally adaptive SLT framework centered on older adults. While the model demonstrates strong contextual relevance in Macao, its core mechanisms show potential for adaptation in low- and middle-income countries through localized reinforcement strategies and infrastructure investment. The findings provide theoretical insights into the social mechanisms of digital health adoption and practical guidance for designing inclusive digital health interventions. Future research should explore personalized digital tools and conduct longitudinal studies to evaluate the long-term effectiveness of technological interventions.

Over the last 25 years, digital health interventions in low- and middle-income countries have undergone substantial transformations propelled by technological advancements, increased internet accessibility, and a deeper appreciation of the benefits of digital tools in enhancing health care availability. This study aims to examine the evolution, impact, and prospects of digital health interventions in low- and middle-income countries, highlighting their role in improving health care accessibility and equity. A retrospective analysis of digital health initiatives scanning the past two and a half decades focused on the progression from basic SMS platforms to sophisticated mobile health apps and other health digital interventions. Relevant literature and case studies were reviewed to elucidate key milestones, successes, challenges, and opportunities in advancing digital health initiatives in low- and middle-income regions. Digital health initiatives in low- and middle-income countries initially targeted specific health concerns, such as malaria diagnosis and treatment, through text-based platforms, demonstrating their efficacy in reaching remote and marginalized communities. With the proliferation of mobile phone ownership and internet access, these interventions evolved into comprehensive mobile health apps, facilitating self-care support, patient education, chronic disease monitoring, and remote consultations. The COVID-19 pandemic further accelerated the adoption of digital health interventions, particularly in disseminating health information, supporting contact tracing efforts, and enabling virtual consultations to alleviate strain on health care systems. The future of digital health interventions in low- and middle-income countries holds immense promise, fueled by emerging technologies such as artificial intelligence, machine learning, and blockchain. However, challenges persist in ensuring equitable access to digital health technologies, addressing disparities in digital literacy, and establishing robust health care infrastructure. Collaboration among governments, health care providers, technology innovators, and communities is essential to overcome these challenges and harness the full potential of digital health to improve health care outcomes in low- and middle-income countries.