Leveraging Mobile Health to Bridge Gaps for Children With Disabilities in LMICs

Abstract

Globally, an estimated 52.9 million (8.2%) children younger than 5 years have a disability, and 95% live in low- and middle-income countries (LMICs).1 Children with disabilities (CWD) in LMICs face profound barriers to health care, including stigma, poor disability awareness, specialist shortages, and financial and logistical challenges.1,2 Accessible and scalable resources are critically needed to close persistent gaps in early screening, diagnosis, care, and support. The rapid growth of mobile technology, through increasing access to mobile phones and tablets, offers an unprecedented opportunity to reimagine disability care. Mobile health (mHealth), the use of mobile devices to deliver and support health care, can play a critical role in extending essential health information, services, and social support to CWD and their families who have been historically left behind.3–6mHealth uses mobile devices to support health promotion, disease monitoring, diagnosis, interventions, and decision support systems. Its flexible tools, ranging from text messaging to interactive apps and videos, enable health communication and service delivery even in areas with limited infrastructure.3,5,7–9 Features such as reminders, visual demonstrations, and gamified content encourage engagement and reinforce learning, making mHealth especially valuable for families of CWD who may face challenges accessing in-person services.3,7This is all made possible by the great strides made toward expanding mobile access globally, with more than two-thirds of the global population subscribed to mobile services and 73% of users residing in LMICs.3 In some regions, mobile connectivity has become more accessible than electricity and water.5 Mobile internet coverage has reached 94%, with notable gains observed in Sub-Saharan Africa and the Pacific Islands.3,5 Building on the numerous successes in maternal, newborn, and child health programs,3,5,10–12 mHealth can extend similar innovations to CWD, improving screening, therapy delivery, and caregiver support at scale when paired with meaningful community infrastructure.mHealth offers unique opportunities to transform early identification, intervention, and caregiver support for CWD in LMICs. Its interactive and adaptable design allows for culturally and linguistically tailored programming and delivery.7 Its remote capabilities make specialized care, such as remote monitoring, teleconsultations, health education, and adherence support, accessible, especially in rural or resource-limited settings.3,5,7,8 Evidence from high-income countries (HICs) demonstrates feasibility and impact. For example, the Malo App, deployed in France, uses caregiver questionnaires to identify children at increased risk for autism, language delay, dyspraxia, dyslexia, and attention-deficit/hyperactivity disorder, prompting physician referrals that 70% of families pursued.13 Gamified therapy apps have improved adherence and outcomes for children with speech and motor delays.7,13 These approaches are now being adapted in LMICs, where mHealth shows strong feasibility for children with autism and other neurodevelopmental disabilities.14WhatsApp-delivered interventions have shown positive outcomes in both HICs and LMICs. In HICs, WhatsApp-based programs for caregivers of CWD have been associated with improvements in parental well-being, reductions in child behavioral symptoms, and increased physical activity.11,15 Likewise, in LMICs (eg, urban Tanzania and rural Zambia), WhatsApp support groups led by trained community health workers (CHWs) have demonstrated efficacy in improving responsive caregiving and caregiver mental health.8 In a systemic review of parent-oriented mHealth interventions, interventions specific to neurodevelopmental disabilities had the greatest impact on both child and parent health outcomes.11CHWs are critical, trusted links between families and health systems in LMICs.9,16 Task-shifting clinical roles to CHWs has improved access to care, reductions in morbidity and mortality, and meaningful behavioral change in a broad range of conditions.9,12,16 mHealth can further expand CHW effectiveness by offering real-time guidance, remote supervision, and digital training resources.9,16 When equipped with mobile tools, CHWs can deliver educational videos, perform technology-guided developmental screenings, and connect with higher-level clinicians, strengthening their expertise and credibility.9,12 In rural India, for example, CHWs had encountered resistance from community members who questioned their education, training, and socioeconomic status when implementing an intervention to support maternal health. When CHWs introduced short educational videos using mHealth, community engagement and motivation to learn from CHWs improved and led to strengthened maternal health outcomes.9,16 This illustrates how mHealth can similarly empower CHWs to deliver high-quality disability-related care and family education.Emerging support for mHealth developmental assessment and screening tools highlight their ability to standardize administration and reduce scoring error, which can allow administration by nonspecialists with minimal training.17 Additionally, mobile devices can capture images, video, and audio, estimate motion and force via accelerometers and gyroscopes, and assess response latency using timers during task. These capabilities allow nuanced data collection on children’s responses.2Tablet-based screening tools, such as the Early Years Toolbox and the NIH Toolbox, have emerged as practical alternatives in HICs and several LMICs, including countries in South Asia, Africa, and Latin America.2,17 Screening Tools for Autism Risk using Technology (START), a tablet-based autism screening tool, demonstrated proof of principle for integrating the use of mHealth by non–health care specialists (ie, CHWs) to identify autistic children in India. START combines interactive tasks, caregiver questionnaires, and observational assessments targeting social, sensory, and motor function. Qualitative interviews of health care workers, the CHWs, and participants families rated the measure as highly acceptable and feasible. Additionally, the majority of START measures yielded consistent differences between autistic and nonautistic children.17Although tablet-based screening tools may increase access in resource-limited settings, these screening tools only partially address workforce limitations as they depend on behavioral observations by nonspecialists and often require parent-reported information, assuming adequate knowledge of developmental milestones. Additionally, because the majority of these assessments were developed in HICs, further investigation of their validity and cross-cultural appropriateness in LMICs is important.2,17 Despite these limitations, such tools offer the potential for earlier identification of CWD.Despite promising evidence, important challenges remain. Inconsistent internet connectivity, variability in individual phone usage, and disparities in technological and health system infrastructure across LMICs are potential barriers to widespread scalability.5,10,18,19 These are particularly pronounced in rural areas and in poorer communities, with limited connectivity and phone ownership. Interestingly, studies suggest that a lack of individual phone ownership does not necessarily prevent involvement, as shared phone use, commonly seen in rural settings, can facilitate engagement.19 Although overall phone use and engagement remain lower in rural areas and poorer communities compared with urban and wealthier settings, evidence suggests this gap is gradually narrowing and connectivity challenges have been mitigated in some rural contexts.5,19 Without deliberate efforts to ensure equitable access, the scale-up of mHealth risks exacerbating these preexisting disparities.10,19,20Additional ethical considerations, such as privacy, data protection, and developmental appropriateness, are also critical, especially for child-facing applications.21 In many LMICs, female caregivers are the primary users of child health services, yet men consistently report higher rates of phone ownership, creating barriers to equitable access.6,12,19,20 Confidentiality concerns with shared devices, limited access to technology, and gender gaps in digital literacy can further constrain maternal caregivers’ ability to fully engage with mHealth programs.4,12 However, in the context of CWD, those sharing devices are often close family members already aware of the child’s condition, which may reduce confidentiality concerns. In fact, shared phone use may even foster social and technological support for caregivers from other users of the shared device.6,19,20 Given fathers’ underrepresentation in maternal newborn and child health (MNCH) initiatives and perception that these initiatives target mothers, mHealth strategies should be designed to address gendered dynamics intentionally, engaging both female and male caregivers to promote shared responsibility and maximize participations.4To fully realize mHealth’s transformative potential for CWD, these tools must be codesigned with end users (ie, caregivers/parent), clinicians, disability specialists, public health experts, and software developers to ensure cultural and contextual relevance.3,4,10,18 Beyond language translation and alignment with local technological infrastructure, programs must account for varying levels of functional literacy and prioritize the use of clear, accessible language for caregiver- or child-facing programs.2,8,10 Implementation strategies should also leverage existing community resources. Disability advocacy organizations and CHWs can play key roles in promoting uptake, bridging digital literacy gaps, and supporting equitable access.9,16 Partnerships with local governments and telecommunication providers are needed to integrate mHealth into national health frameworks, ensuring sustainability, affordability, and equity by improving connectivity, particularly in remote areas, and providing device access.5,9,10Sustained success will depend on strong governance. mHealth platforms should be managed collaboratively by local health authorities, partner nongovernmental organizations, and research institutions, with oversight mechanisms to ensure data security, privacy, and quality of care. Clear policies and governance structures are essential for accountability and institutionalizing mHealth into existing health systems.5,10,18Emerging applications of artificial intelligence (AI) are increasingly strengthening mHealth platforms, offering proactive health management and monitoring.22 For CWD, basic AI can support automated development tracking and generate personalized recommendations, such as behavioral intervention or therapy strategies. AI technologies facilitate translation across languages and dialects, a critical advantage in multilingual LMIC contexts. Conversational agents, programs that simulate human conversation, may provide real-time, individualized support to caregivers.23 Although the integration of AI into disability-focused mHealth remains an untapped frontier, careful attention to ethical oversight, data privacy, algorithm transparency, and local validation are essential to ensure AI tools are safe, effective, and contextually appropriate.22,23mHealth presents a promising opportunity to transform the lives of CWD and their families in LMICs. By increasing access to early identification, interventions, and caregiver education and support, it can dismantle barriers of distance, costs, and stigma. Specific considerations should be made to address language, cultural context, and setting-specific practices to promote effective implementation of mHealth interventions for CWD. With continued innovation, rigorous evaluation, and local collaboration, mHealth has great potential to advance inclusive child health systems—ensuring that every child, regardless of ability or geography, has the opportunity to thrive.