Papers by Dr. Levi Cheruo Cheptora
The MedClarity Journal, 2025
The contemporary human experience is defined by a profound paradox: at a time of unprecedented di... more The contemporary human experience is defined by a profound paradox: at a time of unprecedented digital connectivity, reports of social isolation, loneliness, and mental distress are escalating globally. This digital ghost in the machine haunts our hyper-connected world, where screens that promise community can often deepen our sense of estrangement. It is within this complex landscape that a new class of interventions has emerged, offering technological solutions to these fundamentally human problems. Digital Therapeutics (DTx) and a burgeoning ecosystem of Artificial Intelligence (AI)-powered mental health platforms represent a direct, ambitious, and heavily funded response to this paradox. They promise to democratize access to care, personalize support at an infinite scale, and reach the millions who suffer in silence, left behind by over-burdened and under-resourced traditional health systems.
This paper will argue, however, that the pursuit of a purely automated, AI-driven therapeutic model is a flawed techno-solutionist fantasy, particularly within the socio-culturally rich and infrastructurally complex context of Sub-Saharan Africa. The evidence reveals a landscape of stunning successes, glaring failures, and ethically ambiguous human-AI interactions—the hits, the misses, and the ugly beautiful. An analysis of this terrain suggests that the ideal digital social space for mental health is not a replacement for human connection but a form of "scaffolded digital belonging." This framework posits that technology's highest and best use is not to become a therapist, but to serve as an ethically designed, culturally attuned, and technologically accessible bridge that facilitates, augments, and ultimately hands users back to tangible human and community support systems.
To build this argument, this paper is structured in three parts. Part I will dissect the global landscape of DTx and AI in mental health, critically evaluating its promises and documented perils to understand the state of the art. Part II will ground this global analysis in the specific crucible of Sub-Saharan Africa, where universal models confront local realities of infrastructure, culture, and community, giving rise to a unique ecosystem of homegrown innovation. Finally, Part III will synthesize these global and local findings to propose a new design framework centered on the concept of scaffolded digital belonging, articulating what constitutes an ideal digital social space from the perspective of the adults who navigate these platforms in search of solace and connection.
The MedClarity Journal, 2025
Purpose This paper aims to define prompt engineering as a critical competency for modern healthca... more Purpose This paper aims to define prompt engineering as a critical competency for modern healthcare professionals. It analyzes its practical applications and evaluates its impact on clinical workflows, patient outcomes, and professional practice. Findings The synthesis of peer-reviewed and industry research demonstrates that effective prompt engineering significantly enhances the accuracy, efficiency, and safety of AI-driven tools in healthcare. The findings show that structured prompting techniques improve diagnostics, streamline administrative tasks, and facilitate more effective patient communication. The paper identifies a critical trade-off between accuracy and response time, underscoring the need for context-dependent prompting strategies. Research Limitations/Implications This research acknowledges the nascent stage of the field, noting the variability in model performance and the lack of standardized evaluation frameworks. It highlights the documented risk of professional skill degradation from over-reliance on AI, proposing future research directions into human-AI collaboration models that augment rather than replace core competencies. Practical Implications Mastering prompt engineering provides healthcare professionals with the tools to leverage AI responsibly, reducing administrative burden and combating burnout while focusing on high-value, patient-centric care. It enables the customization of AI to meet specific, nuanced clinical needs, thus maximizing both operational and ethical return on investment (ROI). Social Implications The research highlights the necessity of addressing algorithmic bias to ensure health equity, the critical importance of robust data privacy frameworks, and the transformation of the traditional doctor-patient relationship into a collaborative, information-rich dynamic. Originality/Value This paper provides a unique and timely synthesis of diverse research to establish a robust framework for understanding prompt engineering as a core skill. It bridges the technical and clinical domains to inform not only individual practice but also institutional policy, educational curricula, and ethical governance for the future of medicine.
The Frontiers, 2025
The translation of scientific discoveries from the laboratory to impactful health solutions is a ... more The translation of scientific discoveries from the laboratory to impactful health solutions is a complex, multi-stage endeavor, particularly within the biomedical sector. This report outlines the critical processes and strategic considerations necessary for successful commercialization, emphasizing the unique opportunities and inherent challenges presented by Artificial Intelligence (AI) and digital health innovations, especially in low-resource settings such as Sub-Saharan Africa. Effective commercialization bridges the gap between groundbreaking research and accessible patient treatments, serving as a vital catalyst for health equity. Navigating this intricate landscape requires a holistic approach that integrates robust intellectual property protection, comprehensive market analysis, diversified funding strategies, and adaptive commercialization pathways. Furthermore, the ethical implications of emerging technologies, particularly AI bias and data privacy, demand proactive governance and culturally sensitive deployment to foster trust and ensure sustainable, equitable health outcomes globally.
The Frontiers, 2025
Purpose This paper argues that localizing innovations is the most effective and sustainable strat... more Purpose This paper argues that localizing innovations is the most effective and sustainable strategy for strengthening Primary Health Care (PHC) systems across Africa. It aims to explore why context-specific, community-driven solutions are uniquely positioned to address the continent's diverse health challenges, foster resilience, and accelerate progress towards Universal Health Coverage (UHC). Findings Localized innovations are crucial because they directly address the unique socio-cultural, economic, and epidemiological contexts of African communities, ensuring relevance and acceptability. They promote community ownership, enhance resourcefulness, and build sustainable capacities within the health system. Successful localization involves participatory design, iterative development, and adaptive scaling strategies that prioritize integration into existing health structures and policy frameworks. This approach contrasts sharply with top-down, imported solutions, which often fail due to lack of fit, limited community buy-in, and unsustainable reliance on external resources. Research Limitations/Implications While the benefits of localized innovations are increasingly recognized, research gaps persist in systematically evaluating their long-term impact and scalability across diverse African settings. More robust methodologies are needed to capture the qualitative benefits and economic viability of these grassroots solutions. Implications suggest a need for funding mechanisms and policy frameworks that specifically support the incubation, piloting, and adaptive scaling of locally-generated health innovations, moving beyond short-term project funding. Practical Implications For policymakers and healthcare providers, this paper emphasizes the imperative to shift from a reliance on externally-driven models to fostering an environment that nurtures and scales local ingenuity. This involves investing in community health worker programs, establishing innovation hubs, facilitating knowledge exchange, and creating flexible regulatory pathways for local solutions. Social Implications Localizing innovations empowers communities, enhances health equity by addressing specific needs of marginalized populations, and builds resilient health systems capable of responding to evolving challenges. It fosters self-reliance and dignity, contributing to broader socioeconomic development by leveraging local assets and knowledge. Originality/Value This paper synthesizes arguments for localized innovation within the specific context of African PHC, offering a comprehensive framework that integrates conceptual understanding, methodological approaches, critical success factors, and funding considerations. It provides a foundational perspective for researchers, practitioners, and policymakers committed to building sustainable and equitable health systems in Africa.
The Frontiers Digital Health, 2025
This report critically examines the profound role of patient education, significantly augmented b... more This report critically examines the profound role of patient education, significantly augmented by Generative Artificial Intelligence (GenAI), in addressing the persistent Maternal, Neonatal, and Child Health (MNCH) burden within resource-constrained Sub-Saharan Africa (SSA). It provides a comprehensive synthesis of the current MNCH challenges, explores GenAI's transformative potential in health promotion and prevention, and offers a critical evaluation of the practical, ethical, and social implications of its implementation. SSA continues to bear a disproportionately high MNCH burden, with maternal mortality ratios significantly above global targets and leading causes often preventable. 1 Patient education is recognized as foundational for improved health outcomes, compliance, and self-care. 7 GenAI offers unprecedented opportunities for personalized, scalable, and culturally sensitive health information dissemination. 9 Beyond education, GenAI applications in healthcare extend to diagnostics, personalized treatment plans, monitoring, and administrative efficiency, promising to augment human capacity in settings with limited resources. 10 However, the widespread adoption of GenAI in SSA faces significant barriers, including inadequate digital infrastructure, issues of data quality and inherent bias, digital literacy gaps, and complex regulatory landscapes. 17 Ethical considerations, such as data privacy, algorithmic bias, transparency, and sociocultural acceptance, are paramount for ensuring equitable and effective deployment. 23 To effectively leverage GenAI in addressing the MNCH burden, strategic investments in digital infrastructure, robust data governance, targeted capacity building, and community-led, culturally sensitive AI development are crucial. This report provides a timely and comprehensive analysis, bridging the fields of public health, AI, and development, specifically tailored to the unique context of SSA's MNCH crisis, offering a roadmap for innovative, ethical, and sustainable interventions.
The Frontier Journals, 2025
This paper introduces a comprehensive, multifactorial framework designed to empower academics, Te... more This paper introduces a comprehensive, multifactorial framework designed to empower academics, Technology Transfer Offices (TTOs), and innovators, particularly within Africa and globally, in navigating the intricate journey of research commercialization. Moving beyond traditional linear models, the framework emphasizes the simultaneous consideration and strategic integration of intellectual property (IP) protection, diverse funding mechanisms, rigorous market needs assessment, and robust team building. By dissecting the critical interplay of these factors, the research aims to unlock the full commercial potential of academic and institutional research, fostering a more effective transition from laboratory discoveries to impactful market solutions. This work provides actionable insights and a structured approach to enhance the success rate of commercialization initiatives, contributing significantly to innovation ecosystems worldwide.
The Medical Clarity Journal (MCJ), 2025
Purpose This study aims to comprehensively investigate the critical role and transformative poten... more Purpose This study aims to comprehensively investigate the critical role and transformative potential of Machine Learning (ML) in developing robust and effective symptom-based triage systems for healthcare in low-resource settings, specifically within the unique and often challenging context of Sub-Saharan Africa (SSA). It seeks to meticulously identify and analyze key lessons learned from the region's pioneering experiences with early Artificial Intelligence (AI) and broader digital health adoptions, paying particular attention to their applicability in primary care, community health, and emergency response scenarios. Furthermore, the research endeavors to dissect the prevalent, multifaceted, and interconnected challenges currently hindering the widespread, equitable, and impactful application of ML-driven triage solutions across SSA's diverse and complex health systems. Finally, it proposes a comprehensive set of strategic, actionable, and forward-looking future directions meticulously designed to foster the ethical, sustainable, and truly transformative deployment of AfriHealth AI, a conceptual framework for African-centric ML triage, ensuring it contributes meaningfully to improved health outcomes, enhanced healthcare accessibility, and greater health equity throughout the continent. Findings The research reveals that ML-driven symptom-based triage holds immense and largely untapped promise for SSA healthcare, offering innovative and scalable solutions capable of significantly enhancing the efficiency of patient flow, rapidly identifying critical cases that require immediate attention, optimizing the allocation of scarce medical resources, and expanding access to timely and appropriate medical advice, particularly in underserved and remote areas where conventional healthcare infrastructure is limited. By addressing critical resource scarcities, augmenting the capabilities of overstretched human healthcare professionals, and improving the efficiency of existing systems, ML presents a powerful and indispensable tool for improving the initial assessment, prioritization, and appropriate routing of patients. However, its widespread, equitable, and sustainable adoption is significantly challenged by pervasive and systemic issues. These include the acute scarcity of diverse, high-quality, and representative clinical datasets specific to African populations, which are fundamental for training unbiased and accurate ML models; severe limitations in digital infrastructure, encompassing inadequate computing power, unreliable internet connectivity, and inconsistent energy access across vast geographical areas; a critical and widening talent gap in specialized ML expertise, alongside a broader deficiency in digital literacy within the existing healthcare workforce; and the nascent, often fragmented, development of robust ethical, legal, and regulatory frameworks necessary to
The Medical Clarity Journal (MCJ)
This study aims to comprehensively investigate the critical role and transformative potential of ... more This study aims to comprehensively investigate the critical role and transformative potential of Generative Artificial Intelligence (AI) in driving healthcare innovations within the unique and often resource-constrained context of Sub-Saharan Africa (SSA). Specifically, it seeks to identify and analyze key lessons learned from the region's pioneering experiences with early AI and broader digital health adoptions. Furthermore, the research endeavors to dissect the prevalent and interconnected challenges currently hindering Generative AI's widespread, equitable, and impactful application across SSA's diverse and complex health systems. Finally, it proposes a set of strategic, actionable future directions designed to foster the ethical, sustainable, and truly transformative deployment of Generative AI, ensuring it contributes meaningfully to improved health outcomes and health equity throughout the continent.
The Frontiers, 2025
Purpose This comprehensive scoping review aims to systematically synthesize and critically evalua... more Purpose This comprehensive scoping review aims to systematically synthesize and critically evaluate the existing literature on the feasibility, effectiveness, and multifaceted impact of various digital health technologies in addressing the persistent challenge of maternal, neonatal, and child health (MNCH) deaths across the diverse landscape of Sub-Saharan Africa. With a specific and in-depth focus on Kenya as a compelling case study, the primary objective is to identify and appraise the evidence regarding how these innovative technologies, ranging from basic mobile health (mHealth) applications to advanced telemedicine and sophisticated digital data management systems, can strategically enhance access to quality care, significantly improve the capacity and performance of frontline health workers, strengthen fragmented health information systems, and ultimately contribute to a substantial reduction in preventable MNCH mortality rates. By doing so, this review seeks to illuminate how digital health can effectively bridge critical gaps in healthcare delivery, particularly in the most underserved and resource-limited settings within the region. Findings The synthesized literature consistently indicates that digital health technologies demonstrate significant and growing promise in improving MNCH outcomes across Sub-Saharan Africa, with numerous impactful examples emanating from Kenya. Specifically, studies highlight how mHealth interventions, encompassing targeted SMS messaging, interactive voice response (IVR) systems, and dedicated mobile applications, effectively enhance health education for expectant mothers and caregivers, improve adherence to crucial antenatal and postnatal appointments, and facilitate seamless, real-time communication between patients and healthcare providers. Telemedicine applications are shown to dramatically expand access to specialized medical consultations and expert support for health workers in remote and geographically isolated areas. Concurrently, digital training tools and e-learning platforms demonstrably improve the knowledge, clinical skills, and confidence of frontline health workers, including community health volunteers and midwives. Furthermore, the adoption of robust digital data management systems contributes profoundly to more accurate and timely disease surveillance, optimized resource allocation, and enhanced program monitoring and evaluation. While inherent challenges related to infrastructure, digital literacy, and sustainability persist, the cumulative evidence suggests that these technologies enable more timely and appropriate interventions, significantly improve health literacy among populations, and fundamentally strengthen fragile health systems, collectively contributing to a measurable reduction in preventable MNCH deaths.
The Frontiers, 2025
Purpose This scoping review aims to synthesize existing literature on the feasibility, effectiven... more Purpose This scoping review aims to synthesize existing literature on the feasibility, effectiveness, and impact of integrating AI-automated fetal ultrasound systems, particularly those designed for AIguided probe placement and emergency detection (e.g., breech presentation, placenta previa), into the routine antenatal care provided by community midwives in resource-limited settings. The primary objective is to identify and evaluate evidence regarding how such systems can enhance early detection of high-risk pregnancies, improve referral pathways, and ultimately contribute to better maternal and fetal outcomes, thereby addressing critical gaps in diagnostic imaging accessibility. Findings The synthesized literature indicates that AI-automated fetal ultrasound systems show significant promise in improving the accuracy of basic obstetric scans performed by non-specialist healthcare providers, including community midwives, often with minimal prior sonography training. Studies highlight that AI-guided probe placement features reduce user-dependent variability, leading to more consistent and higher-quality image acquisition. Furthermore, evidence suggests that AIpowered emergency detection modules can accurately identify critical conditions such as breech presentation and suspected placenta previa, facilitating timely referrals to higher-level facilities. This enhanced diagnostic capability at the community level appears to enable earlier intervention, potentially reducing complications associated with late detection of obstetric emergencies. Research Limitations/Implications While the reviewed literature presents a compelling case, limitations include the nascent stage of research in this specific domain, often characterized by pilot studies and small sample sizes. Gaps exist in long-term sustainability assessments, comprehensive cost-effectiveness analyses, and the scalability of these AI systems across diverse cultural and logistical environments. Implications for future research include the urgent need for robust regulatory frameworks for AI in healthcare, the development of scalable training and support mechanisms for midwives, and a thorough examination of ethical considerations related to data privacy, algorithmic bias, and accountability in AI diagnostics. Practical Implications The practical implications derived from the literature are substantial. The integration of AI-automated fetal ultrasound systems could decentralize essential diagnostic services, significantly improving antenatal screening accessibility for pregnant women in remote or underserved areas. This technology empowers community midwives, enhancing their role in identifying and managing high-risk pregnancies and potentially reducing the burden on centralized healthcare facilities. The findings also underscore the potential for innovative training models that integrate AI tools, thereby upskilling the existing healthcare workforce and optimizing resource allocation. Social Implications The adoption of AI-automated fetal ultrasound for community midwives carries profound social implications, as evidenced by the literature. It promotes health equity by democratizing access to critical antenatal diagnostics, potentially contributing to a reduction in maternal and neonatal mortality rates among vulnerable populations. Empowering community midwives with advanced tools can elevate their professional standing and confidence, fostering stronger community trust in local healthcare providers. Moreover, by enabling earlier detection of complications, these systems can alleviate anxiety for expectant mothers and their families, contributing to overall community well-being.
The Digital Health Frontiers Journal, 2025
This report provides a comprehensive analysis of Dr. Levi Cheruo Cheptora's pioneering framework,... more This report provides a comprehensive analysis of Dr. Levi Cheruo Cheptora's pioneering framework, "Harnessing African-Generated Big Data for Precision Drug Discovery: A Low-Cost Framework for Endemic Disease R&D." The framework directly confronts Africa's disproportionate global disease burden-25% of all diseases worldwide-contrasted with its minimal participation in clinical trials, which stands at less than 3% [User Query Abstract]. This significant disparity highlights a critical innovation gap where the populations most affected by diseases are least involved in developing therapeutic solutions. The framework proposes a three-pillar solution: the Reverse Drug Discovery Pipeline, the OASIS Consortium, and the Ubuntu Data Sovereignty Model. The framework's validated outcomes are compelling, demonstrating a 40% faster lead compound identification for malaria and Schistosomiasis, alongside $17 million in R&D cost savings, resulting in three patent-pending drug candidates [User Query Abstract]. These achievements underscore the framework's potential to redefine global drug discovery by strategically leveraging Africa's unique resources and ethical governance principles. The approach transforms Africa from a recipient of global health interventions into a potential global biomedical frontier, offering critical insights into human biology and physiology that can benefit global health. 1 This report will detail the framework's components, its practical applications, its disruptive potential, and strategic implications for drug discovery in Africa and globally, concluding with recommendations for policymakers, researchers, and global stakeholders.
The Digital Health Frontiers Journal, 2025
This report evaluates the transformative potential of integrated digital health solutions in adva... more This report evaluates the transformative potential of integrated digital health solutions in advancing universal health coverage (UHC), improving health outcomes, and empowering patients within resource-constrained contexts across Sub-Saharan Africa (SSA). The analysis draws upon extensive research and real-world experience, particularly highlighting the contributions of innovators like Dr. Levi Cheruo Cheptora. Findings indicate that despite significant advancements and growing interest, the scalable and equitable adoption of digital health technologies (DHTs) in SSA is hindered by persistent, interconnected barriers. These include fragmented health systems, pervasive digital literacy gaps, inadequate policy frameworks, and critical infrastructural and financial limitations.
The Digital Health Frontiers Journals, 2025
Purpose: This white paper aims to synthesize current knowledge and evidence on the intersection o... more Purpose: This white paper aims to synthesize current knowledge and evidence on the intersection of evidence-based policy (EBP) and digital health in Africa, identifying critical challenges and opportunities. It seeks to provide a strategic framework and actionable recommendations for policymakers and stakeholders to foster the sustainable and equitable integration of digital health solutions into African healthcare systems, ultimately enhancing health outcomes across the continent. Findings: Analysis reveals that while digital health holds immense promise for improving healthcare access, efficiency, and quality in Africa, its full potential is hampered by significant barriers. These include inadequate infrastructure, limited digital literacy, fragmented policy frameworks, and insufficient funding. Conversely, successful initiatives demonstrate the transformative impact of digital health in areas like disease surveillance, remote consultations, and health information management. The findings underscore the critical role of robust EBP in overcoming these challenges and ensuring that digital health interventions are effective, sustainable, and tailored to local contexts. Research: This paper adopts a comprehensive review methodology, drawing upon a wide range of academic literature, policy documents, case studies from African digital health initiatives, and reports from international organizations. It synthesizes findings from various disciplines, including public health, health informatics, economics, and policy science, to provide an evidence-based perspective on the current landscape and future directions for digital health in Africa. Limitations/Implications: The primary limitations include the dynamic nature of digital health technologies and policies, which necessitates continuous updates to evidence. Furthermore, while the paper highlights generalizable insights, the diverse socioeconomic and political landscapes across African countries mean that recommendations may require significant contextual adaptation. Implications include the need for sustained investment in digital infrastructure, capacity building, and flexible policy frameworks that can adapt to rapid technological advancements. Practical Implications: The recommendations presented offer practical guidance for policymakers, healthcare leaders, and technology developers. These include prioritizing the development of national digital health strategies, investing in digital literacy and health workforce training, fostering public-private partnerships, and establishing robust monitoring and evaluation frameworks to ensure accountability and impact. Social Implications: Effective evidence-based digital health policies have profound social implications, leading to more equitable access to healthcare services, particularly for remote and underserved populations. They can reduce health disparities, empower individuals through better health information, and strengthen community health resilience. Improved health outcomes contribute to broader socioeconomic development and poverty reduction across the continent. Originality/Value: This white paper provides a unique and timely synthesis of EBP principles applied specifically to the burgeoning field of digital health in Africa. By bridging the gap between evidence generation and policy implementation in this critical area, it offers original insights and a consolidated resource for stakeholders committed to leveraging technology for health improvement in the African context. It moves beyond simply identifying challenges to proposing a structured, evidence-informed pathway for transformation.
Frontiers in Digital Health, 2025
This study examines the state of interoperability in Kenya's public healthcare system, identifyin... more This study examines the state of interoperability in Kenya's public healthcare system, identifying key challenges, opportunities, and pathways to achieving seamless health information exchange. It evaluates the role of policy frameworks, technological innovations, and stakeholder collaboration in enhancing interoperability, with a focus on improving healthcare accessibility, efficiency, and patient outcomes. Findings The research highlights critical interoperability gaps in Kenya's public healthcare system, including fragmented health information systems (HIS), lack of standardized data protocols, and inadequate digital infrastructure. However, opportunities exist through emerging government initiatives, AI-driven health informatics solutions, and increased adoption of electronic health records (EHRs). Addressing these barriers could lead to better patient data integration, improved clinical decision-making, and enhanced health service delivery. Research Limitations/Implications This study relies on secondary data sources, expert analyses, and case studies, which may limit its empirical generalizability. Future research incorporating primary data collection and real-world implementation studies is recommended to validate the findings and assess long-term impact. Practical Implications The study provides policy recommendations and technical insights for government agencies, healthcare providers, and technology developers to design interoperable digital health systems tailored to Kenya's healthcare needs. Strengthening interoperability can improve healthcare coordination, reduce redundancy, and enhance patient outcomes. Social Implications Improved health data interoperability can enable better patient care continuity, reduce medical errors, and enhance resource allocation. This is particularly crucial for rural and underserved communities, where digital health solutions can bridge gaps in healthcare access. Originality/Value This research contributes to the growing body of knowledge on digital health interoperability in Africa by focusing on Kenya's public healthcare system. It provides a comprehensive analysis of interoperability barriers and solutions, offering a strategic roadmap for policymakers, health informatics professionals, and researchers.
Frontiers in Digital Health, 2025
This study explores the integration of artificial intelligence (AI) and telemedicine to improve h... more This study explores the integration of artificial intelligence (AI) and telemedicine to improve healthcare accessibility and efficiency in Kenya. It evaluates current adoption trends, challenges, and the potential impact of AI-driven telemedicine solutions on patient care, particularly in rural and resource-limited areas. Findings The findings indicate that AI-enhanced telemedicine platforms have the potential to bridge the healthcare gap in Kenya by providing timely diagnostics, remote consultations, and predictive analytics for disease management. However, barriers such as inadequate infrastructure, digital literacy challenges, and regulatory hurdles must be addressed for widespread adoption. Research Limitations/Implications This study is based on existing literature, expert opinions, and case studies, which may limit the generalizability of findings. Future empirical studies with primary data collection are necessary to validate the proposed solutions. Practical Implications The study provides insights for policymakers, healthcare institutions, and technology developers to design and implement AI-driven telemedicine solutions tailored to Kenya's unique healthcare landscape. Social Implications Enhancing healthcare delivery through AI and telemedicine can lead to improved health outcomes, reduced patient burden, and increased access to quality healthcare, particularly for underserved populations. Originality/Value This research contributes to the growing body of knowledge on digital health in Africa by focusing on AI-driven telemedicine applications in Kenya, a country with significant healthcare challenges and opportunities for technological innovation.
TELECARE, 2024
This study investigates the efficacy of various digital therapeutic interventions, including apps... more This study investigates the efficacy of various digital therapeutic interventions, including apps, online platforms, and wearables, for managing and treating mental health conditions such as depression, anxiety, and PTSD. The research compares the effectiveness of these digital interventions with traditional face-to-face therapy approaches. Purpose: The purpose of this study is to assess the effectiveness of digital therapeutic interventions in managing mental health conditions and to compare their efficacy with traditional face-to-face therapy. Design/methodology/approach: A systematic review and meta-analysis are conducted to synthesize existing evidence on the effectiveness of digital therapeutic interventions for mental health. Studies comparing digital interventions with traditional therapy approaches are analyzed to determine comparative efficacy.
TELECARE, 2024
The paper aims to shed light on how digital health interventions can serve as a cornerstone for a... more The paper aims to shed light on how digital health interventions can serve as a cornerstone for achieving UHC in regions facing resource constraints, with a specific focus on the Kenyan healthcare ecosystem. It synthesizes realworld examples and practical considerations to provide valuable insights for policymakers, healthcare practitioners, and digital health stakeholders. Design/methodology/approach-Utilizing a qualitative approach, this paper leverages the author's practical experiences and industry knowledge. The methodology involves a comprehensive review of existing digital health initiatives, case studies, and firsthand observations in the Kenyan healthcare sector. Findings-The findings underscore the transformative impact of digital health technologies in overcoming challenges related to limited resources. Key insights include the success stories of specific digital health interventions, their contribution to healthcare equity, and the lessons learned from their implementation in Kenya. Research limitations/implications-While the paper draws on practical experiences, it acknowledges the evolving nature of the digital health landscape. The limitations include the dynamic nature of technology, regulatory frameworks, and the need for ongoing adaptation to emerging challenges.
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Papers by Dr. Levi Cheruo Cheptora
This paper will argue, however, that the pursuit of a purely automated, AI-driven therapeutic model is a flawed techno-solutionist fantasy, particularly within the socio-culturally rich and infrastructurally complex context of Sub-Saharan Africa. The evidence reveals a landscape of stunning successes, glaring failures, and ethically ambiguous human-AI interactions—the hits, the misses, and the ugly beautiful. An analysis of this terrain suggests that the ideal digital social space for mental health is not a replacement for human connection but a form of "scaffolded digital belonging." This framework posits that technology's highest and best use is not to become a therapist, but to serve as an ethically designed, culturally attuned, and technologically accessible bridge that facilitates, augments, and ultimately hands users back to tangible human and community support systems.
To build this argument, this paper is structured in three parts. Part I will dissect the global landscape of DTx and AI in mental health, critically evaluating its promises and documented perils to understand the state of the art. Part II will ground this global analysis in the specific crucible of Sub-Saharan Africa, where universal models confront local realities of infrastructure, culture, and community, giving rise to a unique ecosystem of homegrown innovation. Finally, Part III will synthesize these global and local findings to propose a new design framework centered on the concept of scaffolded digital belonging, articulating what constitutes an ideal digital social space from the perspective of the adults who navigate these platforms in search of solace and connection.