EPIDEMIOLOGY AND HEALTH DATA INSIGHTS
Review Article
Sep 19, 2025 3 1

Behavioral Impacts of AI Reliance in Diagnostics: Balancing Automation with Skill Retention

Omolayo Sunday 1 *
1 Department of Natural Science, Kwara State University, Malete, Nigeria * Corresponding Author
Epidemiology and Health Data Insights, 1(4), 2025, ehdi014, https://doi.org/10.63946/ehdi/17088
Publication date: Sep 19, 2025
Full Text (PDF)

ABSTRACT

The COVID-19 pandemic accelerated the adoption of telemedicine and artificial intelligence (AI), transforming healthcare delivery worldwide. These technologies hold promise for improving access, efficiency, and diagnostic accuracy, but their benefits remain unevenly distributed. In many low- and middle-income countries (LMICs), persistent gaps in infrastructure, affordability, literacy, and governance risk turning digital innovation into a driver of health inequities. This paper examines the digital divide as a multidimensional health determinant encompassing infrastructure, affordability, human capacity, sociocultural inclusion, and governance. Using illustrative case studies from Africa, South Asia, Latin America, and high-income countries, this study highlights how telehealth and AI can enhance accessibility and enable task-shifting, while also demonstrating how exclusionary design and weak systems may perpetuate disparities. Building on these insights, the paper proposes a multi-sector framework for inclusive digital health, integrating investments in infrastructure, affordable and scalable models, digital literacy, culturally sensitive design, governance reform, sustainable financing, and public–private partnerships. To operationalize this framework, we recommend measurable indicators (e.g., affordability thresholds, literacy benchmarks, governance readiness indices) and propose implementation tools, including a logic model and barrier-to-action checklist. We argue that digital equity must be treated not as a peripheral issue but as a moral imperative for global health justice. Achieving this requires embedding equity into design, financing, and governance from the outset so that telehealth and AI reduce, rather than exacerbate, disparities in healthcare.

KEYWORDS

Telehealth Artificial Intelligence Healthcare Digital Divide Health Equity Global Health Policy Resource-Limited Settings

CITATION (Vancouver)

Sunday O. Behavioral Impacts of AI Reliance in Diagnostics: Balancing Automation with Skill Retention. Epidemiology and Health Data Insights. 2025;1(4):ehdi014. https://doi.org/10.63946/ehdi/17088
APA
Sunday, O. (2025). Behavioral Impacts of AI Reliance in Diagnostics: Balancing Automation with Skill Retention. Epidemiology and Health Data Insights, 1(4), ehdi014. https://doi.org/10.63946/ehdi/17088
Harvard
Sunday, O. (2025). Behavioral Impacts of AI Reliance in Diagnostics: Balancing Automation with Skill Retention. Epidemiology and Health Data Insights, 1(4), ehdi014. https://doi.org/10.63946/ehdi/17088
AMA
Sunday O. Behavioral Impacts of AI Reliance in Diagnostics: Balancing Automation with Skill Retention. Epidemiology and Health Data Insights. 2025;1(4), ehdi014. https://doi.org/10.63946/ehdi/17088
Chicago
Sunday, Omolayo. "Behavioral Impacts of AI Reliance in Diagnostics: Balancing Automation with Skill Retention". Epidemiology and Health Data Insights 2025 1 no. 4 (2025): ehdi014. https://doi.org/10.63946/ehdi/17088
MLA
Sunday, Omolayo "Behavioral Impacts of AI Reliance in Diagnostics: Balancing Automation with Skill Retention". Epidemiology and Health Data Insights, vol. 1, no. 4, 2025, ehdi014. https://doi.org/10.63946/ehdi/17088

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