Abstract
This paper conducts a critical comparative policy analysis (CCPA) and technopolitical analysis, selecting the United States—a market with highly penetrated digital health—and China—a market with rapidly expanding mobile health—as research cases. Taking dementia digital biomarkers as an analytical lens, it explores how health resources are allocated between digitally connected and disconnected older adults under the two countries' policy frameworks. Through structured thematic coding of purposively sampled policy documents, critical interpretive synthesis of technical literature on algorithmic bias, and cross-case synthetic critique, this study yields three core findings: (1) Policies of both nations embed an institutional bias of "digital-first", presupposing digital literacy as a prerequisite for service access and forming implicit exclusionary mechanisms; (2) Dementia digital biomarkers carry prominent algorithmic biases in research and validation, and social selectivity in training data leads to systematic misclassification across racial, educational, and linguistic groups; (3) Cross-cultural applicability challenges extend far beyond simple linguistic translation, involving deep cultural embeddedness in cognitive reserve, pragmatic norms, and biomarker cut-off values. Based on the above findings, this paper proposes an algorithmic justice framework, which regards distributive justice, recognition justice, and participatory justice as core ethical principles for digital geriatric health policies. It emphasizes dignity safeguards via non-digital pathways, community-participated algorithm validation, and inclusive representation of the Global South, to ensure digital innovation advances health equity rather than exacerbating pre-existing inequalities. When "smart" shifts from an adjective to the subject itself, technology becomes a de facto access threshold; this is the profound paradox that digital geriatric health policies must guard against.
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