Date of Conferral

2-25-2026

Degree

Ph.D.

School

Management

Advisor

Jean Gordon

Abstract

Rural Appalachian communities in the United States experience disproportionately high chronic disease burden. Mobile health (mHealth) technology adoption among providers remains low despite potential to improve care access. Understanding adoption factors is critical for addressing health inequities. The purpose of this quantitative cross-sectional study was to examine whether diffusion of innovations (DOI) theory attributes predict current mHealth adoption among health care professionals involved in rural Appalachian primary care delivery and whether structural constraints moderate these relationships. Despite extensive DOI validation in well-resourced settings, its applicability to severely resource-constrained contexts remained empirically uncertain. Data from 100 health care professionals across eight Appalachian states were analyzed using hierarchical logistic regression. Results revealed that trialability emerged as the strongest adoption predictor (OR = 3.89, p < .001), followed by relative advantage (OR = 2.34, p < .01), while complexity showed no significant effect. Structural constraints independently reduced adoption likelihood (OR = 0.42, p < .01) but did not significantly moderate attribute-adoption relationships, suggesting additive rather than interactive effects. The final model explained 61% of variance in current adoption and correctly classified 82% of cases. Findings indicate contextual variation in DOI attribute effect magnitudes. The key positive social change implication is that organizations can enhance adoption by prioritizing trial opportunities alongside addressing infrastructure barriers, while policymakers can support mobile health reimbursement and infrastructure investment.

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