Factors Influencing Home Care Nurses' Behavioral Intention to Use Digital Healthcare

Home care and digital healthcare are essential strategies for addressing health challenges in an aging society. This study aims to understand the behavioral intention (BI) to use digital healthcare and its influencing factors based on the Unified Theory of Acceptance and Use of Technology.

This cross-sectional study surveyed 180 home care nurses in South Korea using online questionnaires. Participants were from hospital-based home care (HHC), home hospice (HH), and community health center-based home care (CHC). The survey assessed their experience with and intention to use 19 digital health technologies and measured key factors based on the Unified Theory of Acceptance and Use of Technology: performance expectancy, effort expectancy, social influence (SI), attitude toward digital healthcare, and concerns.

Among the 19 digital health technologies, big data/artificial intelligence solutions (87.2%) and artificial intelligence-assisted care sensors (85.6%) had the highest BI to use. Usage experience and intention were negatively correlated across all technologies (κ = -0.10 to -0.70, p < .001). Behavioral intentions differed significantly between groups (χ² = 6.35, p = .042), with HH nurses reporting the highest intention (93.8%), followed by HHC (87.0%) and community health center-based home care (75.0%) nurses. Effort expectancy increased adoption likelihood (odds ratio = 2.26, 95% confidence interval: 1.10-4.62, p = .026), while SI was the strongest predictor (odds ratio = 2.93, 95% confidence interval: 1.15-7.46, p = .024).

Home care nurses generally showed strong BI to adopt digital healthcare. However, the negative association between experience and intention suggests the need to enhance user satisfaction when implementing digital health technologies. Since effort expectancy and SI significantly affect adoption, reducing perceived effort and strengthening social support are essential for successful integration.