Digital Literacy and Interpersonal Trust as Predictors of Willingness to Share Patient-Generated Health Data Among Korean Internet Users: Cross-Sectional Study Using Privacy Calculus and Communication Privacy Management Theories

Abstract Background The proliferation of wearable devices and advances in data analytics are accelerating the adoption of personalized digital health care, relying heavily on patient-generated health data (PGHD). However, the sensitive nature of this data creates significant privacy boundaries. While previous research has focused on rational cost-benefit trade-offs, there is a limited understanding of how social and cognitive factors—specifically interpersonal trust and digital literacy (DL)—shape the data-sharing decisions of the general public. Objective This study aims to identify the factors predicting individuals’ willingness to share health data (WS) by integrating privacy calculus and communication privacy management theories. It specifically examines the comparative influence of DL, interpersonal trust, and moral motivation on data-sharing decisions. Methods We analyzed data from the 2023 Korea Panel Survey on the Digital Society (n=4518), a nationwide representative sample of internet users. Survey-weighted structural equation modeling with weighted least squares mean and variance adjusted estimation was used to examine the relationships among perceived risk (PR), perceived benefit (PB), DL, interpersonal trust, and WS. Results PR was the strongest negative predictor of WS (standardized coefficient [std β ]=−0.189, P