Digital Health (Dec 2023)
Research on user's highly sensitive privacy disclosure intention in home intelligent health service system: A perspective from trust enhancement mechanism
Abstract
Objective The aim is to investigate the determinants and mechanisms that influence user's highly sensitive privacy disclosure intention (HSPDI) in home intelligent health service system (HIHSS). Methods This study improves the privacy calculus theory by considering the influence of service providers’ trust enhancement mechanism besides benefit and risk factors and investigates their impact on users’ HSPDIs. This study takes perceived valence and perceived security as the trade-off result among perceived benefits, perceived risks, financial trust enhancement mechanism, and the technical trust enhancement mechanism and suggests that perceived valence and perceived security further affect users’ HSPDI in HIHSS. Moreover, the common and differential effects of the perceived justice of privacy violation compensation (PJOPVC) and the perceived effectiveness of privacy protection technologies (PEOPPTs) are studied. The structural equation model is used to analyze 204 valid samples to test the proposed model. Results The results show that perceived benefits and perceived risks are important predictors of perceived valence and perceived security, and further affect users’ HSPDI. We find PJOPVC has a greater impact on perceived valence while PEOPPT has a greater impact on perceived security. Conclusions We recommend that the HSPDI of users with low perceived valence can be improved by providing privacy violation compensation while the HSPDI of users with low perceived security can be enhanced by popularizing relevant knowledge of privacy protection technologies.