Understanding privacy disclosure intentions of young elderly users of mHealth applications: a mixed-methods empirical study

Purpose This study explores the factors influencing privacy disclosure intentions among the young elderly population when using mobile health (mHealth) applications (apps) and their action mechanisms to enhance user experience, improve product competitiveness and address the challenges of global aging. Design/methodology/approach We investigated the privacy disclosure intention of the young elderly using mHealth apps based on a stimulus-organism-response (SOR) model. Data from 746 valid samples were analyzed using a mixed-methods approach, including structural equation modeling (SEM) and fuzzy set qualitative comparative analysis (fsQCA). Findings Trust, health anxiety, and service quality positively influenced perceived value, which significantly enhanced privacy disclosure intentions. Privacy concern and subjective norm positively affected cognitive dissonance, which negatively impacted privacy disclosure intentions. The fsQCA identified three pathways driving these intentions. Building on these findings, we propose a set of practical recommendations to enhance the privacy disclosure intentions of young-elderly users, providing specific and actionable pathways for the design of mHealth apps and for global privacy governance. Originality/value This study extends the application of the SOR model to privacy disclosure intentions, specifically addressing the young elderly population with significant health needs and purchasing power. It provides valuable insights addressing global aging and promoting the development of digital health. By integrating SEM and fsQCA, this study explores cross-cultural differences and the substitution effect in fsQCA, providing a nuanced understanding of the complexities influencing privacy disclosure intentions.