Digital health platforms (DHPs) present the opportunity for individuals to manage their personal health more effectively through seeking and obtaining health advice. However, little is known about the factors that influence self-disclosure on these platforms and are therefore critical for their success. This research proposes that self-disclosure on a DHP is influenced by trust in health platforms (THP) and health information privacy concerns (HIPC) across different cultures and personalities. Using data from Ireland and the United States, it develops a framework that harnesses social exchange theory (SET) and social penetration theory (SPT) as a lens to understand self-disclosure on DHPs. It examines the factors that generate THP and HIPC. It then determines the influence of THP and HIPC on self-disclosure. Finally, the model offers a unique look at the role of personality traits and the influence they have on likelihood to self-disclose. A two-stage mixed-methods data collection approach was employed to explore these propositions. Quantitative surveys were used to collect data from 300 participants in Ireland and America. 20 qualitative research interviews were then conducted with Irish and American participants. The quantitative and qualitative findings were then integrated and evaluated in the context of the hypothesised relationships. The integrated findings show THP is the critical pathway to self-disclosure. THP is shaped by social influence, perceived reciprocity and privacy risk beliefs. HIPC is shown to reduce THP. Personality traits also influence self-disclosure. This study extends SET and SPT to a digital health platform context. The findings provide actionable insights, which can assist policy makers who wish to protect citizen health data and health technology vendors who seek to develop trustworthy platforms.