Digital health and social needs: An empirical study of intentions and behaviors: An empirical study of intentions and behaviors

The convergence of wearable sensor technology and personalized predictive analytics has the potential to help researchers with early detection and treatment of medical problems. We anticipate that the clinical analysis of the flow of data coming from the individual's continuous monitoring will drive new discoveries and treatments. Moreover the development of personalized predictive models will drive the healthcare industry to shift from a reactive model to a proactive model, helping healthcare providers optimize care costs and offer a better customized service to patients. However, amidst the excitement for this new healthcare scenario, the amount of personal and sensitive data flowing from wearable devices to the cloud raises concerns about data security and customer privacy. While cyber-security experts and lawmakers are already working on securing the infrastructure, privacy issues are emerging from the individuals' social habits The convergence of social media with new wearable device features raises potential issues related to the online disclosure of sensitive medical data. Furthermore, the longitudinal collection of wearable data may lend itself to the development of new medical information, what we coin 'emergent medical records'. Data from an exploratory study shows how user intent to avoid potential privacy issues disclosing sensitive medical information collides with the individual's social propensity to share wearable information, generating a potentially regrettable behavior.