Stanford University researchers have launched Stanford Screenomics, a new open-source platform designed to help health scientists study how digital interactions impact physical and mental well-being. Led by postdoctoral fellow Ian Kim and Professor Nilam Ram, the team released the Android-based tool to collect large-scale data on user behavior while strictly adhering to privacy standards. The initiative aims to transform raw digital traces, termed "screenomes," into actionable health insights. Modern smartphones contain numerous sensors that silently track a vast array of user activities, including step counts, sleep patterns, location history, and precise details of screen activity such as taps, scrolls, and visible content. Collectively, these data points form an individual's screenome. Previous research by Ram's group used similar data to uncover correlations between smartphone usage patterns and mental health fluctuations, offering clues about precursors to mental health crises. However, extracting such data has historically required significant technical expertise in software engineering and infrastructure, limiting its use to a select few researchers. Stanford Screenomics addresses this barrier by providing a comprehensive, turnkey solution that eliminates the need for coding skills. The platform features a user-friendly front-end console where researchers can configure study parameters using a drag-and-drop interface with simple on-off controls. A centralized dashboard allows for real-time monitoring of data collection progress, while all data is stored securely in HIPAA-compliant databases. For participants, a dedicated app operates unobtrusively in the background, capturing over twenty different data types simultaneously without disrupting daily routines. Privacy and security remain central to the platform's design due to the sensitive nature of the information involved. The team implemented ethical protocols that exceed standard corporate policies. To access the platform, researchers must secure approval from both Institutional Review Boards and the Google Play Store. The informed consent process is rigorous, requiring participants to explicitly acknowledge and understand every type of data being collected, its frequency, and its intended use. Furthermore, the participant app includes a prominent pause button, allowing users to immediately suspend data collection during private activities such as financial transactions or sensitive conversations. Users retain the ultimate control to disable the app entirely at any time. With a focus on preventive medicine, the platform is already being utilized to investigate the relationship between screen time and physical habits, as well as to identify digital triggers that influence health outcomes. Future developments aim to integrate artificial intelligence to process screenome data into real-time, personalized interventions. By moving beyond simple observation, the team hopes to provide adaptive support that helps individuals navigate their digital environments in healthier ways, ultimately bridging the gap between digital behavior and clinical health strategies.