The Screenomics Data Collection App

Digital phenotyping using personal digital trace data can help identify behavioral patterns and health risk factors, supporting personalized interventions for public health equity. However, tools and frameworks for comprehensive digital trace data collection are lacking.

The Stanford Screenomics Project introduces an open-source platform for Screenomics research, enabling in-situ, real-time capture of multimodal digital traces from users’ smartphones as they go about their everyday lives.

The hyper-intensive longitudinal digital trace data obtained with the Stanford Screenomics app – including screenshots, application usage logs, interaction histories, and phone sensor readings (e.g., GPS, motion) – empowers researchers to conduct in-depth observations of a wide variety of individual and social behaviors. By design, the data collection process is unobtrusive, minimizing the welldocumented biases embedded in individuals’ self-reports of behavior. The platform consists of two native Android front-end applications and a back-end data repository.

The Stanford Screenomics Data Collection application offers extensive customization options, allowing researchers to tailor, with minimal additional development effort, the types of data recorded, sampling frequency, how data are transferred from user smartphone to research server, and upload cadence to match their specific study design and requirements. The platform’s Dashboard application supports research coordinators’ real-time monitoring of participants’ data provision, identifying issues in data collection, and automated reactive communications with participants. The platform’s back-end uses a flexible and scalable NoSQL database (Google Cloud Firestore) for secure HIPAA-compliant data storage. Using illustrative 24-hour digital trace data we demonstrate how the platform expands the range of digital phenotyping studies that researchers can now launch.