Researchers at Stanford University have developed an open-source platform that allows scientists to study how daily digital interactions on smartphones affect physical and mental health. The platform, called Stanford Screenomics, is designed to help health researchers analyze large-scale behavioral data while ensuring the privacy of participants.
Smartphones continuously generate vast amounts of behavioral data through built-in sensors and interactions with users. These digital traces, such as app usage, screen activity, location data, and interaction patterns, form what researchers describe as a person's “screenome,” a concept introduced by Nilam Ram, professor of communication and psychology. According to a study published in Nature Health, the new platform makes it easier for researchers to collect and analyze such data without requiring advanced technical expertise.
Understanding digital behavior and health
The Stanford Screenomics platform was developed by a research team led by Ian Kim, a postdoctoral researcher in psychology at Stanford, and Professor Nilam Ram. Their goal is to better understand how people interact with digital environments and how these interactions affect health and well-being. “We want to gain insight into people's digital lives and help them interact with these environments in a positive way,” Ram said.
Previous work by the research group has already demonstrated the potential of screenome data. By taking screenshots and collecting additional data streams, such as GPS location, app preferences, typed words, and number of steps, the team gained insight into patterns in smartphone use and their relationship to mental health.
For example, the researchers found that smartphone use can correlate with weekly fluctuations in mental health and even show patterns in the days or hours leading up to a mental health crisis.
Flexible research infrastructure
To expand these possibilities, the researchers developed a comprehensive open-source platform that can collect more than 20 types of behavioral and contextual data simultaneously.
Via a web interface, researchers can configure studies using a drag-and-drop system, without the need for programming skills. The platform also provides dashboards to monitor data collection and automatically stores information in databases that comply with US health data regulations.
For participants, the accompanying smartphone app runs in the background while they go about their daily activities, discreetly collecting relevant data. “Our goal was to create a tool that is as flexible as it is powerful,” says Kim.
Built-in privacy safeguards
Because the platform processes highly sensitive information, such as app activity, screen content, physical movements, and location, privacy protection was central to its design. According to Ram, the research team implemented stricter confidentiality and privacy safeguards than those typically used by technology companies. Studies using the platform must be approved by an institutional review board and by the Google Play Store.
Participants must give informed consent and are clearly informed about what data is being collected, how often it is recorded, and how it will be used. The app also includes a pause function that allows users to temporarily stop data collection, for example during financial transactions or private conversations.
Personalized digital health interventions
Researchers hope the platform will support new studies on how digital environments influence health behaviors. Ian Kim is already using the system to investigate how smartphone use correlates with lifestyle factors such as physical activity and how digital triggers can influence health outcomes.
Looking ahead, the team sees opportunities to combine screenomics data with artificial intelligence to generate personalized interventions. “The next step is to integrate AI to convert raw screenome data into actionable insights,” Kim said. “Ultimately, we hope to go beyond observation and provide real-time, personalized, adaptive support.”
By lowering the technical barriers for researchers, the Stanford Screenomics platform could open up new avenues for studying the relationship between digital life and health, and for developing targeted interventions in the future.
Withdrawal symptoms
It is no longer news that (excessive) smartphone use can have negative consequences for (mental) health. Last year, research was conducted into the impact of limiting smartphone use. A study of 25 young adults (aged 18–30) suggested that limiting smartphone use can have effects similar to withdrawal symptoms. The participants had to limit their smartphone use to a minimum for three days and were only allowed to use the device for necessary tasks. Researchers performed fMRI brain scans before and after this period.
The comparison of the scans showed changes in brain areas involved in dopamine and serotonin processes, neurotransmitters that play a role in mood, emotions, and addictive behavior. According to the researchers, these changes show similarities to reactions that occur when detoxing from addictive substances or food cravings. Although the term “smartphone addiction” is still a subject of debate, there is growing attention in neuroscience for excessive smartphone use due to its potential negative effects on physical and mental health, especially in young people.
