Project Baseline launches Mood Study to explore new digital markers of depression
Depression is the leading cause of disability worldwide. While a growing national dialogue around mental health means awareness of mood disorders is higher than ever, there's still much we don't know about the science of depression. To better understand mental health – through rigorous, real-world measurement – the Project Baseline Mood Study is exploring how smartphone data could uncover more objective markers of depression.
Since the Patient Health Questionnaire (PHQ-9) survey became a standard diagnostic tool for depression in 1999, new technologies have unlocked a wealth of untapped data that could provide an even deeper understanding of mood. One of the largest studies of digital devices and mental health to date, the Mood Study will enroll thousands of participants to develop new ways of assessing mood disorders.
The study aims to gather real-world data in a simple and scalable way that blends seamlessly into daily life. Second-by-second, smartphones measure rich behavioral and environmental information that can indicate changes in depression. For instance, smartphones can detect ambient lighting changes and user behaviors that suggest the user is asleep. Significant shifts in sleep may be one indication of a change in an individual's mood disorder.
Along with simply using their smartphones, Mood Study participants will answer brief daily health surveys. The Mood Study will bring all these data together to generate scientific evidence that is clinically trustworthy and generalizable to real-world populations.
Today, measuring symptoms and treating depression still rely on traditional and subjective assessments — with varying rates of success. UC Berkeley researcher Stephan Lammel recently noted that depression treatment is “currently often based on guesswork. No one treatment works for everyone, and no one has objective data on how to differentiate the enormous variability of depression symptoms and subtypes.”
“When collected at scale and with user consent, information from smartphones has the potential to power objective insights into mental health,” says Menachem Fromer, mental health R&D lead at Verily. “This will require machine learning, a type of artificial intelligence in which computer systems can learn from data. Given enough data, these systems can begin to detect new patterns that are difficult to capture with standard clinical tools. By providing new measures of mental health, this process could fundamentally reshape how people and their physicians understand mood and manage mental health.”
“If we’re successful,” says Collin Walter, mental health product lead at Verily, “we envision that one day a person’s unique digital footprint could be used to recommend a personalized, data-driven care path that is most likely to work for that individual.”
To learn more about the Mood Study and its mission to advance mental health research, visit our website.