We all know that wearables can collect health-related data: steps taken, floors climbed, calories burned, hours slept, heart rate, and more. But how to assess a person’s mental health? Wearable devices can do the same, a new study finds.
Motion sensors in wearable devices worn or embedded in clothing take snapshots of a person’s daily activities and sync them to a mobile device or computer. Advances in mobile networks, high-speed data transmission, and tiny microprocessors have made wearable devices an integral part of many people’s everyday lives.
Resilience is a person’s ability to “bounce back,” or recover quickly, from hardship. It enables people to have the emotional fortitude to deal with trauma, adversity, and difficulty, and to maintain good mental health. In 2019, 1 in 8 people worldwide (970 million) lived with a mental disorder.
Researchers at the Icahn School of Medicine at Mount Sinai in New York applied machine learning models to data passively collected by wearable devices such as the Apple Watch to measure a person’s resilience and mental health. To their knowledge, this is the first study to do so.
“Wearable devices provide a means of continuously collecting information about an individual’s physical state,” said lead author Robert Hirten of the study. “Our results provide insights into the feasibility of assessing psychological traits from passively collected data.”
Not everyone has access to vital mental health services, which is why the researchers say their study is so important.
Zahi Fayad, one of the study’s co-authors, said: “Interviews vary widely across geographies and socioeconomic status, and the need for in-person assessments or completion of validated mental health surveys has further limited.” “There is a need for a better understanding of who is at psychological risk and improved methods for tracking the impact of psychological interventions. Developments in digital technology offer opportunities to improve access to mental health services for all.”
The researchers used data they collected during the Warrior Watch Study, which aims to help understand the impact of the pandemic on the mental health of hospital staff. The dataset contains 329 healthcare workers from seven hospitals in New York City.
Subjects wore an Apple Watch Series 4 or 5 during the study, which measured heart rate variability (the time between heartbeats) and resting heart rate. Heart rate variability represents the body’s physical response to stress. A baseline survey was conducted to assess resilience, optimism, and the level of emotional support provided by others.
Using machine learning algorithms to analyze the data, the researchers found that they could use heart rate variability to determine a person’s resilience and a combination of resilience, optimism and emotional support.
Although the Warrior Watch Study was not specifically designed to assess resilience, the researchers say their findings point to the need for further research in assessing mental health from passively collected wearable data.
“We hope this approach will allow us to provide psychological assessment and care to many more people who may not currently have access to it,” said study co-author Micol Zweig. “We also intend to evaluate this technique in other patient populations to further refine the algorithm and increase its applicability.”
The researchers plan to continue their research, using wearable device data to investigate a range of physical and psychological disorders.
The study was published in the journal Jamia Open.
source: Mount Sinai