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Want to be happier? Penn State is working on an app for that

Penn State’s Zita Oravecz, an assistant professor in the Department of Human Development and Family Studies and a co-hire of the Institute for CyberScience, and her colleagues are developing an app that can predict your psychological state using data from smartphones and wearable health monitors.
Penn State’s Zita Oravecz, an assistant professor in the Department of Human Development and Family Studies and a co-hire of the Institute for CyberScience, and her colleagues are developing an app that can predict your psychological state using data from smartphones and wearable health monitors. Photo provided

Editor’s note: The Focus on Research column highlights different research projects and topics being explored at Penn State. Each column will feature the work of a different researcher from across all disciplines.

Imagine a smartphone app that could learn to predict your emotional state, help you avoid stress and even make you a kinder person.

Penn State’s Zita Oravecz, an assistant professor in the Department of Human Development and Family Studies and a co-hire of the Institute for CyberScience, works to realize this vision. Oravecz and her colleagues are developing an app that can predict your psychological state using data from smartphones and wearable health monitors.

With this information, the app will send you texts to help improve your well-being. You might get a reminder to take a deep breath to fend off stress. Or you could receive an encouragement to pay someone a compliment, making both you and that person happier.

“So many people use smartphones nowadays,” said Oravecz. “Why not harness those devices to improve their mental health?”

CYBER-ENABLED PSYCHOLOGY

A major challenge is designing the app to learn how to predict the emotional states of different users. People vary in how they regulate emotions: some become stressed more easily than others or recover from stress quicker. For the app to be effective, it must adapt itself to these kinds of individual differences.

To create a predictive model of emotional states that learns a user’s quirks, Oravecz’s team uses data from a four-week study in which 52 participants received text messages at six random times each day. These messages directed the participants to a brief survey with questions about their daily activities and experiences, such as how pleasant they felt or how much they slept the previous night.

In addition to answering questions, participants wore FitBit-like health monitors. These devices gathered physiological data from their wearers, including anxiety-induced perspiration levels, skin temperature, heart rate and physical movement levels.

Oravecz combines this physiological data with the participants’ self-reports to build a mathematical model that can learn an individual’s unique predictors of well-being.

Because the model involves complex calculations and data, it requires powerful computers. To run the model, Oravecz uses the ICS Advanced CyberInfrastructure, Penn State’s high-performance computing system containing 23,000 computer cores. The initial tests to build the framework of the model might take weeks to run on a single-core desktop computer, but by using many ICS-ACI cores in parallel, Oravecz can speed up the development process and aim to make her algorithms work in real-time.

“We need to make predictions quickly,” Oravecz said. “It doesn’t help someone if they are approaching a period of high stress and we tell them two weeks later to take a deep breath. We’re investigating ways to make the model less computationally intensive, but we’ll still need to rely on high-performance computing to deliver timely analysis on a wide scale.”

COMPASSION AND COMPUTATION

The goal of the app is to reduce stress and increase positive behavior. The messages to calm down when approaching a high level of negative emotion, combined with reminders to act positively, can significantly improve psychological health.

“Random acts of kindness — and other positive behaviors — benefit both you and the recipient,” Oravecz said. “The reminders about acting kindly can increase users’ psychological well-being and help them flourish in their everyday lives.”

The desire to elevate people’s well-being through positive behavior has long motivated Oravecz. As a teenager, she noticed that many of her friends didn’t seem as happy as she was, even though they didn’t have any serious psychological problems. Her compassion for her friends’ unhappiness spurred her to study psychology.

In college, she also fell in love with math and statistics. She knew she could combine these passions with her drive to help others.

“I realized that not many people in my field get as excited about mathematical modeling and statistical programming as I do,” Oravecz said. “I think the field of psychology needs people with computational skills who also understand the human aspects of well-being. I love that I can use the power of computation to bring meaningful change to people’s lives.”

Oravecz wants to share her team’s model and methods with other researchers.

“I hope other researchers learn about our approach and apply it in new ways,” Oravecz said. “That way the impact of our work can extend beyond the app and ultimately benefit many more people.”

Julian Fung is a communications specialist at Penn State’s Institute for CyberScience.

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