DSI postdoctoral fellow Sandrine Müller makes use of smartphone sensor data to examine human habits.
A extensive research team led by Sandrine Müller, a Data Science Institute postdoctoral research fellow, and Heinrich Peters, a Columbia Business School (CBS) doctoral candidate, has linked mobility behavior to well-being by exploring associations between different types of mobility behaviors (e.g., time spent in transit, quantity of locations visited, and total distance covered) and lots of indicators of well-being (e.g., depression, loneliness, and stress).
Müller, Peters, and their co-authors, including Sandra Matz, David W. Zalaznick Associate Professor of Business at CBS; Wang Weichen, a Two Sigma quantitative researcher; and Gabriella Harari, an assistant professor of communication at Stanford University, published their findings in a unique issue on behavioral personality science in age big data of the European Journal of Personality.
To, Müller, Peters, et al., examined GPS and questionnaire data from 2,319 psychology students from the large university in the usa. In the beginning of the scholarly study, the researchers collected students’ reports of the general quantities of loneliness and depression. Additionally, students used their smartphones to answer questions about their anxiety, affect, stress, per day throughout the next a couple of weeks and energy four times.
One unique part of the research is that Global Positioning System (GPS) data were also collected during this period. The GPS data were transformed into several measures of mobility behaviors, of condensed into three broad kinds of mobility patterns: distance (behaviors associated with the distance an individual travelled), entropy (the distribution of time an individual spent in numerous places), and routine (the regularity of an individual’s mobility patterns).
“After linking these mobility patterns to participants’ well-being scores, we unearthed that mobility was linked to well-being on the daily level, along with on the known degree of an aggregate throughout the study period,” Müller said. “This demonstrates that mobility behavior isn’t only important for focusing on how people feel on a certain day, but may predict how they feel across longer also.”
Distance specifically associated with time spent in social places were linked to more positive well-being. Routine behaviors were associated with loneliness and depression. Taken together, these findings show that individuals’ mobility behavior may indeed be useful in predicting their well-being.
“While it wasn’t something our study was planning to do, I do believe it offers ideas for future studies on interventions and real-world applications definitely,” Müller said. “There’s possibility of learning individual patterns and showing that on the occasions where people visit certain places, they better feel. Giving them suggestions to test certain things, we could try to better cause them to become feel.”
Materials given by Data Science Institute at Columbia. Note: Content might be edited for style and length.
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