In a new study, researchers found that people’s circle of friends could help predict their health conditions better than their fitness trackers.
They found the strength and structure of the circle of friends could tell a lot about people’s overall health and wellness.
The research was conducted by a team from the University of Notre Dame.
In the study, the team examined people who wore Fitbits to capture health behavior data, such as steps, sleep, heart rate, and activity level.
They then completed surveys and self-assessments about these people’s feelings of stress, happiness and positivity.
The team then analyzed and modeled the data using machine learning, alongside a person’s social network characteristics, such as connectivity, social balance, reciprocity and closeness within the social network.
They found a strong correlation between social network structures, heart rate, number of steps and level of activity.
Social network structure provided a big improvement in predicting one’s health and well-being compared to just looking at health data from the Fitbit alone.
The finding shows that without social network information, scientists can only have an incomplete view of an individual’s wellness state.
Social network information can help to predict health conditions and determine interventions.
The team hopes their finding can help develop new tools to help improve people’s health.
The findings could provide insight to employers who look to wearable fitness devices to incentivize employees to improve their health.
Those employers may benefit from encouraging employees to build a platform to post and share their experiences with each other.
The lead author of the study is Nitesh V. Chawla, Frank M. Freimann Professor of Computer Science and Engineering at Notre Dame.
The study is published in PLOS ONE.
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