4.2 Article

Using Fitbit data to monitor the heart rate evolution patterns of college students

Journal

JOURNAL OF AMERICAN COLLEGE HEALTH
Volume 70, Issue 3, Pages 875-882

Publisher

ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/07448481.2020.1775610

Keywords

Heart rate; Latent Growth-Curve Model (LGCM); peer influence; social networks; sensor data

Funding

  1. National Institutes of Health [1 R01 HL117757-01A1]

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This study investigates the impact of social, psychological, personality, and behavioral factors on overtime heart rate changes in college students. The results show that heart rate levels are influenced by social contacts, social contexts, and other external factors. The conclusion is that human heart rate is not only a physiological phenomenon but also a social-psychological one.
Objective:To investigate what social, psychological, personality, and behavioral factors affect overtime heart rate changes of college students.Participants:The daily heart rates of over 600 undergraduates at the University of Notre Dame were unobtrusively recorded via Fitbit devices from August 16, 2015, to May 13, 2017.Method:Latent Growth-Curve modeling strategy is utilized to examine how daily mean heart rate and its standard deviation change over time, and what foregoing factors predict observed changes.Results:The mean heart rate increased and its standard deviation stayed the same over the 637 days. Heart rate levels go up with that of social contacts, an indicator of peer influence. Both daily heart rate levels and changes are also affected by multiple external factors.Conclusion:Human heart rate is not only a physiological phenomenon but also a social-psychological one, as it is systematically affected by peer networks, social contexts, and human activities.

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