Real-time Tracking Of Mood, Physical Activity, And Sleep Using Mobile Technology In College Freshmen

Mental health is influenced by many factors, including physical activity and sleep. The relationship between these factors in first-year college students is an ongoing research priority. Use of wearable technology and ecological momentary assessments (EMA) through digital platforms offers a means to objectively capture and assess these relationships with high temporal fidelity in real-time. PURPOSE: Examine relationships between EMA Mood scores, weekly step count, and weekly sleep minutes measured by wearable device over a first-year collegiate academic semester. METHODS: First-year college students were recruited as part of a larger study investigating use of digital and mobile technology to assess the effects of physical activity, sleep, and wellness on academic performance. This subset of participants (n = 75) was provided a wearable device and completed weekly mood surveys on a mobile app over a 12-week academic semester with greater than 75% compliance. Scores from a two-question mood survey (Fig A) reflecting frequency of depressive symptoms were averaged, with higher scores reflecting lower frequency of symptoms. Weekly average step count and sleep minutes preceding weekly mood score assessments were binned by mood score (0,0.5; 1,1.5; 2,2.5; 3). Effect of mood on step count and sleep minutes were assessed by one-way ANOVA followed by Tukey Post-Hoc testing. RESULTS: Average step counts (Fig B) were significantly greater in weeks with the highest mood score (3 points) compared to all other mood bins (0,0.5 p = 0.02; 1,1.5 p = 0.01; 2,2.5 p < 0.0001). Similarly, average nightly sleep minutes (Fig C) were significantly greater in highest (3) vs. lowest (0, 0.5) mood scores (p = 0.03). Subjects reporting a score of 3 averaged 30 minutes more sleep per night than those reporting a score of 0 or 0.5. CONCLUSIONS: The use of wearable technology and mobile data platforms allows for real-time assessment of associations between changes in mood, physical activity and sleep. University of Michigan Bioscience Initiative