2024-03-29T00:49:15
100068
Fri Mar 29 00:49:16 EDT 2024
Smarr student sleep timing logs
Benjamin Smarr
100068
https://doi.org/10.3886/E30744V2
2015-08-27
Stability of sleep and circadian rhythms are important for healthy learning and memory. While experimental manipulation of lifestyle and learning outcomes present major obstacles, the ongoing increase in data sources allows retrospective data mining of people’s sleep timing variation. Here I use digital sleep-log data generated by 1109 students in a biology lab course at the University of Washington to test the hypothesis that higher variance in time asleep and later sleep onset times negatively correlate with class performance, used here as a real-world proxy for learning and memory. I find that sleep duration variance and mean sleep onset times both significantly correlate with class performance. These correlations are strong on weeknights, but disappear on Friday and Saturday nights (“free nights”). These correlations also show large sex differences, with women showing substantially stronger (both larger and more powerful) negative correlations than men. Finally, though these data come with no demographic information beyond sex, the constructed demographic groups of “larks” and “owls” within the sexes reveal a significant decrease in performance of owls relative to larks in male students, whereas for the correlation of performance with sleep-onset time for all male students was only a near-significant trend. This provides a proof of concept that deeper demographic mining of digital logs in the future may identify subgroups for which certain sleep phenotypes have greater predictive value for performance outcomes. The data analyzed are validated by showing known patterns, including sleep-timing delays from weeknights to free-nights, and sleep-timing delays in men relative to women. These findings support the hypothesis that modern schedule impositions on sleep and circadian timing have consequences for real-world learning and memory. This study also highlights the low-cost, large-scale benefits of personal, daily, digital records as an augmentation of sleep and circadian studies.This work was unfunded.
college students
Seattle
9/1/2011 – 6/1/2012 (Academic year 2011-2012)