For this study, we gathered three potential sources for sleep onset and offset data. The first was the watch, which extrapolated sleep intervals from the raw data using Philips Actiware software. The second were the self-report online diaries that the students were assigned to fill out every day. The third were the time stamps students could add to their recordings by pressing a button on their watch. To validate the sleep intervals, as determined by the watch software, we followed the following protocol:

1) We inspected every single actogram day by day to detect false software calls for sleep onsets or offsets. These represent obvious mistakes that can be easily detected upon inspection (fig. S3).

2) We then looked for discrepancies between the diary, or event recorder, and software calls for sleep onsets or offsets that were larger than 1 hour.

3) For all the nights in which the discrepancy was larger than 1 hour, we inspected once again the actograms on those nights to determine whether the 1 hour error was due to a software error or a student error, entering the wrong time in the diary or with the event marker.

After inspection of the actograms in step 3, we determined that 19% of the discrepancies had already been detected in step 1. Of the remaining discrepancies, 77% were caused by student error in the diary or event marker and 19% by a watch error, and on 4%, we were unable to determine the cause. This means that the error of taking the actimeter calls for sleep onset and offset after step 1 is ≤5% and four times lower than the student-generated error, which was 19.5%.

Cleaned sleep data were broken up by onset, offset, duration, and efficiency for school and nonschool days. Sleep data were then exported and analyzed using Python and R Studio. Normality was tested by (i) visual inspection of distribution histograms, (ii) quantile/quantile plots, and (iii) through the Shapiro-Wilk test. None of the variables had normal distribution, and data on Fig. 1 were presented as medians ± quartiles. Differences in sleep onset, offset, and duration for both school and nonschool days were tested using Wilcoxon signed-rank tests with a Bonferroni correction for multiple comparisons. For each student, social jet lag was calculated as the difference between mean mid-sleep on the nonschool days (after subtracting oversleep) minus mean mid-sleep on the school days (22). For the Wilcoxon signed-rank tests, effect sizes were calculated by dividing the U statistic by the product of the Ns (23).

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