Activity, light, and sleep data were collected using Actiwatch Spectrum Plus wrist activity monitors. Watches were programmed to collect data in 15-s epochs for 2 weeks (14 days), and students were instructed to press a marker button on the watch each time they went to sleep and woke up. Philips Actiware (version 6) software was used to construct actograms and determine sleep intervals. Activity and light data were exported and analyzed separately for mean waveforms using R Studio and Prism. Students also completed a daily retrospective online diary, which included questions about sleep onset, offset, how they were awakened, if they took any naps, if they removed the watch, and a place for text comments. Diary information was used in the data cleanup procedure (described below) to validate the sleep bouts automatically determined by Philips Actiware.

Chronotype, daytime sleepiness, and mood were measured by a one-time completion of the respective surveys located in the same portal as the daily diary. Chronotype was assessed using the Horne-Östberg Chronotype Questionnaire (10) and the Munich Chronotype Questionnaire (9). Daytime sleepiness was measured using the Epworth Sleepiness Scale. Mood was measured using the BDI-II. Students who scored higher than 20 on the BDI-II were contacted by their teacher and reminded about access to mental health resources.

Student demographics, including sex, race, birthdate, commute time to school, and mode of transportation, were collected via a paper demographic survey handed out in class. Students were also given the opportunity to disclose any sleep disorders and/or scheduled responsibilities (work, child care, etc.) that might affect the data. In addition, students from the 2017 cohort were asked to disclose any school activities that were scheduled for before school as a result of the delayed start times; the number of cases was small and was not considered separately in the statistics. Second semester grades for the students included in the sleep study were provided by the teachers whom we partnered with for this study. These represent absolute (not normalized) grades and could carry an implicit bias from teachers who could have been for or against the school time change. Last, global attendance data for each school were provided by Seattle Public Schools.

Data were collected over the course of 6 weeks during the Spring of 2016–2017 in 2-week rounds. Students from the first period participated in data collection for the first 2 weeks, second period for the following 2 weeks, and third or fourth period for the final 2 weeks. Students in each round were given the same instructions. The data were stripped of all identifying information upon collection. At the end of the semester, the data were returned to the students for an in-class learning exercise on research methods, data interpretation, and the relationship between sleep and their lifestyles.

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