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- Creators: Buman, Matthew
- Creators: Department of Psychology
The transition from high school to college (TTC) is a critical period of change, the effects of which may be exacerbated for Latino students, who often face additional minority-specific stressors, such as ethnic/racial discrimination (ERD). Research has documented links between ERD and sleep outcomes in adolescents, but less is known regarding the longitudinal impacts of ERD experiences during unique risk periods (e.g., TTC). Further, despite the central role of family in Latino adolescents’ lives, less research has explored the protective role of family factors (e.g., familism, family support) in links between ERD and Latino students’ sleep health. Thus, this study examined: 1) longitudinal associations between peer- and adult-perpetrated ERD in high school and actigraphy-measured (e.g., duration, efficiency, midpoint) and subjective sleep (e.g., problems) during the first year of college among Latino adolescents, accounting for college ERD experiences, and 2) familism and family support as potential moderators of these associations. Participants were 209 Hispanic/Latino adolescents (Mage=18.10; 64.4% female; 84.7% Mexican descent; 67.9% first-generation students) assessed at two time points (i.e., last semester of high school and second semester of college). There were no longitudinal associations between high school ERD and college sleep. However, there were concurrent associations between ERD and sleep in college. Specifically, greater college peer- and adult-perpetrated ERD were associated with less duration and lower efficiency at the same time point. Further, more college adult-based ERD was additionally linked with greater sleep problems. There were no significant moderation findings; however, the interaction between high school adult-based ERD and family support predicting college sleep problems suggested that adolescents reporting low levels of adult ERD in conjunction with higher levels of family support had the fewest sleep problems. Study findings provide additional evidence that ERD from both adults and peers is associated with reduced sleep duration and quality among Latino college students and suggest that current cultural stressors may be particularly influential on sleep during major socio-contextual shifts. These findings can inform future programs (e.g., sleep interventions) that provide support for students experiencing race-based stressors, such as ERD, to promote Latino student health and well-being.
protocols, including within sleep-focused studies. This study seeks to address accuracy of
accelerometer data in detection of the beginnings and ends of sleep bouts in young adults with
polysomnography (PSG) corroboration. An existing algorithm used to differentiate valid/invalid wear
time and detect bouts of sleep has been modified with the goal of maximizing accuracy of sleep bout
detection. Methods: Three key decisions and thresholds of the algorithm have been modified with three
experimental values each being tested. The main experimental variable Sleepwindow controls the
amount of time before and after a determined bout of sleep that is searched for additional sedentary
time to incorporate and consider part of the same sleep bout. Results were compared to PSG and sleep
diary data for absolute agreement of sleep bout start time (START), end time (END) and time in bed
(TIB). Adjustments were made for outliers as well as sleep latency, snooze time, and the sum of both.
Results: Only adjustments made to a sleep window variable yielded altered results. Between a 5-, 15-,
and 30-minute window, a 15-minute window incurred the least error and most agreement to
comparisons for START, while a 5-minute window was best for END and TIB. Discussion: Contrary
to expectation, corrections for snooze, latency, and both did not substantially improve agreement to
PSG. Algorithm-derived estimates of START and END always fell after sleep diary and PSG both,
suggesting either participants’ sedentary behavior beginning and ends were at a delay from sleep and
wake times, or the algorithm estimates consistently later times than appropriate. The inclusion of a
sleep window variable yields substantial variety in results. A 15-minute window appears best at
determining START while a 5-minute window appears best for END and TIB. Further investigation on
the optimal window length per demographic and condition is required.