The Dark Side of the Night Owl Life

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The Dark Side of the Night Owl Life somewhere between the two extremes and is The Dark Side of rather well-aligned with their activities. The discrepancy between biological the Night Owl Life rhythms and social timing that befalls larks and owls is known as social jetlag (SJL) Social jetlag causes “night owls” who follow (Wittman et al., 2006). For larks, who have “early bird” schedules to perform worse earlier bedtimes, this could mean having to academically. stay up later on weekends for social activities. For owls, who tend to sleep in on weekends, Cindy Zhou this could manifest itself as having to be up earlier on weekdays for work or school. Unlike the jetlag one might feel after taking a transoceanic flight, which is a temporary As class registration for the experience, SJL is permanent (Díaz-Morales upcoming semester rolls around, some of the & Escribano, 2015). Past studies have most common complaints are of early classes. correlated social jetlag with poor physical Are college students just lazy and love to and psychological functioning, including an sleep in? Or is there an underlying factor that increased risk of obesity, diabetes, depression, causes a large number of them to be so averse and reduced academic performance to earlier class start times? (Roenneberg et al., 2012; Parsons et al., 2015; This phenomenon can be explained Levandovski et al., 2016). The extensive list by the concept of chronotypes, which are the of adverse health outcomes related to SJL behavioral expressions of an individual's propels it forward as an emerging public circadian rhythm, often related to sleep and health concern. About a third of the activity patterns (Takahashi et al., 2018). population is victim to more than 2 hours of There are three main categories of SJL (Wittmann et al., 2006). In particular, chronotype: early (morningness), later chronotypes (owls) tend to have intermediate, and late (eveningness) disproportionately greater SJL (Wittmann et (Roenneberg et al., 2003). Morning types, al., 2006). Furthermore, because adolescents colloquially known as “larks,” tend to have and young adults are more likely than other an “early to bed, early to rise” schedule. age groups to be owls, researchers have been Previous studies have correlated larks with focusing on how SJL affects schooling in higher academic grades, which could be terms of learning deficits (Roenneberg et al., attributed to their achievement tendency, 2004). goal orientation, and aversion to time wasting A large study done by Smarr and (Enright & Refinetti, 2017). On the other end Schirmer in 2018 utilized 3.4 million of the spectrum are evening types, otherwise learning-management system logins at a known as “owls.” The biological clock of medium-sized public university in Illinois to owls causes them to naturally prefer staying assess how students’ academic performances up late and sleeping in. Previous studies have were affected by social jetlag. By using this correlated this chronotype with preexisting source of extensive, long-term procrastination, lower self-control, and sleep data from a large population that required no deprivation (Enright & Refinetti, 2017; extra effort from students, the researchers Giannotti et al., 2002). Intermediate types, or were able to perform a deep mining of “finches”, have a schedule that lies demographic patterns while sidestepping the extensive and time-consuming process that 1 Figure 1 | Chronotypes and login times. (A) Students with a delayed phase schedule (larks) have later logins on Class days compared to No Class days. (B) Students with a synchronized schedule (finches) had similar login times throughout the week. (C) Students with an advanced phase (owls) have earlier logins on Class days compared to No Class days. Adapted from Smarr & Schirmer (2018). would occur if they were to manually create median login time on class days was later, individual profiles for each student. similar to, and earlier than on non-class days, The login data were confirmed to respectively (Figure 1). 40.4% of the contain circadian information as it displayed population were synchronized (Smarr & a range of chronotypes. Non-class days Shirmer, 2018). Almost half (49.2%) of the represented a person’s natural profile, and subjects advanced their schedules on class class days represented the constrained days, while 10.4% delayed more than half an societal schedule caused by imposing SJL. hour (Smarr & Schirmer, 2018). SJL was The 14,894 subjects ranged from teenagers to quantified as the difference between the individuals in their 70s (median 25 years), average activity phase on days with and and like related studies, circadian phase was without class. found to advance with age in subsequent The data revealed that SJL was decades (Yoon et al., 2003). Preliminary negatively correlated with academic analysis also showed that men were found to performance as measured by GPA, a finding have later sleep times than women, which is supported by earlier research (Haraszti et al., in alignment with existing literature (Santhi 2013; Smarr, 2015). Assuming a linear et al., 2016). Lastly, seasonal changes were relationship, students with phase delays on also consistent with expectations: activity class days (larks) showed a slightly negative during fall semester days were concentrated but not significant trend in GPA, while those in the middle of the day, while spring with phase advances on class days (owls) semester days saw increased activity earlier were found to have significantly decreased and later in the day due to lengthening of the performance (Smarr & Schirmer, 2018), light phase (Brychta et al., 2016). Validation adding to the body of literature highlighting of these known biological interactions of age, the complications that night owls face. gender, and season underlined the robustness The authors speculated that larks of the data and its capacity to act as proxies would fare better in early classes and worse for biological information. in later classes, during which owls might In this study, students were prevail. Because the distribution of class categorized as having delayed (larks), times is skewed towards the morning hours, synchronized (finches), or advanced (owls) larks would still have an overall advantage. class day phases, which meant that their Analyses revealed that, surprisingly, all 2 chronotypes showed improvement in grades delay during school days, their schedules in throughout the day (Smarr & Schirmer, 2018). general are more lined up to the relatively Notably, larks and finches did better than early start times of standard school schedules. owls at all time points (Smarr & Schirmer, Logically, one might infer that owls would 2018). Finches did slightly better than larks perform better during later classes, but in the morning, indicating that those who had strikingly, this is not the case. This may be to delay their schedules on class days were explained to a certain extent by the also not immune to lower grades (Smarr & inconsistency of college schedules. Most Schirmer, 2018). However, when grades classes in university meet one to three times were normalized to account for the a week, which creates a form of schedule possibility of non-chronotype related effects, instability. This schedule change is drastic time of day no longer had a significant effect when compared to grade school, where (Figure 2) (Smarr & Schirmer, 2018). classes start and end at consistent times Contrary to the initial hypothesis, none of the throughout the week. The persistent chronotypes showed any pronounced variability in university schedules can further improvement or worsening of grades as the exacerbate an individual’s internal day went on. desynchrony, opposing any attempt at circadian realignment (Czeisler & Gooley, 2007). This paper by Smarr & Shirmer (2018) in particular is notable for its use of information mining on such a populous data set. It adds depth to the already robust body of research calling for schedule adjustments pertaining to class times. Similar conclusions have been drawn with participant populations across the globe, from nursing students in Korea to university students in Germany (Chang & Jang, 2018; Nowack & Van Der Meer, 2018). Future related studies should implement similar data collection techniques for different stages of education in order to Figure 2 | Owls are at a significant definitively parse out the root of the night owl disadvantage, performing worse academically at disadvantage. The combination of login data all times of day compared to larks and finches. analysis and wearable sensors for more Larks did worse than finches in morning classes reliable, direct biological outputs would be only. There is no effect of the time of day when especially useful. normalized across chronotypes. Adapted from Looking forward, there is a pressing Smarr & Schirmer (2018). need for strategies to reduce social jetlag. The issue has only been exacerbated by the Why do owls perform so much more widespread use of laptops and cellphones, as poorly? This deficit may be attributed to the these light-emitting devices may be shifting fact that it is more difficult to advance one’s people toward later chronotypes (Gamble et phase from “normal” than it is to delay al., 2014). Recent research has shown that (Smarr et al., 2014). Larks would therefore decreasing exposure to blue light at the end have an advantage compared to owls; even of the internal day is effective at advancing though they might need to perform a phase 3 sleep timing and the phase of entrainment References (Zerbini et al., 2018). However, this effect can vary between chronotypes, and further Alterman T, Luckhaupt SE, Dahlhamer JM, studies are needed to establish more robust Ward BW, Calvert GM (2013). results with longitudinal follow-ups. This is Prevalence rates of work organization necessary because young adults may not be characteristics among workers in the as sensitive as older adults when it comes U.S.: data from the 2010 National Health Interview Survey. American Journal of changing chronotype through light exposure Industrial Medicine 56:647-59.
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