Class Start Times,Sleep, and Academic Performance in College: A Path Analysis

Path analysis was used to examine the relationship between class start times, sleep, circadian preference, and academic performance in college-aged adults. Consistent with observations in middle and high school students, college students with later class start times slept longer, experienced less daytime sleepiness, and were less likely to miss class. Chronotype was an important moderator of sleep schedules and daytime functioning; those with morning preference went to bed and woke up earlier and functioned better throughout the day. The benefits of taking later classes did not extend to academic performance, however; grades were somewhat lower in students with predominantly late class schedules. Furthermore, students taking later classes were at greater risk for increased alcohol consumption, and among all the factors affecting academic performance, alcohol misuse exerted the strongest effect. Thus, these results indicate that later class start times in college, while allowing for more sleep, also increase the likelihood of alcohol misuse, ultimately impeding academic success. (Author correspondence: sonyper@stlawu.edu)     

Sleep length,working hours and socio-demographic variables are associated with time attending evening classes among working college students

It is the aim of the present study to assess factors associated with time spent in class among working college students. Eighty-two working students from 21 to 26 years old participated in this study. They were enrolled in an evening course of the University of São Paulo, Brazil. Participants answered a questionnaire on living and working conditions. During seven consecutive days, they wore an actigraph, filled out daily activity diaries (including time spent in classes) and the Karolinska Sleepiness Scale every three hours from waking until bedtime. Linear regression analyses were performed in order to assess the variables associated with time spent in classes. The results showed that gender, sleep length, excessive sleepiness, alcoholic beverage consumption (during workdays) and working hours were associated factors with time spent in class. Thus, those who spent less time in class were males, slept longer hours, reported excessive sleepiness on Saturdays, worked longer hours, and reported alcohol consumption. The combined effects of long work hours (>40 h/week) and reduced sleep length may affect lifestyles and academic performance. Future studies should aim to look at adverse health effects induced by reduced sleep duration, even among working students who spent more time attending evening classes.

     

The Relationships between Sleep-Wake Cycle and Academic Performance in Medical Students

Survey and laboratory studies suggest that several factors, such as social and academic demands, part-time jobs and irregular school schedules, affect the sleep-wake cycle of college students. In this study, we examined the sleep-wake pattern and the role played by academic schedules and individual characteristics on the sleep-wake cycle and academic performance. The subjects were 36 medical students (male = 21 and female = 15), mean age = 20.7 years, SD = 2.2. All students attended the same school schedule, from Monday to Friday. The volunteers answered a morningness-eveningness questionnaire, the Pittsburgh Sleep Quality Index (PSQI) and kept a sleep-wake diary for two weeks. The relationships between sleep-wake cycle, PSQI, chronotypes and academic performance were analyzed by a multiple regression technique. The results showed that 38.9% of the students had a poor sleep quality according to the PSQI. When the medical students were evening type or moderate evening type the PSQI showed a tendency of poor sleep. The multiple regression analysis showed a correlation between sleep onset, sleep irregularity and sleep length with academic performance. These results suggest that chronotypes influence the quality of the sleep-wake cycle and that irregularity of the sleep-wake cycle, as well as sleep deprivation (average length was 6:52), influence the learning of college students.     

The Relationships between Sleep-Wake Cycle and Academic Performance in Medical Students

Survey and laboratory studies suggest that several factors, such as social and academic demands, part-time jobs and irregular school schedules, affect the sleep-wake cycle of college students. In this study, we examined the sleep-wake pattern and the role played by academic schedules and individual characteristics on the sleep-wake cycle and academic performance. The subjects were 36 medical students (male = 21 and female = 15), mean age = 20.7 years, SD = 2.2. All students attended the same school schedule, from Monday to Friday. The volunteers answered a morningness-eveningness questionnaire, the Pittsburgh Sleep Quality Index (PSQI) and kept a sleep-wake diary for two weeks. The relationships between sleep-wake cycle, PSQI, chronotypes and academic performance were analyzed by a multiple regression technique. The results showed that 38.9% of the students had a poor sleep quality according to the PSQI. When the medical students were evening type or moderate evening type the PSQI showed a tendency of poor sleep. The multiple regression analysis showed a correlation between sleep onset, sleep irregularity and sleep length with academic performance. These results suggest that chronotypes influence the quality of the sleep-wake cycle and that irregularity of the sleep-wake cycle, as well as sleep deprivation (average length was 6:52), influence the learning of college students.     

Eveningness,Sleep Patterns,Daytime Functioning,and Quality of Life in Israeli Adolescents

The purpose of the study was to assess the relationships between eveningness, sleep patterns, measures of daytime functioning, i.e., sleepiness, sleep problem behaviors, and depressed mood, and quality of life (QOL) in young Israeli adolescents. A cross-sectional survey was performed in urban and rural middle schools in Northern Israel. Participants were 470 eighth and ninth grade middle school students (14?±?0.8 yrs of age) in the normative school system. Students completed the modified School Sleep Habits Survey (SSHS) and Pediatric Quality of Life Inventory Short Form, assessing six subscales of physical, emotional, social, school performance, and psychosocial functioning, plus an addition generated total score. During weekdays and weekends, evening types went to bed later, their sleep latency was longer, their wake-up time was later, and their sleep duration was shorter than intermediate and morning types. Evening types exhibited more sleep problem behaviors, sleepiness, depressed mood, and lower QOL compared to intermediate and morning types. Based on the regression model, sleepiness, sleep-problem behaviors, and depressed mood were the variables most strongly associated with QOL, followed by morning-evening preference, weekday sleep duration, and weekend sleep latency. This study is the first to assess QOL in normative, healthy adolescents and to demonstrate strong associations between morning-evening preference and QOL. These findings enhance the need to identify young individuals with an evening preference, and to be aware of the characteristics and manifestations of the evening chronotype on daytime and nighttime behaviors in adolescence. (Author correspondence: Orna@yvc.ac.il)     

Fatigue and mood correlates of sleep length in three age-social groups: School children, students, and employees

The aim of the study was to trace the consequences of insufficient sleep, in terms of chronic sleep reduction rather than acute sleep deprivation, on fatigue, mood, cognitive performance self-estimations, and daytime sleepiness in different age-social groups. The age group of the subjects reflects their social situation and their working time organization: adolescents (n = 191) obeyed the strict school schedules with starting times often before 08:00 h; university students (n = 115) had more flexible timetables; young employees (n = 126) were engaged in regular morning schedules or irregular daytime hours or day and night shifts. A questionnaire study determined the declared need of sleep, self-reported sleep length, chronic fatigue (using a scale comprised of eight fatigue symptoms and four mood and three cognitive items), and daytime sleepiness (Epworth Sleepiness Scale). The declared need for sleep decreased in subsequent age groups from 9 h 23 min in school children to 8 h 22 min in university students and to 7 h 37 min in young employees. Consequently, the discrepancy between preferred and real sleep length (sleep deficit) was the largest in adolescents: 106 min. Females showed a greater need of sleep than males (p = .025) and significantly more fatigue, mood, and cognitive problems; they also exhibited higher level of daytime sleepiness (p < .000). The sleep index (reported sleep length related to requirements) correlated significantly with all health issues in women (p < .000), while only with fatigue symptoms in men (p = .013). Actual sleep length was unrelated to mood and fatigue issues; the declared individual need of sleep and sleep index showed significant associations, especially in the group of adolescents. The most frequent complaints of adolescents included tiredness on awakening (46%), nervousness, and general weakness; university students reported excessive drowsiness (50%), tension, and nervousness; employees suffered mostly from negative moods, such as tension (49%), nervousness, and irritability. The findings of the study indicate that chronic sleep loss seems to affect females more severely than males. The associations of fatigue and mood with sleep need and sleep index were more pronounced in younger subjects. Surprisingly, fatigue symptoms in school children and university students were as frequent as in hard-working adults. Because the problem of insufficient sleep is already present in youngsters, their work time organization needs more attention.     

Eveningness, sleep patterns, daytime functioning, and quality of life in Israeli adolescents

The purpose of the study was to assess the relationships between eveningness, sleep patterns, measures of daytime functioning, i.e., sleepiness, sleep problem behaviors, and depressed mood, and quality of life (QOL) in young Israeli adolescents. A cross-sectional survey was performed in urban and rural middle schools in Northern Israel. Participants were 470 eighth and ninth grade middle school students (14?±?0.8 yrs of age) in the normative school system. Students completed the modified School Sleep Habits Survey (SSHS) and Pediatric Quality of Life Inventory Short Form, assessing six subscales of physical, emotional, social, school performance, and psychosocial functioning, plus an addition generated total score. During weekdays and weekends, evening types went to bed later, their sleep latency was longer, their wake-up time was later, and their sleep duration was shorter than intermediate and morning types. Evening types exhibited more sleep problem behaviors, sleepiness, depressed mood, and lower QOL compared to intermediate and morning types. Based on the regression model, sleepiness, sleep-problem behaviors, and depressed mood were the variables most strongly associated with QOL, followed by morning-evening preference, weekday sleep duration, and weekend sleep latency. This study is the first to assess QOL in normative, healthy adolescents and to demonstrate strong associations between morning-evening preference and QOL. These findings enhance the need to identify young individuals with an evening preference, and to be aware of the characteristics and manifestations of the evening chronotype on daytime and nighttime behaviors in adolescence.     

Sleep and academic performance in undergraduates: a multi-measure, multi-predictor approach

The present study examined the associations of sleep patterns with multiple measures of academic achievement of undergraduate university students and tested whether sleep variables emerged as significant predictors of subsequent academic performance when other potential predictors, such as class attendance, time devoted to study, and substance use are considered. A sample of 1654 (55% female) full-time undergraduates 17 to 25 yrs of age responded to a self-response questionnaire on sleep, academics, lifestyle, and well-being that was administered at the middle of the semester. In addition to self-reported measures of academic performance, a final grade for each student was collected at the end of the semester. Univariate analyses found that sleep phase, morningness/eveningness preference, sleep deprivation, sleep quality, and sleep irregularity were significantly associated with at least two academic performance measures. Among 15 potential predictors, stepwise multiple regression analysis identified 5 significant predictors of end-of-semester marks: previous academic achievement, class attendance, sufficient sleep, night outings, and sleep quality (R(2)=0.14 and adjusted R(2)=0.14, F(5, 1234)= 40.99, p < .0001). Associations between academic achievement and the remaining sleep variables as well as the academic, well-being, and lifestyle variables lost significance in stepwise regression. Together with class attendance, night outings, and previous academic achievement, self-reported sleep quality and self-reported frequency of sufficient sleep were among the main predictors of academic performance, adding an independent and significant contribution, regardless of academic variables and lifestyles of the students.     

Circadian Phase Preference in College Students: Relationships With Psychological Functioning and Academics

The current study offers a comprehensive assessment of psychosocial functioning and academic performance in relation to circadian phase preference in a US sample of undergraduate college students (N?=?838), aged 17–26 (M?=?19.78, SD?=?1.89). Women had greater morning preference than men, and seniors had greater morning preference than freshmen. Circadian phase preference, fatigue, perceived stress, depression, anxiety, and substance use were assessed cross-sectionally and grade point average (GPA) was assessed prospectively. Evening phase preference was related to higher levels of fatigue, alcohol and caffeine use, and worse academic performance than morning or intermediate phase preferences. (Author correspondence: djtaylor@unt.edu)     

Prevalence of sleep disorders and their impact on academic performance in medical students/University of Duhok

Full-time students experiencing high levels of stress due to a high bulk of teaching materials and academic performance demands are the most susceptible population class for different types of sleep disorders. The current study examined the prevalence of sleep disorders and their impacts on academic performance of a random sample of medical college students. In this regard, a random sample of 316 medical students of a large public university in Iraq participated in a cross-sectional study. The participants completed the SLEEP-50 self-reported questionnaire and questions about socio-demographic factors. The variables set included sleep apnea, insomnia, narcolepsy, restless legs syndrome, circadian rhythm sleep disorder, sleepwalking, nightmares, grade point average, and some socio-demographic characteristics. The study showed that to some extent, the students suffer from different types of sleep disorders with no substantial difference between males and females. Students with worse level of sleep disorders had a lower grade point average compared with those with normal sleep patterns (p = 0.001). The study confirmed that students with sleep disorders had poorer academic performance at college.

     

Sleep-Wake Patterns of Student Workers and Non-Workers

Adolescents usually exhibit late sleep phase and irregular sleep patterns. As a result, they do not get enough sleep and report daytime sleepiness. This condition could be aggravated in working students who have a more limited time for sleep. In this survey, we investigated the impact of evening classes and employment on the sleep patterns of adolescents. We compared female (n = 17) and male (n = 14) non-worker students to female (n = 28) and male (n = 20) worker students who attended the same high school. The volunteers (aged 17.4 years ± 11 months) answered a sleep log during a 16-day period. Worker students slept and woke up earlier, had a shorter nocturnal sleep length and a shorter daily (nocturnal plus diurnal) sleep length compared to non-working pupils. The four groups of students delayed sleep onset time on weekends, but only worker students delayed wake-up time on Sundays. The wake-up time was similar among groups on Sundays. While student workers tended to increase the sleep length in the weekends, non-working students increased it on Mondays and/or Tuesdays. The results showed that sleep schedules and sleep length were different according to the work status. Going to bed later on Saturday by the four groups of students suggests the influence of social activities, while a later wake-up time on Sundays could result from a shorter sleep length on workdays.     

Circadian phase preference in college students: relationships with psychological functioning and academics

The current study offers a comprehensive assessment of psychosocial functioning and academic performance in relation to circadian phase preference in a US sample of undergraduate college students (N?=?838), aged 17-26 (M?=?19.78, SD?=?1.89). Women had greater morning preference than men, and seniors had greater morning preference than freshmen. Circadian phase preference, fatigue, perceived stress, depression, anxiety, and substance use were assessed cross-sectionally and grade point average (GPA) was assessed prospectively. Evening phase preference was related to higher levels of fatigue, alcohol and caffeine use, and worse academic performance than morning or intermediate phase preferences.     

Sleep and Academic Performance in Undergraduates: A Multi-measure,Multi-predictor Approach

The present study examined the associations of sleep patterns with multiple measures of academic achievement of undergraduate university students and tested whether sleep variables emerged as significant predictors of subsequent academic performance when other potential predictors, such as class attendance, time devoted to study, and substance use are considered. A sample of 1654 (55% female) full-time undergraduates 17 to 25 yrs of age responded to a self-response questionnaire on sleep, academics, lifestyle, and well-being that was administered at the middle of the semester. In addition to self-reported measures of academic performance, a final grade for each student was collected at the end of the semester. Univariate analyses found that sleep phase, morningness/eveningness preference, sleep deprivation, sleep quality, and sleep irregularity were significantly associated with at least two academic performance measures. Among 15 potential predictors, stepwise multiple regression analysis identified 5 significant predictors of end-of-semester marks: previous academic achievement, class attendance, sufficient sleep, night outings, and sleep quality (R²?=?0.14 and adjusted R²?=?0.14, F(5, 1234)?=?40.99, p?<?.0001). Associations between academic achievement and the remaining sleep variables as well as the academic, well-being, and lifestyle variables lost significance in stepwise regression. Together with class attendance, night outings, and previous academic achievement, self-reported sleep quality and self-reported frequency of sufficient sleep were among the main predictors of academic performance, adding an independent and significant contribution, regardless of academic variables and lifestyles of the students. (Author correspondence: ana.allen@ua.pt)     

Social jetlag negatively correlates with academic performance in undergraduates

Discrepancies between sleep timing on workdays and weekends, also known as social jetlag (SJL), affect the majority of the population and have been found to be associated with increased health risk and health-impairing behaviors. In this study, we explored the relationship between SJL and academic performance in a sample of undergraduates of the Semmelweis University. We assessed SJL and other sleep-related parameters with the Munich ChronoType Questionnaire (MCTQ) (n?=?753). Academic performance was measured by the average grade based on weekly test results as well as scores acquired on the final test (n?=?247). The average mid-sleep point on free days in the Hungarian sample fits well the regression line plotted for longitudes within the Central European Time Zone and chronotypes, confirming that sunlight has a major impact on chronotype. Multivariate analysis showed negative effect of SJL on the weekly average grade (p?=?0.028, n?=?247) during the lecture term with its highly regular teaching schedules, while this association disappeared in the exam period (p?=?0.871, n?=?247) when students had no scheduled obligations (lower SJL). We also analyzed the relationship between the time of the weekly tests and academic performance and found that students with later sleep times on free days achieved worse in the morning (p?=?0.017, n?=?129), while the inverse tendency was observed for the afternoon test-takers (p?=?0.10, n?=?118). We did not find significant association between academic performance and sleep duration or sleep debt on work days. Our data suggest that circadian misalignment can have a significant negative effect on academic performance. One possible reason for this misalignment is socially enforced sleep times.     

Chronotype and the Transition to College Life

Social synchronizers of morningness-eveningness, or chronotype, begin to change during the developmental transition from adolescence to college life. The current study examined how these changes related to the sleep/wake patterns of 220 undergraduates (93 males/122 females) ranging in age from 18 to 29 yrs at a private university. Coping strategies students used to deal with early morning commitments and familial conflict over sleep patterns were also examined. Results revealed that evening chronotypes were more likely to report conflict with parents in junior high school and high school over going to bed and waking, followed by a shift to a later sleep/wake pattern in college. They also reported adjusting their schedules and using more coping strategies to accommodate their evening bias. Morning chronotypes, whose routines easily fit a conventional morning schedule, reported little change in schedules and sleep patterns from junior high school to college, and used fewer coping strategies in response to early morning commitments. The shift in social zeitgebers from junior high school to college are significant, and yet little research has examined the effect these changes can have on students' adjustment to college life and the role that chronotype plays in this process. Because students' ability to cope with these changes will ultimately influence how successful they are in their various endeavors, a greater understanding of how chronotype is related to adaptive functioning across this developmental period is needed. (Author correspondence: lzimmerm@su.edu)     

Fatigue and Mood Correlates of Sleep Length in Three Age‐Social Groups: School Children,Students, and Employees

The aim of the study was to trace the consequences of insufficient sleep, in terms of chronic sleep reduction rather than acute sleep deprivation, on fatigue, mood, cognitive performance self‐estimations, and daytime sleepiness in different age‐social groups. The age group of the subjects reflects their social situation and their working time organization: adolescents (n=191) obeyed the strict school schedules with starting times often before 08:00 h; university students (n=115) had more flexible timetables; young employees (n=126) were engaged in regular morning schedules or irregular daytime hours or day and night shifts. A questionnaire study determined the declared need of sleep, self‐reported sleep length, chronic fatigue (using a scale comprised of eight fatigue symptoms and four mood and three cognitive items), and daytime sleepiness (Epworth Sleepiness Scale). The declared need for sleep decreased in subsequent age groups from 9 h 23 min in school children to 8 h 22 min in university students and to 7 h 37 min in young employees. Consequently, the discrepancy between preferred and real sleep length (sleep deficit) was the largest in adolescents: 106 min. Females showed a greater need of sleep than males (p=.025) and significantly more fatigue, mood, and cognitive problems; they also exhibited higher level of daytime sleepiness (p<.000). The sleep index (reported sleep length related to requirements) correlated significantly with all health issues in women (p<.000), while only with fatigue symptoms in men (p=.013). Actual sleep length was unrelated to mood and fatigue issues; the declared individual need of sleep and sleep index showed significant associations, especially in the group of adolescents. The most frequent complaints of adolescents included tiredness on awakening (46%), nervousness, and general weakness; university students reported excessive drowsiness (50%), tension, and nervousness; employees suffered mostly from negative moods, such as tension (49%), nervousness, and irritability. The findings of the study indicate that chronic sleep loss seems to affect females more severely than males. The associations of fatigue and mood with sleep need and sleep index were more pronounced in younger subjects. Surprisingly, fatigue symptoms in school children and university students were as frequent as in hard‐working adults. Because the problem of insufficient sleep is already present in youngsters, their work time organization needs more attention.     

Differences in circadian phase and weekday/weekend sleep patterns in a sample of middle-aged morning types and evening types

Factors contributing to sleep timing and sleep restriction in daily life include chronotype and less flexibility in times available for sleep on scheduled days versus free days. There is some evidence that these two factors interact, with morning types and evening types reporting similar sleep need, but evening types being more likely to accumulate a sleep debt during the week and to have greater sleep extension on weekend nights. The aim of the present study was to evaluate the independent contributions of circadian phase and weekend-to-weekday variability to sleep timing in daily life. The study included 14 morning types and 14 evening types recruited from a community-based sample of New Zealand adults (mean age 41.1 ± 4.7 years). On days 1–15, the participants followed their usual routines in their own homes and daily sleep start, midpoint and end times were determined by actigraphy and sleep diaries. Days 16–17 involved a 17 h modified constant routine protocol in the laboratory (17:00 to 10:00, <20 lux) with half-hourly saliva samples assayed for melatonin. Mixed model ANCOVAs for repeated measures were used to investigate the independent relationships between sleep start and end times (separate models) and age (30–39 years versus 40–49 years), circadian phase [time of the dim light melatonin onset (DLMO)] and weekday/weekend schedules (Sunday–Thursday nights versus Friday–Saturday nights). As expected on weekdays, evening types had later sleep start times (mean = 23:47 versus 22:37, p < .0001) and end times (mean = 07:14 versus 05:56, p < .0001) than morning types. Similarly on weekend days, evening types had later sleep start times (mean = 00:14 versus 23:07, p = .0032) and end times (mean = 08:56 versus 07:04, p < .0001) than morning types. Evening types also had later DLMO (22:06 versus 20:46, p = .0002) than morning types (mean difference = 80.4 min, SE = 18.6 min). The ANCOVA models found that later sleep start times were associated with later DLMO (p = .0172) and weekend-to-weekday sleep timing variability (p < .0001), after controlling for age, while later sleep end times were associated with later DLMO (p = .0038), younger age (p = .0190) and weekend days (p < .0001). Sleep end times showed stronger association with DLMO (for every 30 min delay in DLMO, estimated mean sleep end time occurred 14.0 min later versus 10.19 min later for sleep start times). Sleep end times also showed greater delays on weekends versus weekdays (estimated mean delay for sleep end time = 84 min, for sleep start time = 28 min). Comparing morning types and evening types, the estimated contributions of the DLMO to the mean observed differences in sleep timing were on weekdays, 39% for sleep start times and 49% for sleep end times; and on weekends, 41% for sleep start times and 34% of sleep end times. We conclude that differences in sleep timing between morning types and evening types were much greater than would be predicted on the basis of the independent contribution of the difference in DLMO on both weekdays and weekend days. The timing of sleep in daily life involves complex interactions between physiological and psychosocial factors, which may be moderated by age in adults aged 30–49 years.     

The self-morningness/eveningness (Self-ME): An extremely concise and totally subjective assessment of diurnal preference

The assessment of diurnal preference, or the preferred timing of sleep and activity, is generally based on comprehensive questionnaires such as the Horne–Östberg (HÖ). The aim of the present study was to assess the reliability of a subject’s self-classification as extremely morning (Self-MM), more morning than evening (Self-M), more evening than morning (Self-E) or extremely evening (Self-EE) type, based on the last question of the HÖ (Self-ME). A convenience sample of 461 subjects [23.8?±?4.7 years; 322 females] completed a full sleep–wake assessment, including diurnal preference (HÖ), night sleep quality (Pittsburgh Sleep Quality Index, PSQI), daytime sleepiness (Karolinska Sleepiness Scale, KSS), and habitual sleep–wake timing (12?d sleep diaries; n?=?296). Significant differences in HÖ total score were observed between Self-ME classes, with each class being significantly different from neighboring classes (p?<?0.0001). Significant differences in sleep–wake timing (bed time, try to sleep and sleep onset, wake up, and get up time) were observed between Self-ME classes. Such differences were maintained when sleep–wake habits were analysed separately on work and free days, and also in a smaller group of 67 subjects who completed the Self-ME as a stand-alone rather than as part of the original questionnaire. Significant differences were observed in the time-course of subjective sleepiness by Self-ME class in both the large and the small group, with Self-MM and Self-M subjects being significantly more alert in the morning and sleepier in the evening hours compared with their Self-E and Self-EE counterparts. Finally, significant differences were observed in night sleep quality between Self-ME classes, with Self-EE/Self-E subjects sleeping worse than their Self-MM/Self-M counterparts, and averaging just over the abnormality PSQI threshold of 5. In conclusion, young, healthy adults can define their diurnal preference based on a single question (Self-ME) in a way that reflects their sleep–wake timing, their sleepiness levels over the daytime hours, and their night sleep quality. Validation of the Self-ME across the decades and in diseased populations seems worthy.