how sleep impacts college students cause and effect essay

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College students: getting enough sleep is vital to academic success

WESTCHESTER , Ill. — With the semester drawing to a close, millions of college students are preparing to take their final exams. Unfortunately, research is increasingly showing that more and more students are not getting enough sleep, which can have a negative impact on their grades. Among the reasons for these changes in sleeping patterns are increased part-time working hours, pulling all-nighters to finish a paper or cram for an exam, and watching television at bedtime. According to the American Academy of Sleep Medicine (AASM), the best way to maximize performance on final exams is to both study and get a good night of sleep.

Lawrence Epstein, MD, medical director of Sleep Health Centers in Brighton, Mass., an instructor of medicine at Harvard Medical School, a past president of the AASM and a member of the AASM board of directors, says that sleep deprivation effects not only whether a student can stay awake in class but how they perform as well.

“Recent studies have shown that adequate sleep is essential to feeling awake and alert, maintaining good health and working at peak performance,” says Dr. Epstein. “After two weeks of sleeping six hours or less a night, students feel as bad and perform as poorly as someone who has gone without sleep for 48 hours. New research also highlights the importance of sleep in learning and memory. Students getting adequate amounts of sleep performed better on memory and motor tasks than did students deprived of sleep.”

Clete A. Kushida, MD, PhD, associate professor in the department of psychiatry and behavioral sciences at Stanford University Medical Center, an attending physician at the Stanford Sleep Disorders Clinic, director of the Stanford University Center for Human Sleep Research and a member of the AASM board of directors, notes that the degree of daytime alertness is arguably the most sensitive measure as to how much sleep is necessary for the specific individual.

“If the individual is routinely tired or sleepy during the daytime, odds are that he or she is not getting enough sleep,” says Dr. Kushida. “To take it one step further, there are two primary factors that affect the degree of daytime alertness: sleep quantity and sleep quality. For the student-age population, sleep quantity and quality issues are both important. However, key factors affecting sleep quality, such as the major sleep disorders (e.g., obstructive sleep apnea and restless legs syndrome), are less prevalent in this age group compared to middle-aged or older individuals.”

Dr. Kushida adds that the importance of obtaining adequate sleep in the student-age population cannot be overemphasized.

“There are data that sleep loss leads to learning and memory impairment, as well as decreased attention and vigilance,” says Dr. Kushida. “In the student-age population, studies have found that factors such as self-reported shortened sleep time, erratic sleep/wake schedules, late bed and rise times, and poor sleep quality have been found to be negatively associated with school performance for adolescents from middle school through college. Thus, there is ample evidence to indicate that the lack of adequate nighttime sleep can lead to disturbances in brain function, which in turn, can lead to poor academic performance.”

Other recent studies outline the adverse effects of poor sleep among students with regards to their success in school:

• Sleepiness and poor sleep quality are prevalent among university students, affecting their academic performance and daytime functioning.
• Students with symptoms of sleep disorders are more likely to receive poor grades in classes such as math, reading and writing than peers without symptoms of sleep disorders.
• College students with insomnia have significantly more mental health problems than college students without insomnia.
• College students with medical-related majors are more likely to have poorer quality of sleep in comparison to those with a humanities major.
• College students who pull “all-nighters” are more likely to have a lower GPA.
• Students who stay up late on school nights and make up for it by sleeping late on weekends are more likely to perform poorly in the classroom. This is because, on weekends, they are waking up at a time that is later than their internal body clock expects. The fact that their clock must get used to a new routine may affect their ability to be awake early for school at the beginning of the week when they revert back to their new routine.

The following tips are provided by the AASM to help students learn how to get enough sleep:

Go to bed early

Students should go to bed early enough to have the opportunity for a full night of sleep. Adults need about seven to eight hours of sleep each night.

Get out of bed

If you have trouble falling asleep, get out of bed and do something relaxing until you feel sleepy.

Stay out of bed

Don’t study, read, watch TV or talk on the phone in bed. Only use your bed for sleep.

If you take a nap, then keep it brief. Nap for less than an hour and before 3 p.m.

Wake up on the weekend

It is best to go to bed and wake up at the same times on the weekend as you do during the schoolweek. If you missed out on a lot of sleep during the week, then you can try to catch up on the weekend. But sleeping in later on Saturdays and Sundays will make it very hard for you to wake up for classes on Monday morning.

Avoid caffeine

Avoid caffeine in the afternoon and at night. It stays in your system for hours and can make it hard for you to fall asleep.

Adjust the lights

Dim the lights in the evening and at night so your body knows it will soon be time to sleep. Let in the sunlight in the morning to boost your alertness.

Take some time to “wind down” before going to bed. Get away from the computer, turn off the TV and the cell phone, and relax quietly for 15 to 30 minutes.

Eat a little

Never eat a large meal right before bedtime. Enjoy a healthy snack or light dessert so you don’t go to bed hungry.

Those who believe they have a sleep disorder should consult with their primary care physician or a sleep specialist.

Sleep Education , a patient education website created by the AASM, provides information about various sleep disorders, the forms of treatment available, recent news on the topic of sleep, sleep studies that have been conducted and a listing of sleep facilities.

AASM is a professional membership organization dedicated to the advancement of sleep medicine and sleep-related research.

To arrange an interview with an AASM spokesperson, please contact [email protected] .

Updated Nov. 6, 2017

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Study: Better sleep habits lead to better college grades

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Two MIT professors have found a strong relationship between students’ grades and how much sleep they’re getting. What time students go to bed and the consistency of their sleep habits also make a big difference. And no, getting a good night’s sleep just before a big test is not good enough — it takes several nights in a row of good sleep to make a difference.

Those are among the conclusions from an experiment in which 100 students in an MIT engineering class were given Fitbits, the popular wrist-worn devices that track a person’s activity 24/7, in exchange for the researchers’ access to a semester’s worth of their activity data. The findings — some unsurprising, but some quite unexpected — are reported today in the journal Science of Learning in a paper by MIT postdoc Kana Okano, professors Jeffrey Grossman and John Gabrieli, and two others.

One of the surprises was that individuals who went to bed after some particular threshold time — for these students, that tended to be 2 a.m., but it varied from one person to another — tended to perform less well on their tests no matter how much total sleep they ended up getting.

The study didn’t start out as research on sleep at all. Instead, Grossman was trying to find a correlation between physical exercise and the academic performance of students in his class 3.091 (Introduction to Solid-State Chemistry). In addition to having 100 of the students wear Fitbits for the semester, he also enrolled about one-fourth of them in an intense fitness class in MIT’s Department of Athletics, Physical Education, and Recreation, with the help of assistant professors Carrie Moore and Matthew Breen, who created the class specifically for this study. The thinking was that there might be measurable differences in test performance between the two groups.

There wasn’t. Those without the fitness classes performed just as well as those who did take them. “What we found at the end of the day was zero correlation with fitness, which I must say was disappointing since I believed, and still believe, there is a tremendous positive impact of exercise on cognitive performance,” Grossman says.

He speculates that the intervals between the fitness program and the classes may have been too long to show an effect. But meanwhile, in the vast amount of data collected during the semester, some other correlations did become obvious. While the devices weren’t explicitly monitoring sleep, the Fitbit program’s proprietary algorithms did detect periods of sleep and changes in sleep quality, primarily based on lack of activity.

These correlations were not at all subtle, Grossman says. There was essentially a straight-line relationship between the average amount of sleep a student got and their grades on the 11 quizzes, three midterms, and final exam, with the grades ranging from A’s to C’s. “There’s lots of scatter, it’s a noisy plot, but it’s a straight line,” he says. The fact that there was a correlation between sleep and performance wasn’t surprising, but the extent of it was, he says. Of course, this correlation can’t absolutely prove that sleep was the determining factor in the students’ performance, as opposed to some other influence that might have affected both sleep and grades. But the results are a strong indication, Grossman says, that sleep “really, really matters.”

“Of course, we knew already that more sleep would be beneficial to classroom performance, from a number of previous studies that relied on subjective measures like self-report surveys,” Grossman says. “But in this study the benefits of sleep are correlated to performance in the context of a real-life college course, and driven by large amounts of objective data collection.”

The study also revealed no improvement in scores for those who made sure to get a good night’s sleep right before a big test. According to the data, “the night before doesn’t matter,” Grossman says. “We've heard the phrase ‘Get a good night’s sleep, you've got a big day tomorrow.’ It turns out this does not correlate at all with test performance. Instead, it’s the sleep you get during the days when learning is happening that matter most.”

Another surprising finding is that there appears to be a certain cutoff for bedtimes, such that going to bed later results in poorer performance, even if the total amount of sleep is the same. “When you go to bed matters,” Grossman says. “If you get a certain amount of sleep  — let’s say seven hours — no matter when you get that sleep, as long as it’s before certain times, say you go to bed at 10, or at 12, or at 1, your performance is the same. But if you go to bed after 2, your performance starts to go down even if you get the same seven hours. So, quantity isn’t everything.”

Quality of sleep also mattered, not just quantity. For example, those who got relatively consistent amounts of sleep each night did better than those who had greater variations from one night to the next, even if they ended up with the same average amount.

This research also helped to provide an explanation for something that Grossman says he had noticed and wondered about for years, which is that on average, the women in his class have consistently gotten better grades than the men. Now, he has a possible answer: The data show that the differences in quantity and quality of sleep can fully account for the differences in grades. “If we correct for sleep, men and women do the same in class. So sleep could be the explanation for the gender difference in our class,” he says.

More research will be needed to understand the reasons why women tend to have better sleep habits than men. “There are so many factors out there that it could be,” Grossman says. “I can envision a lot of exciting follow-on studies to try to understand this result more deeply.”

“The results of this study are very gratifying to me as a sleep researcher, but are terrifying to me as a parent,” says Robert Stickgold, a professor of psychiatry and director of the Center for Sleep and Cognition at Harvard Medical School, who was not connected with this study. He adds, “The overall course grades for students averaging six and a half hours of sleep were down 50 percent from other students who averaged just one hour more sleep. Similarly, those who had just a half-hour more night-to-night variation in their total sleep time had grades that dropped 45 percent below others with less variation. This is huge!”

Stickgold says “a full quarter of the variation in grades was explained by these sleep parameters (including bedtime). All students need to not only be aware of these results, but to understand their implication for success in college. I can’t help but believe the same is true for high school students.” But he adds one caution: “That said, correlation is not the same as causation. While I have no doubt that less and more variable sleep will hurt a student’s grades, it’s also possible that doing poorly in classes leads to less and more variable sleep, not the other way around, or that some third factor, such as ADHD, could independently lead to poorer grades and poorer sleep.”

The team also included technical assistant Jakub Kaezmarzyk and Harvard Business School researcher Neha Dave. The study was supported by MIT’s Department of Materials Science and Engineering, the Lubin Fund, and the MIT Integrated Learning Initiative.

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HealthDay reporter Steven Reinberg writes about an MIT study examining the impact of sleep on academic performance. Researchers found that “it's not just how many hours one sleeps that counts, but also the quality of the sleep, including regular sleep times,” Reinberg explains.

A study by MIT researchers underscores the importance of sleep consistency when it comes to academic performance, reports Jamie Ducharme for TIME . “If you can just get the same amount each night, compared to someone who averages the same amount as you but gets less consistent sleep, you’re going to do better,” says Prof. Jeff Grossman.

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UNIVERSITY OF SOUTH FLORIDA

Admit-a-bull // official admissions blog, the importance of sleep for college students.

By Joe Emerson | Last Updated: Jul 15, 2022

College is a matter of dreams and the academic and career aspirations born of those dreams. Sleep problems can turn those dreams into nightmares, causing physical and emotional problems that spiral out of control and land GPAs and hopes of graduating in the trash bin. That’s why the importance of sleep for college students can’t be overstated.

Sleep Deprivation and College Students

“Sleep deprivation” is a label for “the cumulative effect of a person not having sufficient sleep,” according to the American Sleep Association . The condition is common, with more than one-third of the U.S. population not getting enough sleep, according to the U.S. Centers for Disease Control and Prevention. For young adults, eight hours of sleep is thought to be the necessary daily minimum.

A National Institutes of Health report addresses the prevalence among college students of what it labels daytime sleepiness, “defined as the inability or difficulty in maintaining alertness during the major wake period of the day, resulting in unintended lapses into drowsiness or sleep.” The NIH report says:

• More than 70 percent of college students say they get less than eight hours of sleep a day.
• Sixty-percent of college students say they are “dragging, tired, or sleepy” at least three days a week.
• More than 80 percent of college students say loss of sleep negatively affects their academic performance.
• College students rank sleep problems as the No. 2 cause of difficulties with academic performance. Stress is No. 1.

Causes and Effects of College Students Losing Sleep

Quite literally, sleep deprivation is a major problem for college students.  The previously cited NIH study does a deep dive on the reasons why college students lose too much sleep, enough to result in sleep deprivation or daytime sleepiness. Beyond going to sleep too late and/or getting up too early, primary causes of sleep problems fall under these categories:

Inadequate Sleep Hygiene

Sleep hygiene is about behavior that hurts or helps a student get enough quality sleep. The term applies to smart scheduling of sleep time, a good sleep environment, use of caffeine and other stimulants, alcohol consumption, and activities before bedtime that negatively affect sleep.

Aspects of college life that negatively affect sleep hygiene include variable class schedules and sleeping patterns , late-night socializing, and early morning obligations.

Almost 12 percent of students who drink say they use alcohol to help them sleep. It does help them get to sleep, but it fragments the second half of the downtime. It also can cause obstructive sleep apnea, a sleep disorder.

Caffeine and Energy Drinks

The effects of caffeine can last for more than seven hours, making it harder to fall asleep and stay asleep. Caffeine can be found in many drinks, such as coffee, certain teas, energy drinks, and some sodas.

Caffeine is a primary ingredient of energy drinks. NIH notes that the use of energy drinks “is associated with higher use of alcohol and possibly other drugs, including stimulants.”

College students are more likely than others in their age group to use prescription and nonprescription stimulants. Those who use stimulants are more likely to have trouble falling asleep, are less likely to report deep, restorative sleep, and often report an increase in the use of alcohol and illegal drugs.

Keeping the digital world out of your sleep space is the focus here. Studies find that:

• Having a cell phone in your sleeping space can increase daytime sleepiness, reduce the quality of sleep, make it harder to fall asleep and stay asleep, and result in you waking up throughout the night.
• Using a computer before bedtime makes it more likely you will experience drowsy driving, daytime sleepiness, and less restful sleep.
• Playing video games before bedtime makes it harder to fall asleep.

It’s not all about the noise, either. Electronic devices emit light, and exposure to light can reduce the body’s production of melatonin, a natural sleep aid.

Sleep Disorders

Not all hindrances to restorative sleep and productive wakefulness are self-inflicted. Sleep disorders range from obstructive sleep apnea to insomnia , restless legs syndrome , circadian rhythm sleep disorders , and hypersomnia .

The All-Nighter

The all-nighter isn’t a category in the NIH string of causes of sleep deprivation, but the typically forced marathon of studying is addressed , and it appears to have a real downside. Testing indicates that “all-night study sessions are the wrong plan for improved grades and learning.” When you study all night, your body and mind don’t get to recharge. This makes it harder for your brain to recall the facts you studied and makes it harder for you to stay focused during your test.

Plan ahead, so you can study the material multiple times in manageable sections.

Symptoms of Sleep Deprivation

You’re slogging through another semester with too much to do and too little sleep. Aside from constant yawning and sleepiness, fatigue, and irritability, the signs of sleep deprivation can include:

• Memory issues (that obviously affect learning)
• Mood swings
• Weakened immune system
• Higher risk of diabetes
• Decreased balance
• Increased risk of high blood pressure and heart disease
• Increased hunger and weight gain
• Greater risk of accidents
• Trouble concentrating

Common Sense Solutions to College Student Sleep Woes

Beyond the professional assistance available to people with mental and physical problems that affect sleep, there are simple steps you can take to overcome obstacles in getting adequate restorative slumber:

• Keep the electronics out of your sleep space
• Build decompression time into your schedule. Have downtime before bedtime that involves minimal activity, including studies.
• Stay away from caffeine and other stimulants for at least six hours before bedtime.
• Make your bedroom a safe space for sleeping , not studying, playing video games, or chatting (in any form) on your cell phone.
• Use earplugs and an eye cover to minimize noise and light.
• Avoid napping during the day.
• Skip the booze before bed.
• Try to follow a regular bedtime schedule , and follow it on weekends, too.
• Don’t exercise before bedtime. Exercise a few hours before you’re getting ready for sleep.

Use Your School’s Resources

Emotional well-being is a foundation for good sleep habits, and resources for achieving it are a staple of campus life at USF.

The professional medical and psychological support system isn’t all that’s available through Health and Wellness, USF . Relaxation Zone offerings include massage chairs, sleep pods, and sleep packs that feature earplugs, soothing teas, eye masks, and tips on avoiding sleep deprivation.

And if you’re losing sleep over admission issues, the USF Office of Admissions is always ready to answer questions about becoming and being a Bull, so contact us online or by phone at 813-974-3350 .

About Joe Emerson

Joe Emerson spent 30 years as a magazine and newspaper reporter, editor and copyeditor who turned to freelancing after 20 years with The Tampa Tribune, which closed in 2016 after 125 years of serving the Tampa Bay area. Writing and delivering valuable information remain his passion.

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Home > The Review > Vol. 23 (2022)

Article Title

Sleepless in College Town: Causes and Effects of Poor Sleep in College Students

Isabella E. Pandolfo , St. John Fisher University Follow

sleep deprivation, sleep quality, college students, causes, effects

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Health Psychology | Psychology | Social and Behavioral Sciences

This article is an examination of the various causes and effects of sleep deprivation and poor sleep quality in college students. Using various studies and articles as evidence, this review explores the causes of sleep deprivation in college students, and addresses the ways in which other parts of one's well-being may suffer as a result of sleep deprivation. The nature of life as a college student is not conducive to good quality sleep or sufficient amount of sleep, and the various detrimental factors to sleep quality, such as napping, technology, and social factors contribute to problems in other areas. According to existing literature, circadian rhythm-disrupting excessive napping, hyper-vigilance to technology, fear of missing out, and the social nature of life in a dorm room all contribute to sleep deprivation. Consequent problems in the areas of physical health, mental health, and academic performance are common. Such problems include weight gain, immune system deficiency, increased risk for cancer and Alzheimer’s, stress, anxiety, depression, poor memory and decreased concentration, lower grades and poorer test performance. Additionally, this review addresses possible solutions to the poor sleep quality that seems to be inherent in college life, such as sleep hygiene courses incorporated into program requirements, as well as areas for further research, such as the desire for college students to nap.

Recommended Citation

Pandolfo, Isabella E.. "Sleepless in College Town: Causes and Effects of Poor Sleep in College Students." The Review: A Journal of Undergraduate Student Research 23 (2022): -. Web. [date of access]. <https://fisherpub.sjf.edu/ur/vol23/iss1/6>.

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• Published: 01 October 2019

Sleep quality, duration, and consistency are associated with better academic performance in college students

• Kana Okano 1 ,
• Jakub R. Kaczmarzyk 1 ,
• Neha Dave 2 ,
• John D. E. Gabrieli 1 &
• Jeffrey C. Grossman   ORCID: orcid.org/0000-0003-1281-2359 3  

npj Science of Learning volume  4 , Article number:  16 ( 2019 ) Cite this article

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Although numerous survey studies have reported connections between sleep and cognitive function, there remains a lack of quantitative data using objective measures to directly assess the association between sleep and academic performance. In this study, wearable activity trackers were distributed to 100 students in an introductory college chemistry class (88 of whom completed the study), allowing for multiple sleep measures to be correlated with in-class performance on quizzes and midterm examinations. Overall, better quality, longer duration, and greater consistency of sleep correlated with better grades. However, there was no relation between sleep measures on the single night before a test and test performance; instead, sleep duration and quality for the month and the week before a test correlated with better grades. Sleep measures accounted for nearly 25% of the variance in academic performance. These findings provide quantitative, objective evidence that better quality, longer duration, and greater consistency of sleep are strongly associated with better academic performance in college. Gender differences are discussed.

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Introduction.

The relationship between sleep and cognitive function has been a topic of interest for over a century. Well-controlled sleep studies conducted with healthy adults have shown that better sleep is associated with a myriad of superior cognitive functions, 1 , 2 , 3 , 4 , 5 , 6 including better learning and memory. 7 , 8 These effects have been found to extend beyond the laboratory setting such that self-reported sleep measures from students in the comfort of their own homes have also been found to be associated with academic performance. 9 , 10 , 11 , 12 , 13

Sleep is thought to play a crucial and specific role in memory consolidation. Although the exact mechanisms behind the relationship between sleep, memory, and neuro-plasticity are yet unknown, the general understanding is that specific synaptic connections that were active during awake-periods are strengthened during sleep, allowing for the consolidation of memory, and synaptic connections that were inactive are weakened. 5 , 14 , 15 Thus, sleep provides an essential function for memory consolidation (allowing us to remember what has been studied), which in turn is critical for successful academic performance.

Beyond the effects of sleep on memory consolidation, lack of sleep has been linked to poor attention and cognition. Well-controlled sleep deprivation studies have shown that lack of sleep not only increases fatigue and sleepiness but also worsens cognitive performance. 2 , 3 , 16 , 17 In fact, the cognitive performance of an individual who has been awake for 17 h is equivalent to that exhibited by one who has a blood alcohol concentration of 0.05%. 1 Outside of a laboratory setting, studies examining sleep in the comfort of peoples’ own homes via self-report surveys have found that persistently poor sleepers experience significantly more daytime difficulties in regards to fatigue, sleepiness, and poor cognition compared with persistently good sleepers. 18

Generally, sleep is associated with academic performance in school. Sleep deficit has been associated with lack of concentration and attention during class. 19 While a few studies report null effects, 20 , 21 most studies looking at the effects of sleep quality and duration on academic performance have linked longer and better-quality sleep with better academic performance such as school grades and study effort. 4 , 6 , 9 , 10 , 11 , 12 , 13 , 22 , 23 , 24 , 25 , 26 , 27 Similarly, sleep inconsistency plays a part in academic performance. Sleep inconsistency (sometimes called “social jet lag”) is defined by inconsistency in sleep schedule and/or duration from day to day. It is typically seen in the form of sleep debt during weekdays followed by oversleep on weekends. Sleep inconsistency tends to be greatest in adolescents and young adults who stay up late but are constrained by strict morning schedules. Adolescents who experience greater sleep inconsistency perform worse in school. 28 , 29 , 30 , 31

Although numerous studies have investigated the relationship between sleep and students’ academic performance, these studies utilized subjective measures of sleep duration and/or quality, typically in the form of self-report surveys; very few to date have used objective measures to quantify sleep duration and quality in students. One exception is a pair of linked studies that examined short-term benefits of sleep on academic performance in college. Students were incentivized with offers of extra credit if they averaged eight or more hours of sleep during final exams week in a psychology class 32 or five days leading up to the completion of a graphics studio final assignment. 33 Students who averaged eight or more hours of sleep, as measured by a wearable activity tracker, performed significantly better on their final psychology exams than students who chose not to participate or who slept less than eight hours. In contrast, for the graphics studio final assignments no difference was found in performance between students who averaged eight or more hours of sleep and those who did not get as much sleep, although sleep consistency in that case was found to be a factor.

Our aim in this study was to explore how sleep affects university students’ academic performance by objectively and ecologically tracking their sleep throughout an entire semester using Fitbit—a wearable activity tracker. Fitbit uses a combination of the wearer’s movement and heart-rate patterns to estimate the duration and quality of sleep. For instance, to determine sleep duration, the device measures the time in which the wearer has not moved, in combination with signature sleep movements such as rolling over. To determine sleep quality, the Fitbit device measures the wearer’s heart-rate variability which fluctuates during transitions between different stages of sleep. Although the specific algorithms that calculate these values are proprietary to Fitbit, they have been found to accurately estimate sleep duration and quality in normal adult sleepers without the use of research-grade sleep staging equipment. 34 By collecting quantitative sleep data over the course of the semester on nearly 100 students, we aimed to relate objective measures of sleep duration, quality, and consistency to academic performance from test to test and overall in the context of a real, large university college course.

A secondary aim was to understand gender differences in sleep and academic performance. Women outperform men in collegiate academic performance in most subjects 35 , 36 , 37 , 38 and even in online college courses. 39 Most of the research conducted to understand this female advantage in school grades has examined gender differences in self-discipline, 40 , 41 , 42 and none to date have considered gender differences in sleep as a mediating factor on school grades. There are inconsistencies in the literature on gender differences in sleep in young adults. While some studies report that females get more quantity 43 but worse quality sleep compared with males, 43 , 44 other studies report that females get better quality sleep. 45 , 46 In the current study, we aim to see whether we would observe a female advantage in grades and clarify how sleep contributes to gender differences.

Bedtime and wake-up times

On average, students went to bed at 1:54 a.m. (Median = 1:47 a.m., Standard Deviation (SD) of all bedtime samples = 2 h 11 min, SD of mean bedtime per participant = 1 h) and woke up at 9:17 a.m. (Median = 9:12 a.m., SD of all wake-up time samples = 2 h 2 min; SD of mean wake-up time per participant = 54 min). The data were confirmed to have Gaussian distribution using the Shapiro–Wilks normality test. We conducted an ANOVA with the overall score (sum of all grade-relevant quizzes and exams—see “Procedure”) as the dependent variable and bedtime (before or after median) and wake-up time (before or after median) as the independent variables. We found a main effect of bedtime ( F (1, 82) = 6.45, p  = 0.01), such that participants who went to bed before median bedtime had significantly higher overall score ( X  = 77.25%, SD = 13.71%) compared with participants who went to bed after median bedtime ( X  = 70.68%, SD = 11.01%). We also found a main effect of wake-up time ( F (1, 82) = 6.43, p  = 0.01), such that participants who woke up before median wake-up time had significantly higher overall score ( X  = 78.28%, SD = 9.33%) compared with participants who woke up after median wake-up time ( X  = 69.63%, SD = 14.38%), but found no interaction between bedtime and wake-up time ( F (1, 82) = 0.66, p  = 0.42).

A Pearson’s product-moment correlation between average bedtime and overall score revealed a significant and negative correlation ( r (86) = −0.45, p  < 0.0001), such that earlier average bedtime was associated with a higher overall score. There was a significant and negative correlation between average wake-up time and overall score ( r (86) = −0.35, p  < 0.001), such that earlier average wake-up time was associated with a higher overall score. There was also a significant and positive correlation between average bedtime and average wake-up time (r (86) = 0.68, p  < 0.0001), such that students who went to bed earlier tended to also wake up earlier.

Sleep duration, quality, and consistency in relation to academic performance

Overall, the mean duration of sleep for participants throughout the entire semester was 7 h 8 min (SD of all sleep samples = 1 h 48 min, SD of mean sleep duration per participant = 41 min). There was a significant positive correlation between mean sleep duration throughout the semester (sleep duration) and overall score ( r (86) = 0.38, p  < 0.0005), indicating that a greater amount of sleep was associated with a higher overall score (Fig. 1a ). Similarly, there was a significant positive correlation between mean sleep quality throughout the semester (Sleep Quality) and Overall Score ( r (86) = 0.44, p  < 0.00005). Sleep inconsistency was defined for each participant as the standard deviation of the participant’s daily sleep duration in minutes so that a larger standard deviation indicated greater sleep inconsistency. There was a significant negative correlation between sleep inconsistency and overall score ( r (86) = −0.36, p   <  0.001), indicating that the greater inconsistency in sleep duration was associated with a lower overall score (Fig. 1b ).

Correlations between sleep measures and overall score. a Average daily hours slept (sleep duration) vs. overall score for the semester. b Standard deviation of average daily hours of sleep (sleep inconsistency) vs. overall score in class

Timing of sleep and its relation to academic performance

To understand sleep and its potential role in memory consolidation, we examined the timing of sleep as it related to specific assessments. All Pearson correlations with three or more comparisons were corrected for multiple comparisons using false discovery rate. 47

Night before assessments

We conducted a correlation between sleep quality the night before a midterm and respective midterm scores as well as sleep duration the night before a midterm and respective scores. There were no significant correlations with sleep duration or sleep quality for all three midterms (all r s < 0.20, all p s > 0.05). Similar analyses for sleep duration and sleep quality the night before respective quizzes revealed no correlations ( r s from 0.01 to 0.26, all p s > 0.05).

Week and month leading up to assessments

To understand the effect of sleep across the time period while course content was learned for an assessment, we examined average sleep measures during the 1 month leading up to the midterms. We found a significant positive correlation between average sleep duration over the month leading up to scores on each midterm ( r s from 0.25 to 0.34, all p s < 0.02). Similar analyses for average sleep duration over one week leading up to respective quizzes were largely consistent with those of midterms, with significant correlations on 3 of 8 quizzes (rs from 0.3 to 0.4, all p s < 0.05) and marginal correlations on an additional 3 quizzes (rs from 0.25 to 0.27, all p s < 0.08).

There was a significant and positive correlation between sleep quality scores averaged over the month leading up to each midterm for all three midterms ( r s from 0.21 to 0.38, all p s < 0.05). Similar analyses for average Sleep Quality over one week leading up to respective quizzes revealed a significant correlation on 1 of 8 quizzes ( r (86) = 0.42, p  < 0.005) and marginal correlations on 3 quizzes ( r s from 0.25 to 0.27, all p s < 0.08).

Variance of assessment performance accounted for by sleep measures

In order to calculate how much of the variance on assessment performance was accounted for by the sleep measures, we conducted a stepwise regression on overall score using three regressors: sleep duration, sleep quality, and sleep inconsistency. The relative importance of each variable was calculated using the relaimpo package in R 48 to understand individual regressor’s contribution to the model, which is not always clear from the breakdown of model R 2 when regressors are correlated. We found a significant regression ( F (3,84) = 8.95, p  = .00003), with an R 2 of 0.24. Students’ predicted overall score was equal to 77.48 + 0.21 (sleep duration) + 19.59 (Sleep Quality) – 0.45 (sleep inconsistency). While sleep inconsistency was the only significant individual predictor of overall score ( p  = 0.03) in this analysis, we found that 24.44% of variance was explained by the three regressors. The relative importance of these metrics were 7.16% sleep duration, 9.68% sleep quality, and 7.6% sleep inconsistency.

Gender differences

Females had better Sleep Quality ( t (88) = 2.63, p  = 0.01), and less sleep inconsistency ( t (88) = 2.18, p  = 0.03) throughout the semester compared with males, but the two groups experienced no significant difference in sleep duration ( t (88) = 1.03, p  = 0.3). Sleep duration and sleep quality were significantly correlated in both males ( r (41) = 0.85, p  < 0.00001) and females ( r (43) = 0.64, p  < 0.00001), but this correlation was stronger in males ( Z  = −2.25, p  = 0.02) suggesting that it may be more important for males to get a long-duration sleep in order to get good quality sleep. In addition, sleep inconsistency and sleep quality were significantly negatively correlated in males ( r (41) = −0.51, p  = 0.0005) but not in females ( r (43) = 0.29, p  > 0.05), suggesting that it may be more important for males to stick to a regular daily sleep schedule in order to get good quality sleep.

Females scored higher on overall score compared with males ( t (88) = −2.48, p  = 0.01), but a one-way analysis of covariance (ANCOVA) revealed that females and males did not perform significantly different on overall score when controlling for Sleep Quality, F (1, 85) = 2.22, p  = 0.14. Sleep inconsistency and overall score were negatively correlated in males ( r (41) = −0.44, p  = 0.003) but not in females ( r (43) = −0.13, p  = 0.39), suggesting that it is important for males to stick to a regular sleep schedule in order to perform well in academic performance but less so for females. No other gender differences were detected between other sleep measures and overall score.

This study found that longer sleep duration, better sleep quality, and greater sleep consistency were associated with better academic performance. A multiple linear regression revealed that these three sleep measures accounted for 24.44% of the variance in overall grade performance. Thus, there was a substantial association between sleep and academic performance. The present results correlating overall sleep quality and duration with academic performance are well aligned with previous studies 6 , 11 , 12 , 24 , 25 on the role of sleep on cognitive performance. Similarly, this study compliments the two linked studies that found longer sleep duration during the week before final exams 47 and consistent sleep duration five days prior to a final assignment 48 enhanced students’ performance. The present study, however, significantly extends our understanding of the relation between sleep and academic performance by use of multiple objective measures of sleep throughout an entire semester and academic assessments completed along the way.

The present study also provides new insights about the timing of the relation between sleep and academic performance. Unlike a prior study, 23 we did not find that sleep duration the night before an exam was associated with better test performance. Instead we found that both longer sleep duration and better sleep quality over the full month before a midterm were more associated with better test performance. Rather than the night before a quiz or exam, it may be more important to sleep well for the duration of the time when the topics tested were taught. The implications of these findings are that, at least in the context of an academic assessment, the role of sleep is crucial during the time the content itself is learned, and simply getting good sleep the night before may not be as helpful. The outcome that better “content-relevant sleep” leads to improved performance is supported by previous controlled studies on the role of sleep in memory consolidation. 14 , 15

Consistent with some previous research 45 , 46 female students tended to experience better quality sleep and with more consistency than male students. In addition, we found that males required a longer and more regular daily sleep schedule in order to get good quality sleep. This female advantage in academic performance was eliminated once sleep patterns were statistically equated, suggesting that it may be especially important to encourage better sleep habits in male students (although such habits may be helpful for all students).

Several limitations of the present study may be noted. First, the sleep quality measures were made with proprietary algorithms. There is an evidence that the use of cardiac, respiratory, and movement information from Fitbit devices can accurately estimate sleep stages, 32 but there is no published evidence that Fitbit’s 1~10 sleep quality scores represent a valid assessment of sleep quality. Second, the relation between sleep and academic performance may be moderated by factors that can affect sleep, such as stress, anxiety, motivation, personality traits, and gender roles. Establishing a causal relation between sleep and academic performance will require experimental manipulations in randomized controlled trials, but these will be challenging to conduct in the context of real education in which students care about their grades. Third, these findings occurred for a particular student population at MIT enrolled in a particular course, and future studies will need to examine the generalizability of these findings to other types of student populations and other kinds of classes.

In sum, this study provides evidence for a strong relation between sleep and academic performance using a quantifiable and objective measures of sleep quality, duration, and consistency in the ecological context of a live classroom. Sleep quality, duration, and consistency together accounted for a substantial amount (about a quarter) of the overall variance in academic performance.

Participants

One hundred volunteers (47 females) were selected from a subset of students who volunteered among 370 students enrolled in Introduction to Solid State Chemistry at the Massachusetts Institute of Technology to participate in the study. Participants were informed of the study and gave written consent obtained in accordance with the guidelines of and approved by the MIT Committee on the Use of Humans as Experimental Subjects. Due to limitations in funding, we only had access to 100 Fitbit devices and could not enroll all students who volunteered; consequently, the first 100 participants to volunteer were selected. All participants were gifted a wearable activity tracker at the completion of the study in exchange for their participation. Seven participants were excluded from analysis because they failed to wear their activity tracker for more than 80% of the semester, three participants were excluded because they lost their wearable activity tracker, and another two participants were excluded because they completed less than 75% of the assessments in the class. Of the 88 participants who completed the study (45 females), 85 were freshmen, one was a junior and two were seniors (mean age = 18.19 years).

The Solid State Chemistry class is a single-semester class offered in the fall semester and geared toward freshmen students to satisfy MIT’s general chemistry requirement. The class consisted of weekly lectures by the professor and two weekly recitations led by 12 different teaching assistants (TAs). Each student was assigned to a specific recitation section that fit their schedule and was not allowed to attend other sections; therefore, each student had the same TA throughout the semester. Students took (1) weekly quizzes that tested knowledge on the content covered the week leading up to the quiz date, (2) three midterms that tested knowledge on the content covered in the 3–4 weeks leading up to the exam date, and (3) a final exam that tested content covered throughout the semester. Based on a one-way between subjects’ analysis of variance (ANOVA) to compare the effect of teaching assistants (TAs) on overall grade, we found no significant differences in overall grade across the TAs (F (10, 77) = 1.82, p  = 0.07. (One TA was removed from the analysis because he only had one student who was participating in this study).

Participants were asked to wear an activity tracker for the entire duration of the semester without going below 80% usage each week. If 80% or more usage was not maintained, warning emails were sent at the end of that respective week. Participants were asked to return the device if they dipped below 80% usage more than three out of the 14 weeks of the semester. The average usage rate at the end of the semester for the 88 participants who completed the study was 89.4% (SD = 5.5%). The missing data appeared to be at random and were deleted prior to data analysis. As part of a separate research question, 22 of the 88 participants joined an intense cardiovascular exercise class for which they received separate physical education credit. These students performed similarly to the other 67 participants in terms of final class grade ( t (88) = 1.57, p  = 0.12), exercise amount (total amount of moderately and very active minutes on the wearable device) (t (88) = 0.59, p  = 0.56), sleep amount ( t (88) = 0.3, p  = 0.77), and sleep quality ( t (88) = 0.14, p  = 0.9), so they were included in all of the analyses.

Participants’ activities were tracked using a Fitbit Charge HR. Data from the device were recorded as follows: heart rate every 5 min; steps taken, distance traveled, floors climbed, calories burned and activity level measurements every 15 min; resting heart rate daily; and sleep duration and quality for every instance of sleep throughout the day. Sleep quality was determined using Fitbit’s proprietary algorithm that produces a value from 0 (poor quality) to 10 (good quality).

Assessments

Nine quizzes, three midterm examinations, and one final examination were administered throughout the 14-week class to assess the students’ academic achievement. The students’ cumulative class grade was made up of 25% for all nine quizzes (lowest quiz grade was dropped from the average), 15% for each midterm exam, and 30% for the final exam for a total of 100%.

At MIT, freshmen are graded on a Pass or No Record basis in all classes taken during their first semester. Therefore, all freshmen in this class needed a C- level or better (≥50%, no grading on a curve) to pass the class. A failing grade (a D or F grade) did not go on their academic record. All upperclassmen were given letter grades; A (≥85%), B (70–84%), C (50–69%), D (45–49%), F (≤44%). Because a large portion of the class had already effectively “passed” the class before taking Quiz 9 and the final exam, we excluded these two assessments from our analyses due to concerns about students’ motivation to perform their best. We calculated for each student an overall score defined as the sum of the eight quizzes and three midterms to summarize academic performance in the course.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

No custom codes were used in the analysis of this study

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Acknowledgements

This research was supported by a grant from the Horace A. Lubin Fund in the MIT Department of Materials Science and Engineering to J.C.G. and funding from MIT Integrated Learning Initiative to K.O. and J.R.K. The authors are grateful for many useful discussions with Carrie Moore and Matthew Breen at the Department of Athletics, Physical Education, and Recreation at MIT.

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Okano, K., Kaczmarzyk, J.R., Dave, N. et al. Sleep quality, duration, and consistency are associated with better academic performance in college students. npj Sci. Learn. 4 , 16 (2019). https://doi.org/10.1038/s41539-019-0055-z

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The less college students sleep, the worse their grades, study finds

Every lost hour of average nightly sleep at the start of an academic term predicted a 0.07-point drop in a student’s GPA

There are countless reasons to stay up late in college. Here’s one good reason to go to bed.

The less a student sleeps every night, the lower their grade-point average will be, according to a two-year study of the sleep habits of more than 600 college freshmen that was published Monday in the Proceedings of the National Academy of Sciences.

Researchers found that every lost hour of average nightly sleep at the start of an academic term was associated with a 0.07-point drop in a student’s end-of-term GPA. When a student slept less than six hours a night, the effect of lost sleep on a student’s grades was even more pronounced, said David Creswell, the lead author of the study and a professor in psychology and neuroscience at Carnegie Mellon University.

“You’re accumulating this sleep debt ,” Creswell said. “And that has a pretty negative role in terms of people’s academics.”

Sleep, especially undisturbed sleep, helps the brain process and retain information it has learned. And when someone is sleep-deprived, attention span and memory also are impaired .

But students have a number of “competing pressures” to stay up late in college, especially in their freshman year, which is often the first time students are living away from home, Creswell said. The average student in the study fell asleep about 2:30 a.m. Barely any of the students went to bed before midnight. And, on average, they slept 6½ hours a night.

Just one hour of extra sleep each night can lead to better eating habits

Sleep recommendations vary

Sleep recommendations shift by age, and the amount of sleep an individual actually needs can vary person to person. In general, for teenagers, the recommendation is eight to 10 hours of sleep. For those 18 to 25 years old, it drops to seven to nine hours.

Creswell said he doesn’t want to “lecture” students about the findings but, according to the research, it appears that getting enough shut-eye does boost a student’s GPA.

“A lot of students say, ‘I should just stay up a lot later and study a lot longer,’ ” Creswell said. “Well, what we’re showing here is that sleep may be your friend, in terms of helping consolidate this information.”

Creswell and the team of researchers conducted five studies, recruiting college freshmen taking courses in a range of majors at Carnegie Mellon, the University of Notre Dame and the University of Washington. To monitor sleep, the students wore either a Fitbit Flex or a Fitbit HR for the entire academic term, a spring semester or a winter quarter, depending on the school, Creswell said.

Creswell said they avoided studying students’ sleep habits around final exams and term papers because they assumed that the average student’s sleep would just continue to drop off.

“We really wanted to look at this critical period in the semester where you’re starting to establish sleep patterns,” Creswell said. “Because once you start to hit midterm and finals period, you’re sort of too late in the game for actually doing effective intervention.”

After controlling for other factors — such as whether a student takes naps, their number of class credits and their GPA the previous term — the researchers found that average nightly sleep continued to predict a student’s end-of-term GPA. What time a student went to bed and whether their bedtime varied day to day did not seem to play a role, Creswell said.

A similar study of 100 engineering students at the Massachusetts Institute of Technology published in 2019 found the same association between a student’s grades and the amount of sleep they were getting. That study also showed it was tough to make up for bad sleep habits. There was no improvement in scores among students who made sure to get a good night’s sleep right before a big test.

Insufficient sleep may create ‘sleep debt’

It’s not clear why less sleep would cause someone to have a lower GPA, Creswell said. Sleeping for longer, uninterrupted periods of time allows for REM sleep, a period of unconscious rapid eye movement that corresponds with high activity in the brain. Creswell said he suspects a regular pattern of insufficient sleep creates a “sleep debt” over time, leaving students unable to concentrate.

“These college students are going to class with a ton of sleep debt, and they’re having trouble staying focused and learning in college classrooms,” Creswell said. “Those things can really harm your ability to really engage with the material.”

Aric Prather, a psychologist at the University of California at San Francisco, and author of the book, “ The Sleep Prescription ,” said the findings could inform systemic changes at universities, campaigns or workshops to help students have a better night’s sleep.

“There are multiple pathways to get to a GPA, and sleep is like the glue that holds our lives together in lots of domains,” Prather said. “When that whittles away, or is less sticky, bad things happen.”

Grace Pilch, an 18-year-old freshman who lives in a dorm at Pennsylvania State University, said she needs to get at least eight hours of sleep to function in class and during workouts at the gym.

“I can always tell if I didn’t get enough sleep,” Pilch said.

Pilch, who’s majoring in graphic design, said she cares more about getting enough sleep in college than she did in high school because “the classes are expensive,” and she wants to do well. Pilch said she has around a 3.8 GPA so far. And she and her roommate are in bed by 11 p.m. during the week.

“But I do go out with my friends,” Pilch said. “Sleep is important, grades are important, but it’s also important to make connections.”

3 ways to stop waking up frequently during the night and improve sleep

Academic success early on in college has been shown to predict whether students stay in school or drop out years later, and campus programs to address sleep habits could help freshmen during a “critical period” in school, Creswell said.

“We could really teach them, in that first year of college, better sleep patterns that could help them with their academic achievement,” Creswell said.

At the University of Pennsylvania in Philadelphia, 200 students and staff members have enrolled in a seven-week online course on building better sleep habits. Rebecca Huxta, the director of public health and wellness at the university, said that since starting the program, participants have reported an overall decrease in symptoms of insomnia.

Roxanne Prichard, a professor of psychology at the University of St. Thomas in St. Paul, Minn., said that she finds students “have been exhausted since puberty,” and they’ve “grown accustomed” to always feeling lethargic.

“Fundamentally, it comes down to: If we’re not sleeping well, all systems are not a go,” Prichard said. “Our body is not prepared for the day ahead of us and what we’re asking it to do if we don’t have that good, basic chunk of nighttime sleep.”

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Sleeping with technology: cognitive, affective, and technology usage predictors of sleep problems among college students

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Sleep problems in university students – an intervention

Angelika anita schlarb.

Faculty of Psychology and Sports, Bielefeld University, Bielefeld, Germany

Anja Friedrich

Merle claßen, introduction.

Up to 60% of all college students suffer from a poor sleep quality, and 7.7% meet all criteria of an insomnia disorder. Sleep problems have a great impact on the students’ daily life, for example, the grade point average. Due to irregular daytime routines, chronotype changes, side jobs and exam periods, they need specialized treatments for improving sleep. “Studieren wie im Schlaf” (SWIS; (studying in your sleep)) is a multicomponent sleep training that combines Cognitive Behavioral Therapy for Insomnia and Hypnotherapy for Insomnia to improve students’ sleep, insomnia symptoms and nightmares. The aim of the present study is to evaluate the acceptance, feasibility and the first effects of SWIS.

Twenty-seven students (mean =24.24, standard deviation =3.57) participated in a study of pre–post design. The acceptance and feasibility were measured with questionnaires. In addition, the Pittsburgh Sleep Quality Index (PSQI), sleep logs and actigraphy were implemented. Further variables encompassed daytime sleepiness, sleep-related personality traits and cognitions about sleep.

Seventy-four percent of the participants reported symptoms of an insomnia disorder, and 51.9% fulfilled all criteria of an insomnia disorder according to the Diagnostic and Statistical Manual of Mental Disorders (fifth edition). Correspondingly, the students suffered from clinically relevant sleep problems according to the PSQI. The SWIS sleep training is a well-accepted and feasible program. Significant improvements were observed in the subjective sleep quality and sleep-related personality traits, as well as clinical improvements in objective sleep measures.

Findings showed that SWIS is a feasible program for the treatment of sleep problems in college and university students due to its various effects on sleep and cognitive outcomes. Further evaluation of follow-up measurements and additional variables, that is, cognitive performance and mental health, is needed.

Video abstract

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Students experience several important developments when starting at university. They have to cope with “leaving home, increased independence, changes in peer groups, new social situations, maintenance of academic responsibilities and increased access to alcohol or drugs”. 1 About 90% of university students have roommates, and among them, 41% wake up at night due to the noise of others. Bed- and risetimes on weekdays and weekends often differ in the range of more than 1 to 2 hours. These challenges and special circumstances faced by university students are associated with sleep disturbances. 2 About 60% suffer from a poor sleep quality according to the PSQI. 3 Gaultney revealed that 27% of all university students are at a risk of at least one sleep disorder. 4 Furthermore, previous findings reported that a minimum 7.7% of students suffer from insomnia and 24.3% from nightmares. 5 , 6

Sleep problems and sleep disorders severely impair university students’ academic success. In a study conducted by Buboltz et al, 31% of all students suffered from morning tiredness. 2 In another study, poor sleepers reported reduced daytime functioning. 7 Shorter sleep duration and an irregular sleep–wake schedule significantly correlated with a lower GPA. 4 Regarding sleep habits, the wake-up times explained significant amounts of GPA variance. 8 A clinical review provided evidence that sleep problems correlated with impeded learning, especially poorer declarative and procedural learning, neurocognitive performance and academic success. 9

Beyond academic considerations, sleep problems in university students are often connected with mental health issues. It is common for students with insomnia to suffer from mental health problems such as chronic fatigue, depression, stress, lower optimism, anxiety and a lower quality of life. 1 , 10 , 11 Taylor et al controlled the correlation between insomnia and mental health problems for medical problems (ie, migraines, gastrointestinal diseases, sexually transmitted diseases). Even then, significant correlations were found for obsessive–compulsive symptoms, somatization, depression, anxiety and overall symptoms. 12 In addition, students suffering from insomnia often thought about their sleep problems or ruminated about daily events. 13 Furthermore, students with worse sleep reported more rumination about a stressful life event (ie, exam). 14 Correspondingly, other studies showed that rumination predicted longer sleep-onset latency and was associated with lower sleep efficiency, wakefulness after sleep onset and reduced sleep quality. 15 , 16 These associations also existed after controlling for general cognitive arousal, depression and anxiety. 17 , 18 Vail-Smith et al discovered that students who reported physical aggression, suicide ideation and substance abuse had a significantly worse sleep quality than those who did not suffer from one of the aforementioned factors. 19 This relationship between sleep problems and suicidality persisted when taking aggressive behavior and depression into account. 20 Correspondingly, nightmares were significantly related to suicidal ideation even after controlling for depression, anxiety and posttraumatic stress disorder. 21 Students who suffered from nightmares often reported more insomnia symptoms and lower self-efficacy. 6

A poor sleep quality is often associated with stimulant use in university students. 22 Correspondingly, sleep medication is the second most common substance group consumed by German university students. 23

Finally, one-quarter of all university students are evening chronotypes. 24 Eveningness is often associated with a poor sleep quality, 25 lower self-control, more procrastination, 26 more stress sensitivity 27 – 29 and lower sleep efficiency. 24 All in all, various sleep-related parameters and disorders affect university students’ life.

Despite the high prevalence rates and the severe consequences, only a few studies examined the treatment of sleep disorders in university students. A recent systematic review found that there is a lack of specialized treatment of insomnia for college students. 30 Cognitive-behavioral therapy was the most effective approach to improve sleep in university students with relaxation techniques, mindfulness and hypnotherapy additionally benefiting mental health outcomes. 30 However, most of the 27 included studies were conducted on healthy students who did not suffer from sleep problems, different outcomes were investigated, objective sleep was ignored and only a handful of studies provided follow-up data. 30 Not a single study examined other sleep disorders besides insomnia or assessed the sleep regularity and chronotype of the students.

SWIS – a sleep training for university students

“Studieren wie im Schlaf” (SWIS; studying in your sleep) – a sleep training for university students with sleep problems – was derived from the structure of sleep treatment programs for different age groups, for example, Mini-KiSS 31 for infants under the age of five, KiSS 32 for children aged five to ten and JuSt 33 for adolescents. With a maximum of six sessions, all these programs were relatively short and were based on a combination of CBT-I and HT-I. Correspondingly, the six SWIS sessions each contained CBT-I and HT-I elements. As a multicomponent intervention, SWIS focused on the challenges of university students’ life by addressing special circumstances and environmental factors as well as biological factors. These included irregular sleep–wake cycles due to variability in their daily routine, side jobs, chronotype changes as well as learning and exam periods.

In this pilot study, we first examined the acceptance of participants and trainers. Secondly, we assessed whether the students and trainers rated SWIS as a feasible program. Thirdly, we investigated if the SWIS treatment improved various sleep variables including, a) symptoms of sleep disorders, b) sleep quality, c) daytime sleepiness, d) rumination and focusing, as well as e) dysfunctional cognitions about sleep. While the first two hypotheses aimed to evaluate the participants’ and trainers’ acceptance, the other hypothesis tested first hints toward effectiveness, thus incorporating both aspects of feasibility.

The quasi-experimental study investigated the acceptance and feasibility of SWIS. Four treatment groups with five to seven participants completed the training. All participants suffered from symptoms of sleep disorders, such as insomnia disorder, nightmares or irregular sleep–wake type, according to DSM-5. 34 Two psychologists executed the training sessions during the afternoon or early evening. Every training session was supervised for manual adherence and treatment fidelity.

Sleep disorders were diagnosed according to the classification criteria of the DSM-5. 34 In addition, participants were classified as “poor sleepers” by the PSQI if they scored above a cut-off of 5, or as severely impaired sleepers if they scored above 10. 35 , 36

The pretest was taken 2 weeks before the treatment, and the post-measurement 2 weeks after the training. All participants provided written informed consent prior to diagnosis and treatment. The intervention involved six sessions. During pre- and post-measurement, participants filled out sleep logs for 14 days and wore actigraphs for 8 days to assess subjective and objective sleep quality. Furthermore, participants completed various questionnaires. The study was approved by the ethics committee of Bielefeld University.

Inclusion criteria

Based on the inclusion criteria, participants who fulfilled various criteria for an insomnia disorder or an irregular sleep–wake type according to DSM-5 classification, 34 as well as participants who reported nightmares ( Table 1 ) were included in this study. Sleep was assessed with the self-developed SPQ. In addition, participants were categorized as “poor sleepers” by the PSQI. 35

Diagnostic criteria and SPQ

Note: Slashes indicate additional choices (item 1 and/or item 2), whereas plus signs indicate mandatory items (item 1 and item 2).

Abbreviation: SPQ, Sleep Problems Questionnaire.

Sleep Problems Questionnaire

Participants received a 12-item SPQ ( Table 2 ) based on the DSM-5 classification for an insomnia disorder and an irregular sleep–wake type. 34 Due to the fact that the inclusion criteria questionnaire was developed specifically for this study, no psychometric properties were examined. Three items pertained to the diagnosis of insomnia disorder (ie, “I suffer because I have difficulties initiating sleep”, items 1–3), two items supported an irregular sleep–wake-type diagnosis (ie, “I sleep at least three times in 24 hours”, items 7, 9) and the other six items determined sleep problem frequency (items 5, 6), impairment (item 8) and exclusion criteria (“My sleep problems are not mainly caused by bad sleep hygiene”, items 10–12). The exclusion criteria were formulated in a double-negative form. A dichotomous answer mode (yes/no) was employed.

Sample and sleep disturbances during baseline

Abbreviations: M, mean; SD, standard deviation.

Diagnostic criteria

Insomnia was diagnosed if participants had trouble initiating sleep, woke up during the night, or had difficulties falling asleep after waking up at night. In addition, they had to report daytime impairments. Insomnia with sleep-onset latency was diagnosed if students fulfilled all criteria of an insomnia disorder and reported a sleep latency greater than 30 minutes. The irregular sleep–wake type included participants with fragmented sleep (at least three sleep periods in 24 hours) or other self-reported irregular sleep. To receive a diagnosis, the sleep problems had to cause significant distress, occur at least three times per week and persist for longer than 1 month. Nightmares were indicated if participants reported nightmares at least three times per week according to DSM-5 criteria ( Table 1 ).

Figure 1 provides an overview of the participant flow during the study. Forty applications were screened, and 27 participants were invited to take part in the study. Due to exclusion (one participant) and dropouts before (three participants) and during the training (three participants) as well as dropouts after the training (one participant), 19 participants remained for the post-measurement.

SWIS flowchart.

Abbreviation: SWIS, Studieren wie im Schlaf (studying in your sleep).

The sample characteristics for the different measurement times are displayed in Table 3 . The mean age was M =24.24 (SD =3.57) years during pre-measurement. There were more women (77.8%; men 22.2%) participants. One participant had to be excluded due to a low PSQI score (PSQI =4). The remaining 26 participants (96.29%) scored above the PSQI cut-off defining a poor sleep quality (PSQI sum score >5).

SAQ scales and items

Abbreviation: SAQ, Student Acceptance Questionnaire.

Approximately two-thirds of the sample reported difficulties initiating sleep and maintaining sleep and subjective impairment because of the sleep problems. Of all the participants, 51.9% reported early awakening. While more than half of the students fulfilled all criteria for an insomnia disorder, nightmares and irregular sleep–wake types were less common.

Instruments

To evaluate the acceptance of the training, two questionnaires were implemented: one for the students (SAQ) and the other for the trainers (TAQ). They were based on similar questionnaires in a previous sleep study. 33 Students and trainers anonymously completed the questionnaires after each session. Answering modes comprised a five-point Likert scale ranging from “applies to me completely” (1) to “does not apply to me at all” (5). Lower scores indicated a higher satisfaction with the sleep training.

Student Acceptance Questionnaire

The SAQ consisted of 14 items ( Table 4 ). Four scales measured the participants’ acceptance of each training session’s content, didactics, transfer into everyday life and trainer aptitude. Two global items evaluated satisfaction with HT-I and group dynamics.

Trainer acceptance questionnaire

Notes: (a) = acceptance scale; (f) = feasibility scale. Item 15 was reversed (−).

In addition to the acceptance questionnaires, students were asked to grade the training on a scale from 1 (“SWIS did not help at all”) to 5 (“SWIS helped very much”) after completing all training sessions.

Trainer Acceptance Questionnaire

The TAQ contained seven scales that measured the satisfaction with the sleep training’s contents and questions regarding group dynamics ( Table 5 ). The four scales content, hypnotherapy, trainer aptitude and group dynamics were used to measure the trainers’ acceptance.

Items of the SPQ (insomnia/irregular sleep schedule)

A short section for notes and observations provided opportunity for the documentation of additional information and suggestions regarding the sessions’ content.

At the end of the TAQ, the trainers assessed the time-frame, participant comprehension and participant acceptance for each part of the training sessions. The answers were coded in grades from 1 (“completely applies to me”) to 5 (“does not apply to me at all”).

Feasibility

The feasibility of SWIS was indicated by participant dropout and attendance rates during the training. In order to measure the feasibility from the trainer’s point of view, four sections from the TAQ were included: three scales (frame conditions, instruction, co-trainer) and the section at the end containing timeframe, participant comprehension and participant acceptance for each part of the training sessions.

Sleep measurements

Pittsburgh sleep quality index.

The PSQI 35 determines the participant’s sleep quality during the last month. Eighteen items merge into seven scales: subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep problems, sleep medication and daytime sleepiness. Answering modes mostly comprise a four-point Likert scale ranging from “never during the last 4 weeks” to “three times or more per week”. Sum scores range from 0 to 21, with higher scores indicating more sleep problems. There are two cut-off scores: sum scores above 5 indicate a poor sleep quality, while sum scores above 10 indicate chronic sleep problems. 37 , 38 Carpenter and Andrykowski confirmed the instruments’ internal consistency (Cronbach’s α =0.80) and construct validity. 39

The nightmare item of the PSQI (“I slept badly during the last 4 weeks because I had bad dreams”) was regarded as fulfilled if the participants suffered from bad dreams at least three times per week.

Participants were asked to complete a sleep log for 2 weeks during pre- and post-measurement. The diagnostic sleep log contained eight questions about sleep including rise- and bedtimes, waking up during the night, naps during the day and regeneration. The regeneration was measured on a six-point Likert scale ranging from “sleep was very restorative” (1) to “sleep was not restorative at all” (6). As the current study is a feasibility study, we focused on the analysis of the sleep duration and regeneration aspects reported in the sleep logs as main outcomes.

The SOMNOwatch™ plus by SOMNOmedics (Rander-sacker, Germany) is an actigraph wrist watch with three built-in activity sensors. Analysis with the DOMINO Light Software (SOMNOmedics) provides data for time in bed, sleep duration, wake duration, number of night-time awakenings, sleep efficiency and sleep latency. In a study with sleep apnea patients, the SOMNOwatch™ plus had an overall accuracy of 85.9% when compared to polysomnography. 40 The participants wore the actigraphs for 8 days during pre-and post-measurement.

Epworth Sleepiness Scale

The ESS 41 consists of eight items and measures daytime sleepiness across different situations (ie, sitting and reading). Despite its relatively short form, both the test–retest reliability ( r =0.82) and the internal consistency in clinical ( α =0.88) and nonclinical populations ( α =0.73) are adequate. 42

Morningness–Eveningness Questionnaire

The chronotype was measured with the MEQ. 43 The MEQ consists of 19 items that add up to a sum score. According to the sum score, participants are classified as definite evening types (14–30), moderate evening types (31–41), neutral type (42–58), moderate morning type (59–69) or definite morning type (70–86). The reliability and validity of the MEQ could be proven, notwithstanding the instruments’ multidimensionality. 44

Fragebogen zur Erfassung spezifischer Persönlichkeitsmerkmale Schlafgestörter (Questionnaire of specific personality traits for patients with sleep disorders)

The FEPS-II 45 records two personality traits on a five-point Likert scale: focusing (11 items) and rumination (12 items). Gender-specific norms are provided for healthy sleepers (N=346) and patients with sleep disorders (N=322). Though the psychometric qualities of the FEPS-II have not been sufficiently examined yet, it is the only instrument that measures these specific personality traits in participants with sleep problems.

Meinungen-zum-Schlaf-Fragebogen (cognitions about sleep)

Weingartz and Pillmann developed the MZS in order to investigate the participants’ beliefs concerning sleep. 46 Sixteen convictions about sleep are rated on a ten-point scale ranging from “I absolutely disagree” (0) to “I absolutely agree” (10), with higher scores indicating more dysfunctional beliefs about sleep. A factor analysis by Weingartz and Pillmann revealed the three factors, “convictions about long-term consequences”, “biological causes for sleep disorders” and “influence on daytime productivity”. According to the authors, the MZS is a reliable ( α =.87) and valid instrument. 46

Intervention: SWIS

SWIS is a multicomponent group treatment and consists of six training sessions of 100 minutes ( Table 6 ). Behavior therapeutic elements are rules of healthy sleeping, sleep- promoting living arrangements, sleep rituals, progressive muscle relaxation, cognitive restructuring, stress management and problem-solving skills. Trance sessions, self-calming imaginations, self-hypnosis and further imagination techniques comprise the hypnotherapeutic elements. Based on the special requirements and situations of college/university students such as chronotype, sleep environment, self-organization processes for learning and changing starting times at university, first relationship, partying, etc, the treatment was adapted from adolescent treatment (JuSt) and insomnia treatment for adults. Beyond CBT-I, HT-I elements were included to address relaxation and nightmare strategies as imaginary rescripting strategy. As prior results showed, HT-I is helpful to enhance deep sleep and to address insomnia. 47 , 48 Participants have to practice the session contents at home.

Short description for each SWIS session

Abbreviations: SWIS, Studieren wie im Schlaf (studying in your sleep); HT-I, Hypnotherapy for Insomnia; PMR, progressive muscle relaxation.

At the beginning of each session, students were asked to describe their progress and difficulties regarding the implementation of SWIS during everyday life. At the end, they received a CD with the session’s HT-I elements to establish practice at home.

Data analysis

Data were analyzed with the Statistical Package for Social Sciences version 22 (Version 22.0; IBM Corporation, Armonk, NY, USA) and Microsoft Excel 2013 (Microsoft Corporation, Redmond, WA, USA). The inclusion criteria, acceptance questionnaires and grades were analyzed with a descriptive and frequency analysis. The notes and observations of the acceptance questionnaires were listed.

Prior to analysis, each variable was tested for normal distribution (Shapiro–Wilk). The differences between pre- and post-measurement were analyzed with a Student’s t -test for dependent samples if they were normally distributed and a Wilcoxon signed-rank test if they were not. Effect sizes were Cohen’s d for the Student’s t -test (small >0.20, medium >0.50, large >0.80) and Pearson’s correlation coefficient r for the Wilcoxon signed-rank test (small >0.10, medium >0.30, large >0.50). They were only calculated if the test statistic provided significant P -values.

Average weekly sleep duration and regeneration scores were compiled from the diagnostic sleep logs. Missing values were replaced with the average weekly score.

Control for group disparities could not be conducted due to the small sample sizes for pre- and post-measurement comparison. For data analysis, it was assumed that the four treatment groups did not differ significantly.

The significance level was set at P <0.05. A tendency was detected with a P -value <0.10. Due to the small sample size, the missing questionnaire data were not imputed but excluded from the analyses.

Prevalence rates for sleep problems and diagnoses

Many participants (74%) fulfilled criteria for an insomnia disorder or reported various insomnia symptoms in the SPQ (items 1–3). Eighteen participants (67%) rated their sleep problems as a strong impairment (item 4). Similarly, 13 participants (48%) reported that daytime sleepiness reduced their quality of life. Sleep problems often lasted longer than 1 month (74%) and often occurred more than three times per week (59%). Irregular sleep patterns were found in 11%, while fragmented sleep was not reported. Table 7 shows the prevalence rates for each sleep disorder separately. At post-measurement, fewer students reported sleep disturbances and fulfilled the diagnostic criteria for insomnia and nightmares.

Prevalence rates of sleep disturbances for pre- and post-measurement

Figure 2 displays information about the comorbidities in the current sample. Most participants displayed sleep disturbances (74%) or fulfilled the criteria for one sleep disorder (30%). Insomnia and nightmares were the most common comorbidities (11%), followed by a combination of all three sleep disorders (7%). Only 4% reported insomnia and an irregular sleep–wake type simultaneously. The combination of nightmares and irregular sleep–wake type was not present in this sample.

Comorbid sleep disorders. Sleep disturbances indicate difficulties initiating sleep or maintaining sleep, or early awakening.

Abbreviation: ISWT, irregular sleep–wake type.

PSQI sum scores indicated a poor sleep quality mean for the whole group (M =10.41, SD =3.51) with a minimum score of six and a maximum score of 18 ( Figure 3 ). Therefore, all participants reported a poor sleep quality according to the PSQI. Fifteen participants (55.56%) even reported a severely impaired sleep quality (PSQI >10).

Included participants categorized according to PSQI cut-off scores.

Abbreviation: PSQI, Pittsburgh Sleep Quality Index.

The results for the students’ acceptance of the SWIS training as a multicomponent group treatment are presented in Table 8 . All SWIS components were well accepted. The scale group dynamics received the highest acceptance ratings, while the participants’ acceptance of the HT-I components was only medium.

Students’ acceptance of the SWIS training

Notes: Means and standard deviations are provided for the four scales and two global items. Lower scores represent a higher satisfaction (range 1–5).

Abbreviations: SWIS, Studieren wie im Schlaf (studying in your sleep); M, mean; SD, standard deviation; HT-I, Hypnotherapy for Insomnia.

In accordance with the acceptance questionnaires, students gave an average grade rating of M =2.61 (SD =0.69) indicating an overall good satisfaction with the SWIS training. Further acceptance was also documented by the fact that only three of the 27 participants discontinued the SWIS program after two sessions. The students’ acceptance was also documented by the fact that all participants who completed the program attended at least four of the six sessions.

The results for the trainer’s acceptance and the feasibility of the SWIS training are demonstrated in Table 9 . All scales were evaluated positively. The scale group dynamics received the highest acceptance rating (M =1.52, SD =0.46), while the scale co-trainer received the highest feasibility rating (M =1.03, SD =0.13).

Trainers’ acceptance and feasibility of the SWIS training

Notes: Means and standard deviations are provided for six scales and one global item. Lower scores represent a higher satisfaction (range 1–5).

The results for the three feasibility scales of the TAQ are presented in Table 9 . All scales received favorable evaluation. The scale co-trainer had the best evaluation (M =1.03, SD =0.13). Trainers reported a moderate-to-excellent satisfaction with the session parts’ timeframe. Mean timeframe ratings ranged from excellent for the self-hypnosis in session 4 (M =1.00, SD =0.00) to moderate for the rules of healthy sleeping in session 1 (M =2.25, SD =1.41). The trainers evaluated the participants’ comprehension of the session parts to be excellent for the feedback elements at the beginning of each session (M =1.33, SD =0.58) and moderate for the stress section in session 4 (M =2.50, SD =0.55). The trainers rated the participants’ acceptance as excellent for the emergency sleep kit in session 6 (M =1.20, SD =0.45) and moderate for the useful inner phrases in the same session (M =3.00, SD =0.71).

The following paragraphs refer to the comparison between pre- and post-measurement.

The PSQI sum scores declined significantly from pre- to post-measurement ( Table 10 ), indicating a higher sleep quality after the training. Nonparametric results for the seven PSQI scales showed significantly improved scores regarding subjective sleep quality, sleep-onset latency and daytime sleepiness. Positive tendencies ( P <0.10) were detected for sleep duration and sleep efficiency. The two subscales sleep disturbances and sleep medication did not change significantly according to PSQI. The effect size for the change in the PSQI sum scores was large. The differences in the subscales sleep quality, sleep latency, sleep efficiency and daytime sleepiness reached medium effect sizes, and the scale sleep duration had a small effect.

PSQI: descriptive statistics and comparisons for pre- and post-measurement

Notes: Significant differences ( P <0.05) are displayed in bold characters. Higher values indicate worse sleep quality.

Abbreviations: PSQI, Pittsburgh Sleep Quality Index; M, mean; SD, standard deviation.

The results for the diagnostic sleep logs are presented in Table 11 . Compared to pre-measurement level, the SWIS participants reported a reduced number of night-time awakenings at post-measurement with a medium effect size ( d =0.67). The remaining subjective sleep variables from the diagnostic sleep log did not change significantly.

Descriptive statistics of and comparisons between pre- and post-measurement of the diagnostic sleep logs. Regeneration scores are displayed on a six-point Likert scale (N=13)

Notes: Duration of night waking describes the discrepancy between time in bed and the sleep duration. Significant differences ( P <0.05) are displayed in bold characters. Higher regeneration scores indicate a better regeneration.

Descriptive statistics and differences between pre- and post-measurement for the actigraphs are displayed in Table 12 . Statistically significant tendencies were discovered for sleep-onset latency, which decreased from 38.4 minutes to 13.8 minutes. This equates to a medium effect size ( r =−0.31). Additionally, clinically significant improvements were found for duration of night wakings (<30 minutes at posttest) and sleep efficiency (>95% at posttest).

Actigraphy: descriptive statistics and comparisons between pre- and post-measurement in hours. Sleep efficiencies are displayed in percentages (N=15)

Notes: Duration of night waking describes the discrepancy between time in bed and the sleep duration. Clinically significant results are displayed in bold.

Average daytime sleepiness decreased from pre- (M =9.92, SD =5.02) to post-measurement (M =8.25, SD =4.83), although the difference was not significant ( t (18) =0.86, P =0.40).

The average chronotype was neutral during pre- (M =45.42, SD =10.34) and post-measurement (M =47.75, SD =8.36). A nonsignificant development toward morningness was detected ( t (11) =−1.69, P =0.12).

The participants’ tendency to ruminate decreased significantly ( Z (19) =−2.60, P =0.009, r =−0.42) from pre- (M =46.53, SD =9.95) to post-measurement (M =40.37, SD =11.18). In addition, participants reported significantly reduced focusing ( t (18) =4.69, P =0.000, d =1.33) after the training (M pre =33.00, SD pre =5.80; M post =25.63, SD post =7.85).

Descriptive statistics and differences between pre- and post-measurement for the convictions about sleep are displayed in Table 13 . The MZS sum score did not change significantly from pre- to post-measurement. Similar results were found for the two subscales convictions about long-term consequences and biological causes for sleep disorders. However, the participants reported a reduction of dysfunctional beliefs concerning daytime productivity with a small effect size ( d =0.32).

MZS: descriptive statistics and comparisons between pre- and post-measurement (N=19)

Abbreviations: MZS, Meinungen-zum-Schlaf-Fragebogen (cognitions about sleep); M, mean; SD, standard deviation.

The purpose of the current study was to examine the feasibility of the SWIS sleep training, a specialized treatment for college/university students. It addresses insomnia symptoms, nightmares and irregular sleep–wake cycles. First indications of acceptance, feasibility and effectiveness were investigated with several instruments including sleep logs, actigraphy and questionnaires.

Overall, participants showed a high acceptance of the SWIS sleep training that encompassed nearly all subscales. The CBT-I elements were rated as very good, whereas the HT-I elements received a slightly lower but still acceptable rating. On average, participants graded the training as good to moderate. The trainers displayed a high to very high acceptance of the SWIS content, hypnotherapy, trainer aptitude and group dynamics. Based on these results, the first hypothesis can be confirmed.

The training’s feasibility was reflected in the participants’ high attendance and low dropout rates. Similarly, the trainers evaluated the frame conditions, instructions and co-trainers positively, likewise indicating SWIS feasibility from the trainers’ perspective.

After the SWIS training, sleep improved on nearly all outcome measures. Students reported a significantly better sleep quality, including shorter sleep latency and less daytime sleepiness according to the PSQI. The sleep log data showed a reduced number of night-time awakenings after the treatment. As an objective measure, actigraphy results showed tendencies of reduced sleep-onset latency and clinically significant improvements for the duration of night wakings and sleep efficiency. Daytime sleepiness according to the ESS and the chronotype did not change significantly from pre- to post-measurement. However, participants showed cognitive changes as a reduction of rumination and focusing as well as a tendency to have less dysfunctional beliefs about daytime productivity. All in all, the students’ sleep was improved after the SWIS training.

In general, prior to treatment, the students reported an impaired sleep quality and sleep problems, most commonly insomnia symptoms. This is in accordance with current research that indicates reduced sleep quality and more sleep disorders in university students in comparison to the general population. 3

After SWIS, the sleep-onset latency decreased in both actigraphy results and subjective ratings (PSQI), which is in accordance with Lichstein et al. 49 Most notable, sleep was improved on a subjective basis in sleep questionnaires, but also on more detailed instruments as sleep logs and objective actigraphy. However, some instruments that measured the same aspects of sleep did not concur. These differences might be explained by the fact that students with sleep disorders, especially insomnia, often have a distorted perception of sleep. This misperception leads to an overestimation of their sleep-onset latency and an underestimation of their sleep duration. 50 Disparities between the ESS and the daytime sleepiness from the PSQI can be explained by the different accuracy levels. While the PSQI uses only one item to measure daytime sleepiness, the ESS is a more comprehensive scale with seven items. In any case, daytime sleepiness is more likely to change in patients who suffer from other sleep disorders such as obstructive sleep apnea or narcolepsy than in patients with insomnia. 51 The lack of significant changes concerning the students’ chronotypes may be attributable to the fact that the chronotype is a relatively stable construct in young adults and that changes might need more time. 52

Cognitive Behavioral Therapy for Insomnia

The content of the SWIS sleep training including CBT-I and HT-I converges with other programs regarding stimulus control, sleep hygiene, relaxation training and cognitive therapy. Based on theoretical constructions, the reflexion of our training is in line with the results of Taylor et al: 53 both trainings were accepted by the participants and improved sleep quality as well as sleep latency. Despite these similarities, considerable differences between the CBT-I implemented by Taylor and SWIS emerge. While SWIS does not contain bedtime restriction, it offers a great variety of study-related strategies that are not present in other sleep treatments. These strategies include a focus on stress management, sleep in exam periods, problem solving and the HT-I elements.

In contrast to Taylor et al, the SWIS treatment led to improvements in objective sleep measures (actigraphy), like a reduced duration of night wakings, reduced sleep onset latency and higher sleep efficiency. Furthermore, the participants of the SWIS training reported an improved daytime sleepiness according to PSQI. On the one hand, the differences in daytime sleepiness may be caused by methodical disparities, as Taylor et al used a specific questionnaire to assess daytime sleepiness (ESS), while the current study used the ESS as well as the PSQI subscale. On the other hand, a study that investigated side effects of psychotherapy found that sleep restriction results in objectively reduced total sleep time, increased daytime somnolence and impaired vigilance. 54 Therefore, the additional positive effects of SWIS on objective measures and daytime sleepiness may be attributable to the elements that are missing (ie, stress management) as well as the elements that are included in Taylor’s CBT-I (ie, bedtime restriction).

Most important, the CBT-I concept of Taylor was designed to treat only insomnia, while the SWIS sleep training treats insomnia disorder, nightmares and irregular sleep–wake type according to DSM-5, 34 enabling a wider range of implementation and effectiveness.

Strengths and limitations

The most important advantages of the SWIS sleep training are the great applicability to different sleep disorders and the focus on university students’ lives. Methodological strengths include the additional application of objective measures of sleep and the anonymity of the acceptance assessments.

As this study was a pilot study, the most obvious limitation is the small sample size of only 27 participants. Two aspects relativize this limitation. Firstly, the current study is a feasibility study with the aim of testing the program’s acceptance and seeking first indications of effectiveness. Furthermore, despite the small sample size, significant results for all hypotheses were obtained. Another factor is the quasi-experimental design. Due to the missing control group, the positive effects may be attributable to other factors than SWIS. Finally, the lack of a follow-up measurement impeded the investigation of long-term effects.

Conclusion and future prospects

The current feasibility study showed a high acceptance and effectiveness of the SWIS sleep training for university students. The SWIS sleep training scored well on participant and trainer acceptance as well as feasibility. Furthermore, the students’ sleep quality improved significantly, making it a feasible program for university context.

These results strongly support further investigation of the SWIS sleep training, especially regarding important aspects of college students’ life such as study-related impairments and cognitive performance. These could encompass the ability to concentrate as well as different aspects of memory, learning and other neuropsychological faculties. Future evaluations should include the methodological changes indicated by the limitations section, that is, a control group design, follow-up assessments and a larger sample size to expand the generalization of results. Lastly, the improvements in the sleep variables may lead to reduced mental health issues (ie, depression, anxiety, somatization, etc) and a better life quality, which should be assessed in future studies.

Acknowledgments

The authors would like to thank Neele Busse for supporting the diagnostic process and being a co-trainer. Furthermore, they would like to thank Nina Schäfer for helping with the analysis of the actigraphy data. They also acknowledge the support for Article Processing Charge by the Deutsche Forschungsgemeinschaft and the Open Access Publication Fund of Bielefeld University.

Abbreviations

Author contributions

All authors contributed toward data analysis, drafting and critically revising the paper and agree to be accountable for all aspects of the work.

The authors report no conflicts of interest in this work.

Problem of Sleep Deprivation Cause and Effect Essay

Introduction.

• What is Sleep Deprivation?

Causes of Sleep Deprivation

Effects of sleep deprivation, managing sleep deprivation, works cited.

The functioning of the human body is influenced by a number of factors, which are mainly determined by the health status of an individual. Oftentimes, people seek medication when the body deviates from its normal and usual functioning mechanisms. Through different activities and processes, the body is able to use energy and replenish itself. Sleeping is one of the activities that has a direct effect on the functioning of the body.

This sleep deprivation essay explores how the functioning of the human body is influenced by various factors, primarily determined by an individual’s health status. While most people do not understand the implications of sleep, human effectiveness solely depends on the amount of time dedicated to sleeping. However, for various reasons, people fail to get enough sleep daily, weekly, or on a regular basis.

What Is Sleep Deprivation?

This cause and effect of sleep deprivation essay defines sleep deprivation as a condition occurring among human beings when they fail to get enough sleep. Sleep deprivation is defined as a condition that occurs when human beings fail to get enough sleep. Many experts argue that sleep deficiency is widespread even though most people do not consider it to be a serious issue, which affects their (Gaine et al.). Sleep deprivation has become a major problem in the United States, with almost 47 million suffering from the condition (Wang and Xiaomin). This lack of sleep can lead to a variety of physical and mental health issues, impacting daily functioning and quality of life.

The present essay about sleep deprivation defines sleep deprivation as a condition that occurs among human beings when they fail to get enough sleep. Many experts argue that sleep deficiency is widespread even though most people do not consider it to be a serious issue that affects their lives. Sleep deprivation has become a major problem in the United States, with almost forty-seven million suffering from the condition (Wang and Xiaomin). Among other reasons, one may get insufficient sleep in a day as a result of various factors. Some people sleep at the wrong time due to busy daily schedules, while others have sleep disorders, which affect their sleeping patterns. The following segment of the paper discusses the causes of deprivation.

Sleep deprivation may occur as a result of factors that are not known to the patients. This is based on the fact that sleep deprivation may go beyond the number of hours one spends in bed. In some cases, the quality of sleep matters in determining the level of deprivation.

In this context, it is possible for one to be in bed for more than eight hours but suffer from the negative effects of sleep deprivation. Whilst this is the case, there are people who wake every morning feeling tired despite having spent a recommended number of hours in bed (Griggs et al.14367).

Sleep deprivation can be caused by medical conditions, which may include but are not limited to asthma, arthritis, muscle cramps, allergies, and muscular pain. These conditions have been classified by researchers as common medical conditions that largely contribute to most of the cases of sleep deprivation being witnessed in the United States.

Similarly, these medical conditions have a direct impact on not only the quality but also the time one takes in bed sleeping. It is worth noting that sometimes people are usually unconscious to realize that their sleep is not deep enough (Wang and Xiaomin). This also explains the reason why it is not easy for a person to recall any moment in life when he or she moved closer to waking up.

Treatment of cases like sleep apnea is important because it affects the quality of sleep without necessarily awakening the victim. This is because medical surveys have revealed fatal effects of sleep apnea, especially on the cardiovascular system. Besides these, one is likely to experience breathing difficulties caused by insufficient oxygen.

Even though the treatment of sleep deprivation is important, it has been found that some drugs used to treat patients may worsen the case or lead to poor quality of sleep. It is, therefore, necessary for the doctor to determine the best drugs to use. Discussions between doctors and victims are imperative in order to understand patients’ responses (Conroy et al. 185).

Sleep deprivation is also caused by sleep cycle disruptions, which interfere with the fourth stage of sleep. Oftentimes, these disruptions are described as night terrors, sleepwalking, and nightmares.

Though these disorders are known not to awaken a person completely, it is vital to note that they may disrupt the order of sleep cycles, forcing a person to move from the fourth stage to the first one. Victims of these disruptions require attention in order to take corrective measures.

In addition, there are known environmental factors which contribute to several cases of sleep deprivation. However, doctors argue that the impact on the environment is sometimes too minimal to be recognized by people who are affected by sleep deficiency (Gaine et al.). In other words, these factors affect the quality of sleep without necessarily arousing a person from sleep.

Common examples include extreme weather conditions, like high temperatures, noise, and poor quality of the mattress. As a result, they may contribute to a person’s awakening, depending on the intensity when one is sleeping.

Moreover, the impact of these factors may develop with time, thus affecting one’s quality of sleep. In addition, most of the environmental factors that contribute to sleep deprivation can be fixed easily without medical or professional skills. Nevertheless, the challenge is usually how to become aware of their existence.

Lastly, sleep deprivation is caused by stress and depression, which have been linked to other health disorders and complications. Together with some lifestyles in America, these factors are heavily contributing to sleep deficiency in most parts of the world. Even though they might not be acute enough to awaken an individual, their cumulative effects usually become significant.

There are countless stressors in the world that affect youths and adults. While young people could be concerned with passing exams, adults are normally preoccupied with pressure to attain certain goals in life. These conditions create a disturbed mind, which may affect a person’s ability to enjoy quality sleep.

Sleep deprivation has a host of negative effects which affect people of all ages. The commonest effect is stress. Most people who suffer from sleep deficiency are likely to experience depression frequently as compared to their counterparts who enjoy quality sleep (Conroy et al. 188). As a result, stress may lead to poor performance among students at school.

Research has revealed that students who spend very few hours in bed or experience disruptions during sleep are likely to register poor performance in their class assignments and final exams. Additionally, sleep deprivation causes inefficiency among employees.

For instance, drivers who experience this disorder are more likely to cause accidents as compared to those who are free from it (Griggs et al.14367). This is based on the fact that un-refreshed people have poor concentration and low mastery of their skills.

Besides stress and anxiety, sleep deprivation has a wide-range of health-related effects. For instance, medical experts argue that people who spend less than six hours in bed are likely to suffer from high blood pressure. Quality sleep gives the body an opportunity to rest by slowing down the rate at which it pumps blood to the rest of the body (Wang and Xiaomin).

Inadequate sleep implies that the heart has to work without its normal and recommended rest. Additionally, sleep deprivation is known to affect the immune system. People who experience this disorder end up with a weakened immune system, leaving the body prone to most illnesses. This reduced immune response accumulates and may become fatal with time.

Sleep paralysis is also a common effect of inadequate sleep. This is due to disruption of the sleep cycle. It primarily occurs when the body is aroused during the fourth stage of the sleep cycle. In this case, the body is left immobile as the mind regains consciousness. Due to this conflict, one may experience pain and hallucinations.

Based on the negative effects of sleep deprivation, there is a need to manage this disorder among Americans. Firstly, it is necessary for people to seek medical advice concerning certain factors which could be contributing to this condition, like stress and infections (Wang and Xiaomin).

Proper counseling is also vital in stabilizing a person’s mental capacity. Physical exercises are also known to relieve a person from stressful conditions, contributing to sleep deficiency. Lastly, it is essential to ensure that the environment is free from noise and has regulated weather conditions.

Sleep deprivation remains a major problem in America, affecting millions of people. As discussed above, sleep deprivation is caused by a host of factors, ranging from environmental to health-related issues. Moreover, sleep deficiency has countless effects, most of which may become fatal in cases where the disorder is chronic.

Conroy, Deirdre A., et al. “ The Effects of COVID-19 Stay-at-home Order on Sleep, Health, and Working Patterns: A Survey Study of US Health Care Workers. ” Journal of Clinical Sleep Medicine , vol. 17, no. 2, Feb. 2021, pp. 185–91.

Gaine, Marie E., et al. “ Altered Hippocampal Transcriptome Dynamics Following Sleep Deprivation. ” Molecular Brain, vol. 14, no. 1, Aug. 2021.

Griggs, Stephanie, et al. “ Socioeconomic Deprivation, Sleep Duration, and Mental Health During the First Year of the COVID-19 Pandemic. ” International Journal of Environmental Research and Public Health, vol. 19, no. 21, Nov. 2022, p. 14367.

Wang, Jun, and Xiaomin Ren. “ Association Between Sleep Duration and Sleep Disorder Data From the National Health and Nutrition Examination Survey and Stroke Among Adults in the United States .” Medical Science Monitor , vol. 28, June 2022.

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Bibliography

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• About Sleep
• Sleep Facts
• Sleep Resources

FastStats: Sleep in High School Students

• The Youth Risk Behavior Survey (YRBS) looks at how much sleep U.S. high school students get.
• The percentage of high school students who do not get enough sleep in the United States varies over time and by sex, state, age, and racial and ethnic group.

• The Youth Risk Behavior Survey (YRBS) measures health-related behaviors, including sleep, among high school students.
• High school students who take part in the YRBS are asked: "On an average school night, how many hours of sleep do you get?"
• The recommended amount of sleep for high school students is 8 hours each day.
• High school students who do not get 8 hours of sleep each day are considered to have insufficient sleep (also called short sleep duration).

Quick stats

Trends in insufficient sleep, 2009–2021.

The percentage of high school students who do not get enough sleep increased from 2009 to 2021. More female students than male students reported not getting enough sleep during this period.

Insufficient sleep by state, 2021

The percentage of high school students who do not get enough sleep varies by state. In 2021, it ranged from 71% in South Dakota to 84% in Pennsylvania.

Insufficient sleep among high school students, 2021

The percentage of high school students who do not get enough sleep was highest in certain groups, including:

• Female students (80%)
• 12th grade students (84%)
• Black students (84%)

Data sources

CDC National Youth Risk Behavior Survey (YRBS), 2009–2021.

• Youth Online: High School Youth Risk Behavior Surveillance System (YRBSS)
• Healthy People 2030
• National Survey of Children's Health

By sharing information and resources, CDC raises awareness about the importance of sleep health and its effect on public health.