Sleep Debt and Academic Success in Relation to School Type...stress levels, GPAs, and average hours...
Transcript of Sleep Debt and Academic Success in Relation to School Type...stress levels, GPAs, and average hours...
Sleep Debt and Academic Success in Relation to School Type
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Abstract How do hours of sleep and school type impact the academic success of high school
students? According to the CDC, 1 out of 10 people are affected by sleep deprivation. Two independent variables were tested, public and STEM high school students. Questions about their stress levels, GPAs, and average hours of sleep were asked of the participants using an online survey at http://www.quia.com/sv/620383.html. The study shows that there is a weak negative correlation between Sleep and GPA. The study also shows that students who feel pressure from their parents to succeed tend to have higher GPAs compared to students who do not. An ANOVA test supported the null hypothesis; however observations can still be made of the trends seen. According to the data getting more sleep does not mean your GPA will necessarily improve and students who are encouraged to succeed are more likely to have higher GPAs. The issue is more about time usage during waking hours than actual number of hours slept. It is evident that students must decide if they are willing to trade the benefit of sleep for the benefit of more time to do work. So, while sleeping more will not inherently improve your grades, it cannot be concluded that sleep is unimportant. Further study should evaluate quality of time management as well as sleep.
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Introduction According to the Centers for Disease Control and Prevention more than 1 in 10 people
did not get enough sleep or rest on any night in the past 30 days. The purpose of this project is to
determine if there is a correlation between sleep and study habits among high school and college
students and if their educational environment affects these results. The basic rationale is that
sleep is an important biological process that heals the body and refreshes the mind. Today sleep
deprivation is a major issue. Teens and young adults are especially impacted by sleep deprivation
as perceived workload, stress, and peer pressure keep them awake. Sleep deprivation is
associated with a wide variety of disorders and health problems that may impair behavior,
growth and development, and basic functionality.
Sleep deprivation can contribute to health issues like: heart failure, stroke, obesity,
mental impairment, injury from accidents, attention deficit disorder (add), and psychiatric
problems, including depression and other mood disorders. A compounding lack of sleep has been
proven to lead to a significantly decreased quality of life. One of the primary goals of this project
is to determine the effect of environment; specifically the learning and/or work environment, on
the individuals sleep patterns.
The research hypothesis for this experiment was that there will be a greater negative
correlation between sleep debt (negative hours of sleep) and academic success in Ivy League
University students and the null hypothesis is that there will be no correlation between sleep
debt, academic success, or school type.
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Literature Review “Neurocognitive consequences of sleep deprivation” by Durmer, J. S., & Dinges, D. F
highlights some detrimental day time behaviors caused by sleep deprivation. Issues like micro-
sleeps, sleep attacks, and lapses in cognition increase with sleep loss as a function of state
instability are discussed. Serious Issues are described involving previous sleep studies are
discussed within this work. Deficits in daytime performance due to sleep loss are experienced
universally and associated with a significant social, financial, and human cost.. Sleep deprivation
studies repeatedly show a variable (negative) impact on mood, cognitive performance, and motor
function due to an increasing sleep propensity and destabilization of the wake state. Specific
neurocognitive domains including executive attention, working memory, and divergent higher
cognitive functions are particularly vulnerable to sleep loss. In humans, functional metabolic and
neurophysiological studies demonstrate that neural systems involved in executive function (i.e.,
prefrontal cortex) are more susceptible to sleep deprivation in some individuals than others.
Recent chronic partial sleep deprivation experiments, which more closely replicate sleep loss in
society, demonstrate that profound neurocognitive deficits accumulate over time in the face of
subjective adaptation to the sensation of sleepiness. Sleep deprivation associated with disease-
related sleep fragmentation (i.e., sleep apnea and restless legs syndrome) also results in
neurocognitive performance decrements similar to those seen in sleep restriction studies.
Performance deficits associated with sleep disorders are often viewed as a simple function of
disease severity; however, recent experiments suggest that individual vulnerability to sleep loss
may play a more critical role than previously thought.
In their study, “Functional consequences of sustained sleep deprivation in the rat”
Everson, C. A. aimed to discover the physiological changes that occur as a result of sleep
deprivation by testing lab rats. In the rat, the course of prolonged sleep deprivation has a
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syndromic nature resulting in a steady decline of health. The study shows the change in various
conditions of the rate including metabolic brain activity. Metabolic mapping of the brain
revealed dissociation between the energy metabolism of the brain and that of the body. Sleep
deprivation's effects on cerebral structures are heterogeneous and unidirectional toward
decreased functional activity. the four major abnormalities identified in the sleep deprived rats
were -- (1) a deep negative energy balance and associated malnutrition; (2) heterogeneous
decreases in cerebral function; (3) low thyroid hormone concentrations; and (4) decreased
resistance to infection - can be viewed as having an early origin during the sleep deprivation
process to signify the foremost pathogenic situation to which the other abnormalities might be
secondarily related. The findings therefore remain unclear for a single function for sleep, but can
support accepted roles for sleep in thermoregulation, energy conservation, immune system
integrity, and tissue restoration.
This study, Effects of prolonged sleep deprivation on local rates of cerebral energy
metabolism in freely moving rats, focused on how the brain, a rat’s brain in this experiment,
changed and the rate of metabolism. It was conducted 1-2 days and the results showed an
unidirectional change toward unidirectional toward decreased energy metabolism, primarily in
regions associated with mechanisms of thermoregulation, endocrine regulation, and sleep.
However, correspondence was found between the hypo-metabolic brain regions and some
aspects of peripheral symptoms.
In this review, Sleep and circadian rhythms: Key components in the regulation of energy
metabolism, the researchers Laosky, A. D., Bass, J., Kohsaka, A., & Turek, F. W. present
evidence from human and animal studies to evaluate their hypothesis that sleep and circadian
rhythms have direct impacts on energy metabolism, and represent important mechanisms
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underlying the major health epidemics of obesity and diabetes. The first part of this review
focused on studies that support the idea that sleep loss and obesity are ‘‘interacting epidemics.’’
The second part discussed recent evidence that the circadian clock system plays a fundamental
role in energy metabolism at both the behavioral and molecular levels. These lines of research
are still recent, but nevertheless, have provided an experimental framework that could prove
instrumental in understanding metabolic health and disease.
Why we sleep: The temporal organization of recovery goes into detail on the neural
processes during wake, NREM Sleep, and REM sleep with detailed diagrams of brain activity. It
explains the effects of sleep illnesses like insomnia. Naturally the paper’s goal is to discovery the
purpose for sleep and includes much information on the effects sleep has on the body. In the
paper it is stated that sleep is necessary, though it is unclear at this time, why it is required and
maintained by evolution. Recent work suggests multiple roles, a correlation with synaptic
plasticity changes in the brain, and widespread changes in gene expression, not unlike what has
been recently discovered in circadian biology. Functional data are however still largely lacking,
and studies such as functional genomic screens in model organisms, comparative sleep
neuroanatomy through phylogeny, and the study of molecular changes within specific wake,
REM sleep, and NREM sleep regulatory systems are needed. The resilience of behavioral sleep
in evolution and after experimental manipulations may be secondary to the fact that it is
grounded at the molecular, cellular, and network levels.
The entirety of “Never enough sleep: A brief history of sleep recommendations for
children” discusses patterns of recommended sleep for children. The aim of this study was to
describe historical trends in recommended and actual sleep durations for children and
adolescents, and to explore the rationale of sleep recommendations. The paper is basically an
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extensive literature review over the topic designed to identify recommendations for children’s
sleep requirements and data reporting children’s actual total sleep time. A thematic analysis was
conducted to determine the rationale and evidence-base for recommendations. Thirty-two sets of
recommendations were located dating from 1897 to 2009. On average, age-specific
recommended sleep decreased at the rate of –0.71 minute per year. This rate of decline was
almost identical to the decline in the actual sleep duration of children (–0.73 minute per year).
Recommended sleep was consistently ∼37 minutes greater than actual sleep, although both
declined over time. In conclusion the study suggested that inadequate sleep was seen as a
consequence of “modern life,” associated with technologies of the time and that no matter how
much sleep children are getting, it has always been assumed that they need more.
Oka, Y., Suzuki, S., & Inoue, Y assessed the impact of bedtime activities and sleep
environment on sleep/wake patterns. 509 Japanese elementary school students (6–12 years of
age; 252 males and 257 females) participated in thier study, Bedtime activities, sleep
environment, and sleep/wake patterns of japanese elementary school children. Most activities
involving electronics had a negative impact on the sleep/wake patterns. The presence of a device
in the child’s room increased the activity before bed. Curfews later than 8 p.m. were shown to
have a negative effect as well. This information can help health care professionals inform parents
of the detrimental effects of these activities on sleep.
The goal of the study, Online assessment of sustained attention following sleep
restriction, was to assess the feasibility of conducting home-based sleep restriction studies with
actigraphic monitoring of sleep and a new online continuous performance test (OCPT). 34
female university undergraduate students repeated home assessments using self-administered
OCPT following a regular night of sleep (8 h or more) and following sleep restriction (4 h of
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sleep) in a within–between subjects counter-balanced design. Actigraphy was used to monitor
sleep. OCPT sessions were scheduled in the morning and the evening of days following normal
and restricted sleep. OCPT measures demonstrated acceptable test–retest reliability. Actigraphic
monitoring revealed good compliance with sleep requirements, and reported alertness reflected
significant effects of sleep manipulation (p < .0001). In comparison to performance following an
8-h sleep night, sleep restriction to 4 h was associated with a significant increase in omission
errors in the high-target section of the test (p < .0005) and with a significant increase in omission
errors in the low-target section of the test (p < .01). The researchers concluded that these
preliminary results support the feasibility of conducting home-based sleep restriction studies and
the validity of the online version of the OCPT, suggesting that it may serve as a sensitive tool for
assessment of sleep restriction/deprivation
Quality of sleep among university students effects of nighttime computer and television
use was a study based on subjective questionnaires that assessed nighttime habits of television
viewing and Internet use during weekdays and perceived sleep quality among university
students. Sleep perception was measured using the Pittsburgh Sleep Quality Index (PSQI). The
study group comprised 710 university students aged 17-25 years. Analysis of sleep perception in
relation to internet use revealed that 58.06% of subjects who accessed the internet between 19:00
and 21:00 slept poorly; 71.43% between 19:00 and 22:00; 73.33% between 19:00 and 24:00; and
52.38% between 19:00 and 03:00 (p=0.0251). Concerning the relationship between television
exposure and perceived sleep, the groups did not differ from each other (p=0.9303). This study
showed that internet use between 19:00 and 24:00 increases the risk of poor sleep among young
adults, in comparison with television viewing times.
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Research Methodology First data pertaining to the project was gathered and analyzed. The information gathered
was used to write the literature review. The information was then used to create a survey. The
survey was alpha tested to confirm the viability of the questions. When negative feedback was
received the material would be reviewed again and the question would be rewritten. An email
was then written detailing the primary goal of the study along with a link to the
survey, http://www.quia.com/sv/620383.html. The email was then distributed to high school
teachers. The educators then distributed the survey to their students. Each student participated in
the online survey and their results were analyzed using an ANOVA test. Conclusions were then
formed based on correlations between GPA, school type, and average hours of sleep.
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Data Analysis The Confidence level for this experiment was 95%, p < 0.05 indicating significance
One-way ANOVA:GPA versus School Type
• P =0.52
• Accept the null hypothesis: School type does not have an influence on GPA.
• One-way ANOVA: Average Hours of Sleep versus School Type
• P = 0.71
• Accept the null hypothesis: School type does not have an influence on Average Hours of Sleep
• One-way ANOVA: Average Hours of Sleep versus Gender
• P =0.959
• Accept the null hypothesis: Gender does not have an influence on Average Hours of Sleep
In the preceding graph you can see a weak negative correlation between Average Hours Sleep and GPA. This indicates that sleep has either a negative effect on Grade Point averages or has little to no impact.
Average Hours of Sleep
GPA
98765432
4.0
3.5
3.0
2.5
Scatterplot of GPA vs Average Hours of Sleep
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In the Graph above you can see there isn’t a great deal of difference between the average GPAs of Males versus the average age of Females. Females though can be said to have a wider range of sleep hours than males.
3.61 3.24
3.63 3.427941176 3
3.5125 3.355 3.55
1 3.00 5.00 7.00 9.00
Aver
age
GPA
s
Average Hours of Sleep
GPA in Relation to Sleep and Gender
Females Males
3.75 3.7
3.4 3.433333333
3.316666667
3.573684211
1 3.00 5.00 7.00 9.00
Aver
age
GPA
s
Average Hours of Sleep
GPA in Relation to Sleep and School Type Amoung Males
STEM School Males Public School Males
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This graph shows that males in public schools are more likely to have lower GPAs and are also likely to get more sleep. It is interesting to note that public school students who ordinarily get about 7 hours of sleep have a higher average GPA than those of STEM school students who get the same amount of sleep.
This graph shows that there isn’t a great deal of variation between females GPAs. It is interesting to see that only STEM School Females had fewer than 2 hours of sleep where the only public school females got 8 or more hours.
3.61 3.566666667 3.516666667 3.24 3.6365 3.408928571
3
1 3.00 5.00 7.00 9.00
Aver
age
GPA
s
Average Hours of Sleep
GPA in Relation to Sleep and School Type Amoung Females
STEM School Females Public School Females
Average Hours of Sleep
GPA
98765432
4.0
3.5
3.0
2.5
NoYes
the Parefrom
PressureIs There
Scatterplot of GPA vs Average Hours of Sleep
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This graph could be used to support the hypothesis that Students who are externally motivated are more likely to have higher GPAs and are also more likely to get more sleep.
Sources of Error
It is possible for the participants to lie. Any incorrect answers would cause the trend to deviate from the actual trend. Disproportionate representation is another possible source of data distortion.. There were more participants from public schools and all of the public school students were upperclassmen. There were more female participants. This is a problem because it does not represent the entire population and only expresses the data given by specific subgroups.
Conclusions Though the results cannot be considered statistically significant the trends seen show a
slight negative correlation between Sleep and GPA and Students who receive encouragement to succeed are more likely to have higher GPAs. This shows that students can overcome the negative effects of sleep deprivation and still have good grade point averages. The study does not show the effects of Sleep deprivation on heath however so getting less sleep does not necessarily beneficial.
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Everson, C. A., Smith, C. B., & Sokoloff, L. (1994). Effects of prolonged sleep deprivation on local rates of cerebral energy metabolism in freely moving rats.The Journal of Neuroscience, 14(11), 67869-6778. Retrieved from www.jneurosci.org/content/14/11/6769.full.pdf
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Glossary
Thalamus The thalamus is a midline symmetrical structure within the brains of vertebrates including humans, situated between the cerebral cortex and midbrain. Its function includes relaying sensory and motor signals to the cerebral cortex, along with the regulation of consciousness, sleep, and alertness
Prefrontal Cortex The prefrontal cortex (PFC) is the anterior part of the frontal lobes of the brain, lying in front of the motor and premotor areas. The basic activity of this brain region is considered to be orchestration of thoughts and actions in accordance with internal goals.
Neuroimaging Neuroimaging includes the use of various techniques to either directly or indirectly image the structure, function/pharmacology of the brain. It is a relatively new discipline within medicine and neuroscience/psychology.
Psychomotor learning Psychomotor learning is the relationship between cognitive functions and physical movement. Psychomotor learning is demonstrated by physical skills such as movement, coordination, manipulation, dexterity, grace, strength, speed; actions which demonstrate the fine motor skills such as use of precision instruments or tools, or actions which evidence gross motor skills such as the use of the body in dance, musical or athletic performance.
Behavioral neuroscience Behavioral neuroscience, also known as biological psychology,[1] biopsychology, or psychobiology[2] is the application of the principles of biology (in particular neurobiology), to the study of physiological, genetic, and developmental mechanisms of behavior in human and non-human animals. It typically investigates at the level of nerves, neurotransmitters, brain circuitry and the basic biological processes that underlie normal and abnormal behavior.
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Appendix A
Experimental Design:
Research Hypothesis: There will be a greater negative correlation between sleep debt (negative hours of sleep) and academic success in Ivy League University students.
Null Hypothesis: There will be no correlation between sleep debt, academic success, or school type.
IV: School Type Public High School
STEM High School
Private High School
Home school
Home school (Online)
State University
Ivy League University
Liberal Arts College
Military Academy
100 100 100 100 100 100 100 100 100 DV: The relationship between sleep debt and academic success. Constants: Age ranges of participants, nationality of participants, survey questions. Control: No control is needed, this experiment is for comparison between the established groups.
Slope intensity and correlation will be measured. Slope intensity=absolute value of slope, higher values=steeper slopes.
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Appendix B Materials
• Internet connection • Quia survey • Microsoft Excel Program • Microsoft Word Program • Microsoft PowerPoint Program
Budget: Total Cost of Reusable Materials & New Equipment Ordered: $ ___0______ Total Cost of Disposable Materials Needed (cannot be reused): $ ___0_____
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Detailed Procedures
Analyze data using school type, GPA, and sleeping
habits
Crate survey concerning sleep
Testing Methodology
Alpha Test Questions
Receive feed back from
Alpha- participants
Positive results N
egative results
Is the feedback
positive or
Rewrite questions
Review m
aterial and feed back
Find flaws in the questions
Post survey on Quia
Send link to high school teachers and college
professors
Advertise the survey on Social N
etworking sites
Make a graph for both the
median m
ean and mode of
both sets of data
Was the
hypothesis supported?
Yes N
o
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1. Week 1 and 2 work on survey and alpha test in class.
2. Week 3 Distribute survey, http://www.quia.com/sv/620383.html to high school and
college students ages 13-24. The IV level for this study Is School and Sleep dept. The DV
is GPA.
3. Participants will then complete the survey.
4. The survey results will then be analyzed using an ANOVA test and Microsoft excel.
Correlations and other patterns will be observed and recorded.
5. Reject or accept hypothesis based on analysis.
6. Write conclusions
Safety
All participants will remain anonymous. No personal information will be asked for. There is no perceived danger in participating in the study. The entire study will take place online.
Materials • Internet connection • Quia survey • Microsoft Excel Program • Microsoft Word Program • Microsoft PowerPoint Program