Statistical Study on the Factors Affecting the Sleeping Disorder during Exams among the Students of University of the Punjab
BS (Hons.) Statistics
Roll No. 43-14
Mam Nadia Saeed
College of Statistical and Actuarial Sciences
University of the Punjab, Lahore
O My Lord!
Increase me in my Knowledge!
O Allah! I ask you for knowledge that is of benefit
All praise and thanks to Almighty Allah, the creator of the universe who is the supreme authority who guides the way and gives the courage to complete the task with His blessings.
My thoughts enable me to His last messenger Holy prophet (S.A.W) who enable us to recognize creator and to understand the philosophy of life.
This research would not be possible without the encouragement and guidance of number of people.
In addition, I am very grateful to the institute the University of the Punjab, College of Statistical and Actuarial Sciences, principle of college Dr. Shahid Kamal and all the professor and lecturers.
I acknowledge thanks and sincere gratitude to my respected, gracious highly learned and distinguish supervisor Ms. Nadia Saeed for her helpful comments, for her keen interest and inspiring guidance that enable me throughout research.
I would like to express my deepest gratitude to my Parents whose affection, love, encouragement and prays of day and night make me able to get such success and honour. They always lightened my burdens, always stood by my side in every hurdle of my life. Along with all, my friends, siblings especially Dr. Mehak Irfan whose guidance and constant support helped me throughout my work.
Last but not least, I am thankful to all those students of University, who actively participated in my research work without whom this research would not have been possible.
Every challenging work needs self-efforts as well as guidance of elders especially those who are very close to our heart.
My humble effort I dedicate to my sweet and loving Parents, whose affection, love, encouragement and prays of day and night make me able to get such success and honour.
This is to certify that thesis entitled “A statistical study on factors affecting the sleeping disorder during exams among the students of University of the Punjab”. It is submitted by Fara Irfan in partial fulfilment of the requirement for the award of degree of BS (Hons.) statistics to College of Statistical and Actuarial Sciences, University of the Punjab, is a record of the candidate’s own work carried out under my supervision. The matter embodied in this thesis is original and has not been submitted for the award of any other degree.
Ms. Nadia Saeed
This is to certify that the researcher work which I am submitting has not already been submitted and shall not in future be submitted for obtaining similar degree from any other university.
Moreover, this thesis is submitted to the College of Statistical and Actuarial Science, University of the Punjab, Lahore, in partial fulfilment of the requirements for the degree of BS (Hons.) Statistics.
Roll No. 43-14
The present research is conducted to study the sleeping disorder in exams among the students of University of the Punjab, Lahore. The main aim of the study is to explore the factors affecting the sleeping disorders. The target population is comprised of the students in the University of the Punjab. A sample of 276 students is selected by using convenience sampling technique. Questionnaire is used as a tool for data collection. Further in descriptive analysis the frequencies and percentages are taken into account. Factor analysis is done to extract the factors related to the opinion of the respondents about sleeping disorders. Mann Whitney U test applied to test the opinions with respect to gender versus different factors that are associated with sleeping disorders during exams. Similarly the grouping variables any sort of sleeping disorder and time of the study with the factors associated with sleeping disorders using SPSS 23.
It is concluded that during exams there are major sleeping problems. There are 5 factors extracted from factor analysis. There are statistically significant relationship with disturbed inner peace, sleep consciousness and mental laziness.
Table of Contents
Sr. No. Title Page No.
Chapter No. 1 Introduction 1 – 13
1.1 Sleep 1
1.2 Types of Sleep 1
1.2.1 REM Sleep 1
1.2.2 NREM Sleep 2
1.3 Quality of Sleep 3
1.3.1 Theoretical Models on Sleep Quality 3
1.3.2 Factors Affecting the Sleep Quality 4
1.4 Sleep Disorder 5
1.4.1 Sleep apnea 6
1.4.2 Insomnia 6
1.4.3 Narcolepsy 7
1.4.4 Sleep paralysis 7
1.4.5 Restless leg syndrome 7
1.4.6 Hypersomnia 7
1.4.7 Parasomnias 8
1.5 Examinations 8
1.6 Exams Anxiety 8
1.6.1 Pressure of High Grades 8
1.6.2 Parental Expectations 8
1.6.3 Financial Problems 8
1.6.4 Passionate 9
1.6.5 Adjustment Problem 9
1.7 Benefits of Good Sleep 9
1.8 Sleeping Difficulty During Exams Seasons 10
1.9 Side Effects of Lack of Sleep 10
1.10 Importance of Sleep 11
1.11 Significant of the Study 12
1.12 Objectives of the Study 13
Chapter No. 2 Literature Review 14 – 19
Chapter No. 3 Methodology 20 – 30
3.1 Research Methodology 20
3.2 Consideration of Population 20
3..3 Sampling Unit 20
3.4 Study Design 20
3.5 Sampling Technique 20
3.6 Determination of Sample Size 21
3.7 Data Type 22
3.8 Data Collection 22
3.9 Field Experience 22
3.10 Data Management 22
3.11 Reliability 22
3.12 Coding Scheme of the Study 23
3.13 Methods Used for Analysis 24
3.14 Factor Analysis 24
3.15 Mann Whitney U Test 29
Chapter No. 4 Statistical Analysis 31 – 51
4.1 Descriptive Analysis 31
4.2 Inferential Analysis 36
4.2.1 Factor Analysis 36
4.2.2 Mann Whitney U Test 45
Chapter No.5 Summary ; Conclusion 52
Appendix List of Tables
Table No. Page No.
Table 3.1 Reliability of Data 22
Table 3.2 Coding scheme of the Data 23
Table 4.1 Frequencies and percentages of respondent’s demographic information 31
Table 4.2 Frequency and percentage table for perception-based questions 33
Table 4.3 KMO and Bartlett’s test 37
Table 4.4 Communalities 38
Table 4.5 Total Variance Explained 40
Table 4.6 Rotated Component Matrix 42
Table 4.7 Component Transformation Matrix 43
Table 4.8 Naming of Factor Extracted 43
Table 4.9 Reliability Analysis 45
Table 4.10 Mann Whitney U test summary of gender versus different factors 45
Table 4.11 Mann Whitney U test summary of any sort of sleeping disorder versus different factors 48
Table 4.12 Mann Whitney U test summary of time of the day for prefer for studying versus different factors 50
Figure 4.1 Scree Plot 41
A condition of body and mind which typically recurs for several hours every night, in which the nervous system is inactive, the eyes closed, the postural muscles relaxed, and consciousness practically suspended.
The MacMillan Dictionary for Students offers:
“Sleep is a naturally recurring state characterized by reduced or absent consciousness, relatively suspended sensory activity, and inactivity of nearly all voluntary muscles”.
Adequate sleep is a key part of healthy life style and can benefit your heart and mind.
Sleep is a naturally recurring state of mind and body, characterized by altered consciousness, relatively inhibited sensory activity, inhibition of nearly all voluntary muscles, and reduced interactions with surroundings.
Sleep is one of our basic need that plays a very important role in a human beings health. It is not only a biological necessity but also a physiological drive. In today’s fast-paced world, though, a good night’s sleep is often the first thing to go. The effects of inadequate sleep are more than mere annoyances. They affect our mood and how we perform at school, work, and home and behind the wheel.
1.2 Types of Sleep
There are two main broad types of sleep, each with its own distinct physiological, neurological and psychological features: rapid eye movement (REM) sleep and non-rapid eye movement (non-REM or NREM) sleep, the later of which can in turn be divided into three or four separate stages. Non-REM sleep is sometimes referred to as “quiet sleep” and REM as “active sleep”.
1.2.1 REM Sleep
REM sleep is abbreviated as “rapid eye movement”. A very active type of sleep where the brain is almost as active as if it was awake. In REM sleep the brainwaves are almost identical as if you’re awake. REM sleep is known as paradoxical sleep. It may look like you are fast asleep, but there is a lot happening inside your brain.
REM interrupts deep sleep in 90 minutes cycles throughout the night. Usually, REM sleep happens 90 minutes after you fall asleep. The first period of REM typically lasts 10 minutes. Your heart rate and breathing quickens. Maybe this is because deep sleep cannot be sustained for long periods of time. Such inactivity could be bad for the brain. Maybe coming out of deep sleep prevents us from having too much sleep, which we know can be harmful. Perhaps also REM sleep aids our survival by making us semi aware of our surroundings every 90 minutes. Being deeply asleep increases the risk that we won’t be alert enough to be alerted to danger. But in REM sleep, we would be able to wake up alert and act quickly. You can have intense dreams during REM sleep, since your brain is more active.
1.2.2 NREM Sleep
NREM sleep is abbreviated as “non-rapid eye movement”. A very relaxed type of sleep that gets progressively deeper. NREM sleep is what people most commonly associate with sleep. Your brain waves become progressively slower until you reach the deepest stage of sleep.
Deep sleep is essential for restoring energy and allowing the body to undergo maintenance. While in NREM sleep:
Wounds are healed
White blood cells are created to aid your body’s defences
The muscles are restored
The growth hormone is released
Without enough deep sleep, all of these processes will be hampered.
While under the deepest levels of sleep the brain reorganizes the many mental pathways within the cortex. This process is critical for learning and ongoing brain development.
There are three phases of non-REM sleep. Each stage can last from 5 to 15 minutes. You go through all three phases before reaching REM sleep.
Stage 1: Your eyes are closed, but it’s easy to wake you up. This phase may last for 5 to 10 minutes.
Stage 2: You are in light sleep. Your heart rate slows and your body temperature drops. Your body is getting ready for deep sleep.
Stage 3: This is the deep sleep stage. It’s harder to rouse you during this stage, and if someone woke you up, you would feel disoriented for a few minutes. During the deep stages of NREM sleep, the body repairs and regrows tissues, builds bone and muscle, and strengthens the immune system.
1.3 Quality of Sleep
Quality of sleep is defined as sufficient period and depth that results in feeling of awake and makes one relaxed and feeling good whole the day. It is an individual’s satisfaction with sleep experience, sleep adjust and sleep maintenance and experience fresh mood when wake from sleep.
Both the insomnia and normal sleeper groups defined sleep quality by tiredness on waking and throughout the day, feeling rested and restored on waking, and the number of awakenings they experienced in the night. The insomnia group had more requirements for judging sleep to be of good quality. (Allison G. Harvey).
1.3.1 Theoretical Models on Sleep Quality
There are following theoretical models on sleep quality
This theory states that our life depends on circadian cycle that moves from light to dark and dark again. This rhythms give cues in environment. Our whole life depends upon this cue that helps in survival from any damage.
This theory states that sleep is necessary for several functions. During sleep organisms restore energy for afterward usage. They consumes lots of energy during deep sleep that helps in their lazy hours than energetic in day times (WEBB, 1986)
This theory states that sleep has a large impact on learning. Neurons that are major part of brain that make proper functioning and involved in learning are highly influenced by sleep. Deep sleep makes nerve cells relax and calm (Pinal, 2005)
Repair and Restoration Theory of Sleep
This theory states that sleeping is essential for revitalizing and restoring the physiological processes that keep the body and mind healthy and properly functioning. This theory suggests that NREM sleep is important for restoring physiological functions, while REM sleep is essential in restoring mental functions.
Evolutionary Theory of Sleep
It is also known as adaptive theory of sleep, suggests that period of activity and inactivity evolved as means of conserving energy.
This theory hold that unimportant information is erased and important information is locked into more permanent memory. Infants, who are acquiring information at a rate faster than at any other point during life. All sleep may not be equal for reinforcing learning.
1.3.2 Factors Affecting the Sleep Quality
The major factors which affect the sleep quality are as follows:
Life Styles and Habits
Various lifestyle factors can affect a person’s ability to sleep well. People working a shift other than the day shift must recognize their priorities, or sleep difficulties may occur.
Physical and mental disorder can cause psychological stress, and it tends to disturbance of sleep. It affects sleep in two ways. 1. The person experiencing stress may find it difficult to obtain the amount of sleep he or she needs. 2. REM sleep decreases in amount which tends to add anxiety and stress.
Mostly people sleep best in their usual home environment. Sleeping in a strange or new place can tends to influence both REM and NREM sleep.
It has long believed that dietary amino acid L- tryptophan acts to promote sleep. A small protein containing snack before bedtime used to be recommended for patient with insomnia. Protein may actually increase alertness and concentration, whereas carbohydrates appear to affect brain serotonin level and promote calmness and relaxation.
Alcohol beverages, when used in moderation, appear to induce sleep in some people. However, large quantities have been found to limit REM and Delta sleep. This effect may partially explain the phenomena of hangover after excessive alcohol consumption.
Caffeine is a central nervous system stimulant. For many people beverages containing caffeine interfere with the ability to fall asleep. As for example beverages include tea, coffee, chocolates and soft drinks.
1.4 Sleep Disorder
Sleep disorders involve problems with the quality, timing and amount of sleep, which cause problems with functioning and distress during the daytime. Sleep difficulties are linked to both physical and emotional problems. Sleep problems can both contribute to or exacerbate mental health conditions and be a symptom of other mental health conditions.
A sleep disorder is a medical disorder of the sleep patterns of a person or animal. Some sleep disorders are serious enough to interfere with normal physical, mental, social and emotional functioning. Polysomnography and actigraphy are tests commonly ordered for some sleep disorders.
There are following main sleeping disorders
Restless leg syndrome
1.4.1 Sleep Apnea
Sleep apnea is a potentially serious sleep disorder in which breathing repeatedly stops and starts. You may have sleep apnea if you snore loudly, and you feel tired even after a full night’s sleep.
There are two types of sleep apnea:
Obstructive Sleep Apnea (OSA)
It is caused by a blockage of the airway, usually when the soft tissue in the back of the throat collapses during sleep.
Central Sleep Apnea
Unlike OSA, the airway is not blocked, but the brain fails to signal the muscles to breathe, due to instability in the respiratory control centre.
Insomnia is defined as difficulty with the initiation, maintenance, duration, or quality of sleep that results in the impairment of daytime functioning, despite adequate opportunity and circumstances for sleep. Insomnia is a sleep disorder that is characterized by difficulty falling or staying asleep.
Types of Insomnia
There are two types of insomnia
Acute Insomnia is brief and often happens because of life circumstances (for example, when you can’t fall asleep the night before an exam, or after receiving stressful or bad news). Many people may have experienced this type of passing sleep disruption, and it tends to resolve without any treatment.
Chronic Insomnia is disrupted sleep that occurs at least three nights per week and lasts at least three months. Chronic insomnia disorders can have many causes. Changes in the environment, unhealthy sleep habits, shift work, other clinical disorders, and certain medications could lead to a long-term pattern of insufficient sleep. People with chronic insomnia may benefit from some form of treatment to help them get back to healthy sleep patterns. Chronic insomnia can be comorbid, meaning it is linked to another medical or psychiatric issue, although sometimes it’s difficult to understand this cause and effect relationship.
Narcolepsy is a neurological disorder characterized by the brain’s inability to control its sleep or wakefulness cycle. Excessive Daytime Sleepiness (EDS). EDS is the most common symptom of narcolepsy and usually the first symptom to appear (usually between the ages of 10-20 years old). EDS is characterized by a chronic persistence of feeling sleepy and involuntary episodes of falling asleep without warning. People with EDS report it as feelings of mental cloudiness, a lack of energy and concentration, a depressed mood, or extreme exhaustion.
1.4.4 Sleep Paralysis
Sleep Paralysis is the inability to move or speak while one is falling asleep or beginning to wake up. During sleep paralysis the sufferer is consciously aware of their surroundings but is unable to move because the body is still in REM sleep. During REM sleep, the voluntary muscles are “paralyzed” to keep people from being able to act out their dreams. Sleep paralysis usually lasts only a few seconds up to a few minutes with no permanent effects.
1.4.5 Restless Leg Syndrome
Restless legs syndrome is a neurological sleep disorder that make you have an overwhelming urge to move your legs. It makes it difficult to get comfortable enough to fall asleep. The symptoms are usually worse at night. The sensation is difficult for some people to describe. You may lie down and begin to feel burning or itching inside your legs.
Hypersomnia, which refers to either excessive daytime sleepiness or excessive time spent sleeping, is a condition in which a person has trouble staying awake during the day.
They also have other sleep-related problems, including a lack of energy and trouble thinking clearly.
A category of sleep disorders that involve abnormal and unnatural movements, behaviors, emotions, perceptions, and dreams in connection with sleep.
Periods for examinations causes so much stress in students. Examinations is the only means for a student to prove that he deserves a better grade for a course and due to these students think a lot and also revise everything they have learn during the whole period of the cause. The thought of these stuff makes them frustrated and confused which at the long run stress them up.
1.6 Exams Anxiety
Exams anxiety is may be due to major following reasons:
1.6.1 Pressure of High Grades
Students often feel stress in their class due to competition in class they also want to get good position and higher marks in class. It also caused academic stress in students.
It is the desire of every student to excel in their field studies as such high grades mean a lot to students. In situations where students believe they expect a high grade but at the end get a lower grade. It kills their motivation and they become stressed up with that and are not able to do everything right again.
1.6.2 Parental Expectations
Parental expectations are associated with academic stress around the time of examination. They have a strong attachment to their parents and view them as authority figures that can set rules and expectations for their behaviour and academic achievement.
1.6.3 Financial Problems
One reason of academic stress is financial problem in students those who are not able to pay their dues regularly, they fell embraced. Life becomes very challenging when a student is behind on bills payment; for when deadlines are not met and bills stares at you. It is definitely a conductive experience when a student has to handle dual challenges of academics and financial constraints.
It was observed that those students who studying in universities are more eager to learn something new or more passionate than those who are studying in school and other institutes. Those students who have particular goals want to achieve they have proper pathway and need proper awareness in every step of life, but due to stress they also feel anxiety in their lives.
1.6.5 Adjustment Problem
Most of students face problems in their academic life like learning problem, educational problem, occupational problems, financial problems that is why students cannot adjust in anywhere. Due to this problems the people are becoming dependent and students are starting to shift their needs and desires to other and have less passion about education.
1.7 Benefits of Good Sleep
There are following major benefits of good sleep:
1.7.1 Sleep Improves Memory
Researchers do not fully understand why we sleep and dream, but they have found that sleep plays an important role in a process called memory consolidation. During sleep our body may be resting, but our brain is busy processing our day, making connections between events, sensory input, feelings, and memories. Deep sleep is a very important time for brain to make memories and links, and getting more quality sleep will help remember and process things better.
1.7.2 Sleep may help lose weight
Researchers have found that people who sleep less than 7 hours per night are more likely to be overweight or obese. It is thought that a lack of sleep impacts the balance of hormones in the body that affect appetite. The hormones which appetite, have been found to be disrupted by lack of sleep. If we want to maintain or lose weight, don’t forget that getting adequate sleep on a regular basis is a huge part of the equation.
1.7.3 Sleep May Reduce Risk for Depression
Sleep impacts many of the chemicals in our body, including serotonin. People with serotonin deficiencies are more likely to suffer from depression. We can help to prevent depression by making sure we are getting the right amount of sleep between 7 and 9 hours each night.
1.8 Sleeping Difficulty during Exams Seasons
Most of the students are in the clutch of this problem. Most of the students shorten their sleep duration so that they can dedicate more time for studies. On the contrary reducing times for sleep results in dizziness and uneasiness thus affecting the course of studies. A normal sleep schedule is required for the smooth functioning of a body. Many students take their worries on their bed so they cannot sleep easily.
A transcript of grades and GPAs often determines your future if you don’t get the chance to have an in-person interview with a school, program, or company. The pressure to impress on paper can be overwhelming and often leads students to frantically worry over school and grades.
This pressure is at its worst during exam week. Students studying for their midterms, practicals, and finals find themselves locked up in the library trying to master what seems like a lifetime’s worth of knowledge condensed into one semester.
1.9 Side Effects of Lack of Sleep
There are following side effects of lack of sleep:
1.9.1 Health Problems
Sleep disorders and chronic sleep loss can put you at risk for heart disease, heart attack, Heart failure, irregular heartbeat, high blood pressure, stroke, diabetes etc.
A lack of sleep significantly increases symptoms of depression. Symptoms of depression can also impact a patient’s ability to fall asleep. Sleep and depression are interrelated: Research suggests people who suffer from insomnia are more likely to suffer from major depression than people who sleep regularly.
1.9.3 Learning Process
Sleep is essential to cognitive process associated with learning. A lack of sleep bring down alertness and attention span that makes it easier to take in information. A lack of attention also limits a person’s ability to reason and solve problems effectively.
Skills that have been learned during the day are converted into memories during the night. Even if we manage to learn a significant amount during the day, we will not be able to remember it if we do not get enough sleep to allow our body to store this knowledge in the long term area in the brain.
1.9.4 Poor Decisions
Many parts of the brain are involved in decision-making. When you don’t give your brain enough rest, it do not functions properly and it tends to lead poor decisions.
1.9.5 Lower GPA
Research suggests that college students who sleep the least earn lower grades than those who sleep nine or more hours per night. Your brain needs to cycle through certain deep sleep stages to store memories and solidify the things you learn. When you fall asleep, your heart rate and metabolic rate drop so your body can focus on those things.
1.10 Importance of Sleep
Sleep plays a very vital role in a normal functioning of a body. Most of us need sleep to give our body and mind some amount of relaxation. A human body is like a machine, which needs some amount rest and repair for its smooth functioning. Proper sleep cycle is necessary for a sound body and mind. Most of us are not able to meet this demand of our body. Lack of sleep creates disturbances in a person “daily” routine.
Sleep plays a vital role in good health and well-being throughout your life. Getting enough quality sleep at the right times can help protect your mental health, physical health, quality of life, and safety.
The way you feel while you’re awake depends in part on what happens while you’re sleeping. During sleep, your body is working to support healthy brain function and maintain your physical health. In children and teens, sleep also helps support growth and development.
Sleep helps your brain work properly. While you’re sleeping, your brain is preparing for the next day. It’s forming new pathways to help you learn and remember information. Studies show that a good night’s sleep improves learning. Whether you’re learning math, how to play the piano, how to perfect your golf swing, or how to drive a car, sleep helps enhance your learning and problem-solving skills. Sleep also helps you pay attention, make decisions, and be creative.
Studies also show that sleep deficiency alters activity in some parts of the brain. If you’re sleep deficient, you may have trouble making decisions, solving problems, controlling your emotions and behaviour, and coping with change. Sleep deficiency also has been linked to depression, suicide, and risk-taking behaviour. Sleep helps maintain a healthy balance of the hormones that make you feel hungry (ghrelin) or full (leptin). When you don’t get enough sleep, your level of ghrelin goes up and your level of leptin goes down. This makes you feel hungrier than when you’re well-rested.
Sleep also affects how your body reacts to insulin, the hormone that controls your blood glucose (sugar) level. Sleep deficiency results in a higher than normal blood sugar level, which may increase your risk for diabetes.
Sleep also supports healthy growth and development. Deep sleep triggers the body to release the hormone that promotes normal growth in children and teens. This hormone also boosts muscle mass and helps repair cells and tissues in children, teens, and adults. Sleep also plays a role in puberty and fertility.
Your immune system relies on sleep to stay healthy. This system defends your body against foreign or harmful substances. Ongoing sleep deficiency can change the way in which your immune system responds. For example, if you’re sleep deficient, you may have trouble fighting common infections.
1.11 Significant of the Study
The significant of the study is to analyse the sleeping troubles among university students and to examine the demographic and various academic related factors correlates of quality of sleeping disorders.
1.12 Objectives of the study
To find the factors associated with sleep habits and exams anxiety among students.
To find the association between sleeping disorder during exams in respondents.
To find out the association between any sort of sleeping disorder, time of the study and the factors of sleeping disorder.
Pagel et al. (2007) determined the association between sleep disturbance and poor academic performance. A frequency scaled paediatric sleep disturbance questionnaire and demographic questions with n=238. Statistical tests (Chi-square and ANOVA) were run to compare all the variables. In this study there was a strong correlation between the complaint of restless/aching legs at sleep onset and poorer school performance. Students with lower grade point averages (GPAs) were more likely to have restless/aching legs when trying to fall asleep, dif?culty concentrating during the day, snoring every night, dif?culty waking in the morning, sleepiness during the day, and falling asleep in class. Lower reported GPAs were signi?cantly associated with lower household incomes. After statistically controlling for income, restless legs, sleepiness during the day, and dif?culty with concentration continued to signi?cantly affect school performance.
Ka-Fai Chung and Miao-Miao Cheung (2008) determined sleep-wake patterns and sleep disturbance in Hong Kong adolescents to identify factors that were associated with sleep disturbance and examined the relationship of sleep-wake variables and academic performance. Self-report questionnaires were administered. The average school-night bedtime was 23:24, and total sleep time was 7.3 hr. During weekends, the average bedtime and rise time was delayed by 64 min and 195 min, respectively. The prevalence of sleep disturbances occurring ?3 days per week in the preceding 3 months were difficulty falling asleep (5.6%), waking up during the night (7.2%), and waking up too early in the morning (10.4%). The prevalence of ?1 of these three symptoms was 19.1%. Stepwise regression analyses revealed that circadian phase preference was the most significant predictor for school night bedtime, weekend oversleep, and daytime sleepiness. Students with marginal academic performance reported later bedtimes and shorter sleep during school nights, greater weekend delays in bedtime, and more daytime sleepiness than those with better grades.
Medeiros et al. (2010) examined the sleep wake pattern and the role played by academics schedules and individual characteristics on the sleep wake cycle and academic performance. The subjects were 36 medical students (male=21 and female=15), mean age= 20.7 years. All students attended the same school schedule, from Monday to Friday. The volunteers answered a morningness–eveningness questionnaire, the Pittsburgh Sleep Quality Index (PSQI) and kept a sleep-wake diary for two weeks. A multiple regression technique was used. The results showed that 38.9% of the students had a poor sleep quality. The multiple regression analysis showed a correlation between sleep onset, sleep irregularity and sleep length with academic performance. These results suggested that chronotypes influence the quality of the sleep-wake cycle and that irregularity of the sleep-wake cycle, as well as sleep deprivation (average length was 65:2), influence the learning of college students.
Jane F. Gaultney (2010) examined the prevelance of risk for sleep disorders among college students by gender and age and their association with GPA. Participants were 1,845 college students a large, south eastern public university. 27% of students were at risk for at least ones sleep disorder. Students reported less risk for insomnia and fewer poor sleep practices relative to white and Latino students. Students reported insuf?cient sleep and a discrepancy between weekday and weekend amount of sleep. Students at risk for sleep disorders were over-represented among students in academic jeopardy (GPA < 2.0). Many college students were at risk for sleep disorders, and those at risk may also be at risk for academic failure.
Gomes et al. (2011) examined the associations of sleep patterns with multiple measures of academic achievement of undergraduate university students. A sample of 1654 (55% female) full-time undergraduates 17 to 25 years of age responded to a self-response questionnaire on sleep, academics, lifestyle, and well-being that was administered at the middle of the semester. Univariate analyses found that among 15 potential predictors, stepwise multiple regression analysis identified 5 significant predictors of end-of-semester marks: previous academic achievement, class attendance, sufficient sleep, night outings, and sleep quality (R2 =0.14 and adjusted R2 =0.14, F(5, 1234)=40.99, p<.0001. Associations between academic achievement and the remaining sleep variables as well as the academic, well-being, and lifestyle variables lost significance in stepwise regression.
Abdulghani et al. (2012) examined the prevalence of sleep disorder among medical students and investigated any relationship between sleep disorder and academic performance. This was a cross-sectional self-administered questionnaire-based study. The Epworth Sleepiness Scale (ESS) was also included to identify sleep disorder and grade point average was recorded for academic performance. There were 491 responses with a response rate of 55%. The ESS score demonstrated that 36.6% of participants were considered to had abnormal sleep habits, with a statistically significant increase in female students (p=0.000). Sleeping between 6–10h per day was associated with normal ESS scores (p=0.019) as well as the academic grades ?3.75. Abnormal ESS scores were associated with lower academic achievement (p=0.002). Analysis of the relationship between sleep disorder and academic performance indicated a significant relationship between abnormal ESS scores, total sleeping hours, and academic performance.
BaHammam et al. (2012) studied on relationship between the sleep and wake habits and academic performance of medical students. The study was conducted by systematic random sample of healthy students in 1st, 2nd and 3rd academic levels. A questionnaire was distributed to Epworth Sleepiness Scale (ESS) and academic performance was stratified as excellent (GPA? 3.75/5) and average (GPA <3.75/5). The analysis included 410 students (males 67%). 115 students had excellent performance and 295 students had average performance. The average group had a higher ESS score and a higher percentage of students who felt sleepy during class, whereas, the excellent group had an earlier bedtime. Subjective feeling of obtaining sufficient sleep and non-smokers were the only predictors of excellent performance.
Alya Atieah Al Ghamdi (2013) explored the relationship between the sleep deprivation and academic performance of students in college of nursing at King Saud University. An explanatory and exploratory cross sectional study was done. There were 114 students; 10 of them master students and 104 undergraduate students were included in the study. The study related from sleep especially the night before exam. Results of this paper proved a significant difference between students’ grades and their sleep hours. There was an association between insufficient sleep duration and lower university grades. Furthermore, this study showed no correlation between any of the personal characteristics, sleep deprivation and academic achievement.
ElArab et al. (2014) examined the sleep pattern and the common sleep disorders among medical students and possible associations with academic performance and evaluation. A cross sectional study was carried out through questionnaire. The Insomnia Severity Scale to assess the presence of insomnia and its severity. The Epworth Sleepiness Scale to assess them for daytime sleepiness in different situations. This study was carried out on 435 medical students (51.5% female), with a mean age ± SD of 21.4±1.88. A total of 125 (28.7%) students scored 10 or more on Epworth Sleepiness Scale, suggesting excessive daytime sleepiness. The academic achievements reflected by their last year’s evaluation degrees were distributed among the sample as follows: fair (40.6%), good (69.3%), very good (74%), and excellent (73%). Insomnia during the month preceding data collection was reported as occurring frequently in 32.6% and occasionally in 36.3% of the students and was evident among 62.5, 67.9, 70.9, and 69.7% of the fair, good, very good, and excellent students, respectively.
Ahmad et al. (2014) worked to know the effects of late sleeping habits on academic performance in school girls aged 10-13 years and to identify the factors leading to late sleeping habits in them. A cross sectional survey was conducted on 355 girls studying in girls only schools. Multistage sampling technique was used. Sleep and academic performance questionnaire was administered after taking written informed consents from principals, students and their parents/guardians. Chi square test was applied for finding association between sleep habits and academic performance. P value less than 0.05 was taken as significant. No significant association was found between late sleeping habit and academic performance since majority of the students i.e. 267 (75%) students slept before 11pm, the time which demarcates the late sleeping time with normal time. Significant association was found between habit of book reading before bed time and above average academic performance. Around 43% students drink milk before sleeping and majority watch television before sleeping. Likewise students who wake up fresh in the morning and do breakfast have above average academic performances.
Satti et al. (2015) examined the prevalence of sleep habits and problems among female medical students, and their correlation with perceived sleep quality and academic performance, using a self-administered questionnaire of Sleep and Daytime Habits (QS and DH). About 25% reported sleep problems. Perceived sleep quality was reported as excellent by 55.2% during no exams and by 28% during examination periods. The most prevalent sleep habit is going to bed late at night (Prevalence; 0.97), followed by drinking coffee late at night (Prevalence; 0.61). Taking sleeping pills prevalence was 0.21. The most two prevalent sleep problems were difficulty in falling sleep and wake up because of noise reaching a prevalence of 0.84, and 0.82 respectively. Leisure activity has significant correlation to both quality of sleep and GPA; p<0.05. The quality of sleep was significantly correlated with getting late to bed, nightmares, tired feeling in the morning and using sleeping pills (p<0.05). GPA was only negatively correlated with sleep latency, and use of sleeping pills (p<0.05).
Nicolas Agustin Roig (2015) identified the causal effect of afternoon school shift, correlated with sleep deprivation and academic achievement on adolescents. The regression model was used in this analysis, i.e. Outcomei = ? Afternoon+ ? Ci + €i. The results showed that students attending morning shift sleep one hour less, had worst school performance, and were less likely to smoke cigarettes and marijuana. The results also suggested that drug consumption habits among students were associated with the need of new friends.
Ziyar et al. (2016) determined the quality of sleep and its relationship with test anxiety among students in Qom city, Iran. A cross sectional study performed among 250 students who were going to pass the exam preparation classes. In order to collect data Pittsburgh Sleep Quality Index (PSQI) questionnaires and Test Anxiety Inventory (TAT) questionnaire were used. Data was analysed using SPSS-16 with descriptive statistics and statistical methods, independent t-test, ANOVA and Pearson correlation coefficient. In this study, 50% of participants were male n=125 and 50% were female n=125. 81.4% of subjects had poor sleep quality and 69.9% had average to high score for test anxiety. There was a significant correlation between anxiety and sleep quality.
Jain and Verma (2016) determined the prevalence of sleep disorders among college students and their effect on academic performance. The present study was conducted on 1,524 college students. It included first year students, juniors and seniors. The survey used, the SLEEP-50 has been validated for college students. It consists of 50 items that tap a variety of sleep characteristics. Scoring was done by students as 1- “not at all”, 2-“somewhat”, 3- “rather much”, or 4- “very much” true. The SLEEP-50 provides scores for Insomnia, Narcolepsy, Obstructive Sleep Apnea s(OSA), Circadian Rhythm Disorders (CRDs), Sleep walking, Nightmares. Scoring was done to determine which students were at risk for the various disorders. Out of 1524 students examined, 381 were found to have sleep disorder. Females comprised 57% and males comprised 43%. Obstructive sleep apnea was seen in 11% of examined students. Narcolepsy was seen in 18% of students. Other sleep disorders were CRDs (6%), sleep walking (1%), nightmares (3%) and insomnia (4%). The difference among different sleep disorders were significant (P- 0.04). Maximum numbers of student complaint of use of alcohol at night (17%). Concluded that college students are at risk for sleep disorders or poor sleep hygiene, and that sleep may impact academic success. Students should be taught to reduce stress level in their life which may improve their academic performance.
Iqbal et al. (2018) determined sleep and academic performance on medical students. Students with any chronic disease or using any medication were not included. Students were asked to fill a questionnaire asking about their sleep duration and quality before and after admission to medical college. A total of 100 apparently normal healthy students of First Year MBBS class were included in this study. Group1: Who had the same quality and duration of sleep in medical college as before admission. Group2: Who had more sleep duration after admission to medical college. Group3: Who had less sleep duration after admission to medical college. The academic performance of these 3 groups was compared by taking into consideration the percentage of marks obtained by them in the First Professional MBBS Annual examination. 28% students had same sleep duration and quality after admission to medical college as was before admission. 26% students had increased sleep duration in the medical college and 46% had decreased sleep duration in medical college as compared with before admission. 50% of Group-1 and 50% of Group-2 students secured ?70% marks in the First Professional MBBS examination while 37% of Group-3 students obtained ?70% marks in First Professional MBBS examination. Disturbance in sleep affects academic performance adversely. Decreased sleep duration affects the academic performance more adversely as compared with the increased sleep duration.
3.1 Research Methodology
The word “Methodology” is defined as “Process which is used to collect information and data for the purpose of making decision”. Methodology may include publication research, interview, surveys and other research technique and could include both present and historical information.
3.2 Consideration of Population
“The population is a summation of all organisms of the same group or species, which live in the same geographical area, and have the capability of interbreeding.” The study was conducted in University of the Punjab, New Campus, Lahore. The total number of students in this University was 45000 during the year 2017- 2018.
Our target population for the present study was all the students enrolled during the year 2017-2018 in University.
3.3 Sampling Unit
The individual members of the population or universe is called sampling units. It is determined according to objective of the research because it defines the units to be studies.
3.4 Study Design
It was a cross sectional analytical study. A cross sectional study is a type of observational study that involves the analysis of data collected from a population at one specific point in time. It aims to provide data on the entire population under study. It is less time consuming, inexpensive and gives quick picture of prevalence of exposure and prevalence of outcome, but, it is difficult to determine temporal relationship through this study.
3.5 Sampling Technique
Since, it is a big University and there are many departments, colleges, institutes and centres under it. So, it was not possible for researcher due to shortage of time to reach and get information from all the students. Therefore, convenience sampling had been used in this research.
3.6 Determination of Sample Size
In order to determine the sample size of this study, the formula given by Yamane’s (1967) has been used
n= Sample size
N= Population size
e= Level of precision which is 0.06
n= 450001+(45000)(0.06)2n=276Thus, a sample of size 276 was selected for the study.
3.6.1 Sample Size from Each stratum
The equal allocation technique was used for sample size from each stratum.
nh=nlStrata Stratum nh
1 Male 138
2 Female 138
3.7 Data Type
The primary data is collected by using structured questionnaires from various departments of University of the Punjab. Therefore, personal visits were made by the researcher to collect the responses.
3.8 Data Collection
The success of survey depends upon accuracy of the data collection. Face to face survey method was used of the data collection. Data was collected through a self-administered questionnaire in the presence of researcher. The information required in questionnaire comprised 37 questions along with demographic details. The scale used to evaluate questions in section 1 and section 2 was Likert scale-5 points.
3.9 Field Experience
The overall field experience was good. Respondents were cooperative and behaved gently but some respondents refuse to fill up the questionnaire but after explaining the objectives of the study they agreed to fill up. Some respondents were hesitating to disclose information then assurance was given, that all this information is for the research purpose only and all the information will be kept confidential.
3.10 Data Management
Statistical Package for Social Sciences (SPSS) version 23 was used for data entry and analyses.
The reliability of the scales was tested using the Cronbach alpha score. Cronbach’s alpha determines the internal consistency or average correlation of items in a survey instrument to estimates its reliability, where higher scores indicate higher reliability of the generated scale.
Table 3.1: Reliability of Data
Cronbach’s Alpha No. of Items
3.12 Coding Scheme of the Study
Table 3.2: Coding
Variables Categories Codes
Gender Male 1
Family Income ;20,000 1
Do you have any sort of sleeping disorder? No 1
What time of the day do you prefer for studying? Late Night 1
Early Morning 2
During past month, how would you rate your sleep quality overall?
Very Good 1
Fairly Good 2
Fairly Bad 3
Very Bad 4
Do you drink coffee or tea? Yes 1
How long has it taken you fall asleep each night?
; 30 minutes 1
30-60 minutes 2
1-2 hour 3
2-3 hour 4
Do you use mobile phone or laptop before sleeping? Yes 1
How much time do you sleep at night? 3-5 hour 1
5-7 hour 2
7-9 hour 3
Q 1-25 SD 1
3.13 Methods Used for Analysis
In this section, the methodology for data analysis is elaborated. The relationship between different attributes and different variables have been studied, conclusions has been drawn about the associations and difference between various attributes and variables. For this purpose, most relevant tests were used:
Mann Whitney U Test
3.14 Factor Analysis
Factor analysis is data reduction technique used to reduce a large number of variables into a smaller size of underlying factors. It is used as an exploratory technique when the researcher wishes to summarize the structure of a set of variables. It provides the tools for analysing the structure of the interrelationships (correlation) among a large number of variables.
All variables must be correlated to some extent.
Sampling adequacy must be greater than 0.5 to perform analysis.
3.14.2 Standard for Conducting Factor Analysis
There are the following general procedure for conducting factor analysis:
Kaiser-Mayer-Olkin Measure of Sampling Adequacy:
The Kaiser-Mayer-Olkin Measure of Sampling Adequacy is an index for comparing the magnitude of the observed correlation coefficient to the magnitude of partial correlation. The measure varies from 0 to 1. If KMO measure close to 1, then the choice of factor analysis is better. Reasonably, small KMO values indicate that factor analysis of the variables may not be a good idea.
Bartlett’s Test of Sphericity:
It tests the null hypothesis i.e.
H0: Correlation matrix is an identity matrix i.e. ?=1
H1: Correlation matrix is not an identity matrix i.e. ??1
It is used for the adequacy of the correlation matrix, i.e. the correlation matrix has correlation among at least some variables. If the variables are independent, the observed correlation matrix is expected to have all off-diagonal coefficient. If the test value is larger and significant level is small (0.05), then the hypothesis that variables are independent can be rejected.
Total Variance Explained
It consists of following parts
Factor: Linear combination of the original variables. Factor also represent the underlying dimensions (constructs) that summarize and account for the original set of observed values.
Initial Eigen Values: Eigenvalues are the variances of the factors.
Total: This column contains the eigenvalues.
Percentage of Variance: This column contains the percent of total variance accounted for by each factor.
Cumulative Percentage: This column contains the cumulative percentage of variance accounted for by the current and all preceding factors.
Extraction Sum of Squares Loading: The number of rows in this panel of the table correspond to the number of factors retained.
Rotation Sums of Squared Loadings: The values in this panel of the table represent the distribution of the variance after the varimax rotation.
Rotated Component Matrix: This table contains the rotated factor loadings (factor pattern matrix), which represent both how the variables are weighted for each factor but also the correlation between the variables and the factor. Because these are correlations, possible values range from -1 to +1.
Criteria for Deriving Factors
Once the variables are specified and the correlation matrix is prepared, the next step is to apply factor analysis and identify the underlying structure of relationship. In doing so, decision must be made concerning.
The method of extracting the factors (common factor analysis vs components analysis)
The number of factors selected to represent the underlying structure in the data.
Selecting the Factor Extraction Method
There are two basic method for obtaining factor analysis
Principal Component Analysis
Common Factor Analysis
Principal Component Analysis: The total variance and derive factors that contain small proportions of unique variance and, in some instances error variances.
Common Factor Analysis: In contrast, considers only the common and shared variance, consider unique and error variance both are not of interest in defining the structure of the variables.
The choice between two methods of factor extraction based on the objective of researcher. If the purpose is no more than to “reduce data”. To obtain the minimum number of factors needed to represent the original set of data and the factors extracted need not have any theoretical validity, then principal component analysis is appropriate. Conversely, when the objective is to identify theoretically meaningful underlying dimensions, the common factor analysis is appropriate model.
Criteria for Number of Factors to Extract
After selecting the factor extraction method, the next phase is to decide the number of factors to be extract. Both factor analysis methods are interested in the best linear combination of the variables, best in the sense that the particular combination of original variables account for more of the variance in the data as a whole than any linear combination of variables. Therefore, the first factor may be viewed as the single best summary of linear relationships exhibited in the data. The second factor is defining as the second best linear combination of the variables, subject to the constraint that it is orthogonal to the first factor. To be orthogonal to the first factor, the second factor must be derive from the variance remaining after the first factor has been extracted. The process continues extracting factor emphasizing for smaller and smaller amounts of variance until all of the variance is explained. Any decision on the number of factors to be retained should be based on several considerations.
Latent Root Criterion
The most commonly used technique is the latent root criterion. The rationale for the latent root criterion is that any individual factor should account for the variance of at least a single variable. If it is to be retained for interpretation with component analysis, each variable contributes a value of 1 to the total eigenvalue. Thus, only the factors having latent roots or eigenvalues greater than 1 are considered significant; all factors with latent roots less than 1 are considered insignificant and disregarded.
A Priori Criterion
The priori criterion is a simple so far reasonable criterion under certain circumstances. When applying it, the researcher already knows how many factors to extract before undertaking the factor analysis and vast reading of literature may also be needed for this criterion.
Percentage of Variance Criterion
The percentage of variance criterion is an approach based on achieving a specified cumulative percentage of total variance extracted by successive factors. The purpose is to ensure the practical significance for the derived factor by ensuring that they explain at least a specified amount of variance. Usually the factors which meet a specified percentage of variance explained almost 50% or higher are considered significant.
Scree Test Criterion
The scree test is derived by plotting the Eigen values on the y-axis against the number of factors with their extraction on the x-axis. This test is used to identify the optimum number of factors that can be extracted before the amount of unique variance begins to dominate the common variance structure. Graphically the graph will show a steep slope between the large factors and the regular trailing of the rest of factors. The point at which the curve first begins to flatten out is considered to indicate the maximum number of factors to extract. As a general rule, the scree test results in at least one and sometimes two or three more factors being considered significant than does the Eigen values criterion.
Rotation of Extracted Factors
Factor produced in the initial extraction phase are often difficult to interpret. This is because the procedure in this phase ignores the possibility that variables identified to load on or represent factors may already have high loadings (correlations) with previous factor extracted. This may result in significant cross- loadings in which many factors are correlated with many variables. This makes interpretation of each factor difficult, because different factors are represented by same variables. The rotation phase severs to “sharpen” the factors by identifying those variables that load on one factor and not on another. The ultimate effect of rotation is to achieve a simpler, theoretically more meaningful factor pattern.
There are two main classes of factor rotation method: Orthogonal and Oblique. Orthogonal rotation assumes that the factors are independent and the rotation process maintains the reference axis of the factors of 90 degree. Oblique rotation allows for correlated factors instead of maintaining independence between the rotated factors. The Oblique rotation methods do not require that the reference axis by maintained at 90 degree. Of the two rotation methods, the oblique rotation is more flexible because the factor axis needs not to be orthogonal. There are three methods of orthogonal rotation:
Varimax has achieved the most widespread use as it seems to give the clearest separation of the factors. It does this by producing the maximum possible simplification of the columns (factors) within the factors matrix. In contrast, both quartimax and equimax approached have not proven very successful in producing simpler structures and have not gained widespread acceptance.
In interpreting factor, the size of the factor loadings (correlation coefficient between the variables and the factors they represent) will help in interpretation. As a general rule, variables with large loadings indicate that they are representative of the factor, while small loadings represent they are not. In deciding what is large or small, a rule of thumb suggests that the factor loadings greater than ±0.33 are considered to meet the minimal level of practical significance. The reason for using the ±0.33 criterion is that if the value is squared, the squared value represents the amount of the variable’s total variance account for by the factor. Therefore, a factor loading of 0.33 denotes that approximately 10% of the variable’s total variable’s total variance accounted for by the factor. The grouping of factors with high factor loadings should suggest what the underlying dimension is for that factor.
3.15 Mann-Whitney U Test
The Mann-Whitney U test is a non-parametric alternative to the Student’s t test which requires random sampling from normal population with equal variances. The test is based on ranks and is used to determine whether or not two independent samples of size n1 and n2 come from populations having identical distributions. The null hypothesis to be tested is that the two populations are identical.
The data must be drawn from independent random samples.
The data must be measured at least at the ordinal level.
The underlying dimension of the dependent variable is continuous in nature, even though the actual measurements may be only ordinal in nature.
3.15.2 General Procedure
Formulation of Hypothesis
H0: The two independent samples came from identical population
H1: The two independent samples are came from different population
Level of Significance
? = 0.05
Compute the value of test statistic Z from the sample data in order to decide whether to accept or reject the null hypothesis H0, also compute p-value to draw conclusion.
We reject H0 if
If p-value < ? then reject H0, otherwise accept H0.
If p-value is greater than ?=0.05, we accept H0, and conclude that two samples came from identical populations.
If p-value is less than ?=0.05, we reject H0, and conclude that two samples came from different populations.
4.1 Descriptive Analysis
This part deals with the concept and method concerned with summarization ad description of the important aspect of the numerical data. This area of study consists of the concentration of data and the computation of the few numerical quantities that provide information about the center of the data and indicate the spread of the observation.
Table 4.1: Frequencies and percentages of respondent’s demographic information
Variables Categories Frequency (%)
Age Less than 20 83 (30.0)
21-24 165 (59.9)
25-28 21 (7.7)
Above 28 6 (2.4)
Gender Male 138 (50)
Female 138 (50)
Residential Area Urban 208 (75.4)
Rural 68 (24.6)
Last CGPA Less than 2 4 (1.4)
2.0-2.70 36 (13.3)
2.71-3.5 143 (51.6)
Above 3.5 86 (31.2)
Family Income Less than 20,000 23 (8.3)
20,000-40,000 77 (27.9)
40,0000-60,000 81 (29.3)
Above 60,000 95 (34.4)
Do you have any sort of sleeping disorder? Yes 122 (44.2)
No 153 (55.4)
What time of the day do you prefer for studying? Early Morning 148 (53.6)
Late Night 128 (46.4)
During past month, how would you rate your sleep quality overall? Very Good 50 (18.2)
Fairly Good 132 (47.8)
Fairly Bad 49 (17.8)
Very Bad 44 (15.9)
Do you drink coffee or tea? Yes 196 (71.0)
No 80 (29)
How long has it taken you fall asleep each night? Less than 30 minute 103 (37.3)
30-60 minute 73 (26.4)
1-2 hour 46 (16.7)
2-3 hour 54 (19.6)
Do you use mobile phone or laptop before sleeping? Yes 240 (87)
No 36 (13)
How much time do you sleep at night? 3-5 hour 49 (17.8)
5-7 hour 149(54)
7-9 hour 78(28.3)
Table 4.1 shows the demographic information of respondents 276 Questionnaire were filled out. Age groups of most of the respondents were 21-24 (59.9%). Gender of the respondents were equal 50%. Most of them live in urban area 75.4%. Most of the respondents (51.6%) having 2.7-3.5 CGPA. Most of the respondents having above 60,000 family income (34.4%). Most of them having no sleeping disorder (55.4%). Most of them were studied at early morning (53.6%). Most of the respondents had fairly good sleep quality (47.8%). Most of them were take caffeinated products (71.0%). Most of the respondents were take less than 30 minutes to sleep (37.3%). Most of them (87%) were use technology before sleep. Most of them were sleep 5-7 hour at night (54%).
Table 4.2: Frequency and percentage table for perception-based questions
Variables SD (%) D (%) N (%) A (%) SA (%)
I lose sleep over worrying about examination. 67
I yawn a lot, feel sleepy and lazy all day. 31
My sleeping habits disturbs my friends and family. 60
I feel headaches or neck pain. 45
I use sleeping pills in order to get good sleep. 153
I wake up too early and have difficulty in getting to sleep again 55
I wake up because of little noise. 45
I feel excessive sleepiness during academic lessons. 21
My stress level seems high when I lie down to rest at night. 57
After I woke up at night, I had trouble falling asleep again. 56
I snore 102
I fall asleep while watching television or reading. 44
I feel tired, even if I sleep 8-10 hours the night before. 49
I ever had a sudden attack of intense sleepiness. 34
I often take any sort of medicine for ailment. 103
During exams, I feel blank. 60 (21.7) 59 (21.4) 57 (20.7) 69
During exam, I feel that I may not be able to do well. 42 (15.2) 68 (24.6) 58
(21) 74 (26.8) 34
I feel under a lot of pressure to get good grades on tests. 27
(9.8) 43 (15.6) 68 (24.6) 97 (35.1) 41
Before taking an exam, I feel confident and relaxed. 29 (10.5) 53 (19.2) 73 (26.4) 87 (31.5) 34
While taking an exam, I feel confident and relaxed. 22
(8) 51 (18.5) 73 (26.4) 91
During exam, I think about how I should have prepared for it. 26
(17) 68 (24.6) 90 (32.6) 45
When I take exam, my nervousness causes me to make errors. 31
I read through exam, I feel I don’t know any of the answers. 30
I am afraid of what awaits me in future. 25
I think I’m good at dealing with assignments. 25
The above table shows the frequency and percentage of the respondents when different questions were asked from the researcher side. Out of the 276 respondents, 67(24.3) of the respondents were strongly disagreed that they lose sleep worrying about examination. Out of the 276 respondents, 87(31.5) of the respondents were disagree that they yawn a lot, feel sleepy and lazy all day. 84(30.4) of the respondents were disagree their sleeping habits disturbs friends and family. Out of the 276 respondents, 76(27.5) of the respondents were agree they feel headaches or neck pain. Out of the 276 respondents, 153(55.4) of the respondents were strongly disagree that they use sleeping pills in order to get good sleep. Out of the 276 respondents, 75(19.9) of the respondents were disagree wake up too early and have difficulty in getting to sleep again. 66(23.9) of the respondents were disagree they wake up because of little noise. Out of the 276 respondents, 81(29.3) of the respondents were agree that they feel excessive sleepiness during academic lessons. Out of the 276 respondents, 71(25.7) of the respondents were disagree that their stress level seems high when they lie down at night. Out of the 276 respondents, 81(29.3) of the respondents were disagree that after woke up at night, they had trouble falling asleep again. Out of the 276 respondents, 102(37) were strongly disagree that they snore. Out of the 276 respondents, 72(26.1) of the respondents were agree that they fall asleep while watching television or reading. 68(24.6) of the respondents were strongly agree that feel tired even they sleep 8-10 hours the night before. Out of the 276 respondents, 76(27.5) were disagree that they had a sudden attack of intense sleepiness. Out of the 276 respondents, of the respondents were that they often take any sort of medicine for ailment. Out of the 276 respondents, 69 (25) were agree that during exams they feel blank. 74 (26.8) of the respondents were agree that during exam, they feel may not be able to do well. Out of 276 respondents, 97 (35.1) of the respondents were agree that feel under a lot of pressure to get good grades on tests. 87 (31.5) of the respondents were agree that before taking an exam, they feel confident and relaxed. 91 (33) of the respondents were agree that while taking an exam, they feel confident and relaxed. Out of the 276 respondents, 90 (32.6) of the respondents were agree that during exam, they think about how should have prepared for it. 86 (31.2) of the respondents were agree that when they take exam, their nervousness causes to make errors. Out of the 276 respondents, 78 (28.3) of the respondents were agree that they read through exam, feel that they don’t know any of the answers. Out of the 276 respondents, 91 (33) of the respondents were agree that they were afraid what awaits in future. Out of the 276 respondents, of the respondents were agree that good at dealing with assignments.
Inferential statistics infer from the sample to the population. It determine probability of characteristics of population based on the characteristics of sample along with help assess strength of the relationship between independent variables and dependent variables.
Mann Whitney U Test
4.2 Factor Analysis
The first objective of the study is to determine the factors that affect sleeping habits and exams anxiety. For the purpose of achieving this objective, factor analysis technique has been used. So here factor analysis shrinks the information of 25 variables into a reduced set of new variables with least possible loss of information, and then these variables are used for profiling the factors.
4.2.1 Kaiser-Meyer-Olkin Measure of Sampling Adequacy and Bartlett’s test of sphericity
After factor analysis the no. of possible factors is extracted including all 25 statements of sleeping habits and exams anxiety. Factor analysis method “Principal Component Analysis” is used to see whether variables summarize in a meaningful factor or not. To fulfil the necessary assumption, find the value of Kaiser-Meyer-Olkin (KMO) and Bartlett’s test of sphericity.
Table 4.3: KMO and Bartlett’s test
KMO and Bartlett’s Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .782
Bartlett’s Test of Sphericity Approx. Chi-Square 1253.504
The value of KMO statistic is 0.782 showing that data is appropriate for factor analysis. Bartlett’s test measures the null hypothesis that correlation matrix is an identity matrix, or the variables are uncorrelated. For the current data the Bartlett’s test of sphericity yielded a Chi-square statistic 1253.504 with 210 degrees of freedom. The null hypothesis was rejected at 5% level of significance with p=0.000. Thus, we can proceed for the factor analysis as the correlation matrix is not identity matrix.
Table 4.4 given below consists of initial and extraction communalities for the whole set of variables included in the analysis. These communalities show that how much of the variance in the variable has been accounted for by the extracted factors. All initial communalities are equal to 1 because these all are computed by using all the possible factors (i.e. factors equal to the number of variable extracted in the analysis) and all the variables have been explained while extraction communalities have been computed by using the extracted factor only.
Table 4.4: Communalities
Variables Initial Extraction
I lose sleep over worrying about examination. 1.000 .436
I yawn a lot, feel sleepy and lazy all day. 1.000 .504
I use sleeping pills in order to get good sleep. 1.000 .623
I wake up too early and have difficulty in getting to sleep again. 1.000 .466
I wake up because of little noise. 1.000 .605
I feel excessive sleepiness during school lessons. 1.000 .452
My stress level seems high when I lie down to rest at night. 1.000 .568
After I woke up at night, I had trouble falling asleep again. 1.000 .426
I fall asleep while watching television or reading. 1.000 .486
I feel tired, even if I sleep 8-10 hours the night before. 1.000 .495
I ever had a sudden attack of intense sleepiness. 1.000 .554
During exams, I feel blank. 1.000 .419
During exam, I feel that I may not be able to do well. 1.000 .617
I feel under a lot of pressure to get good grades on tests. 1.000 .558
Before taking an exam, I feel confident and relaxed. 1.000 .610
While taking an exam, I feel confident and relaxed. 1.000 .644
During exam, I think about how I should have prepared for it. 1.000 .600
When I take exam, my nervousness causes me to make errors. 1.000 .462
I read through exam, I feel I don’t know any of the answers. 1.000 .448
I am afraid of what awaits me in future. 1.000 .452
I think I’m good at dealing with assignments. 1.000 .330
Extraction Method: Principal Component Analysis.
4.2.3 Deriving the Factors
For deriving the factors, following criteria has been used.
Latent Root Criteria
Table 4.5 contains the information related to the total variance explained. The column at the left most of the table contains eigen value for all the factors (component) arranged in descending order. The middle part contains the information about the factor extracted with eigen value greater than 1 and the last column contain the information about the values computed after carrying varimax factor rotation and Eigen values differ from those obtained previously. Therefore, by latent root criterion 5 factors with Eigen value greater than 1 have been extracted.
Percentage of Variance Criterion
The middle part of the Table 4.5 given below shows the variance explained by the extracted factor before rotation. The cumulative variability explained by 5 factors (having eigen values greater than 1) is about 51.214%. The last portion of the table shows the variance explained by the extracted factor after rotation. When applying the varimax factor rotation each extracted factor (component) accounts for 21.770 %, 9.032%, 7.957%, 6.377% and 6.078% of the variance successively.
Table 4.5: Total Variance Explained
Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Total % of Variance Cumulative % Total % of
Variance Cumulative % Total % of Variance Cumulative %
1 4.572 21.770 21.770 4.572 21.770 21.770 3.002 14.296 14.296
2 1.897 9.032 30.802 1.897 9.032 30.802 2.119 10.089 24.385
3 1.671 7.957 38.759 1.671 7.957 38.759 1.911 9.099 33.484
4 1.339 6.377 45.136 1.339 6.377 45.136 1.863 8.871 42.355
5 1.276 6.078 51.214 1.276 6.078 51.214 1.860 8.859 51.214
6 .943 4.491 55.705 7 .921 4.388 60.093 8 .853 4.062 64.155 9 .813 3.870 68.025 10 .807 3.843 71.868 11 .752 3.579 75.447 12 .706 3.361 78.808 13 .663 3.157 81.965 14 .632 3.011 84.976 15 .610 2.903 87.879 16 .551 2.622 90.501 17 .445 2.120 92.621 18 .443 2.109 94.730 19 .430 2.047 96.778 20 .388 1.846 98.624 21 .289 1.376 100.000 Extraction Method: Principal Component Analysis.
4.2.4 Scree Test Criterion
Figure 4.1 shows the scree plot. It is the graph of eigen values against all the factors (components). The graph is useful for determining how many factors to retain. The point of interest is where the curve starts to flatten. From the figure, curve begin to flatten after the factor 5. This result concurs with the choice made based on the two criteria discussed before. First factor associated with highest eigenvalue i.e. 4.572, Second factor associated with eigenvalue i.e. 1.897, Third factor associated with eigenvalue i.e. 1.671, Fourth factor associated with eigenvalue i.e. 1.339, and Fifth factor associated with eigenvalue i.e. 1.276. These five factors explain most of the variability in the data i.e. 51.214.
Figure 4.1: Scree Plot
4.2.5 Rotated Component Matrix
Table given below shows the factor loading of each variable on each factor (component) after carrying out varimax factor rotation. These factor loading are the correlation between variables and the factors. Highest loadings have been shown in bold face.
Table 4.6: Rotated Component Matrix
1 2 3 4 5
I lose sleep over worrying about examination. .645 I yawn a lot, feel sleepy and lazy all day. .398 .516 I use sleeping pills in order to get good sleep. .422 -.596 I wake up too early and have difficulty in getting to sleep again .633 I wake up because of little noise. .764 I feel excessive sleepiness during school lessons. .348 .440 My stress level seems high when I lie down to rest at night. .638 After I woke up at night, I had trouble falling asleep again. .425 .328 I fall asleep while watching television or reading. .691 I feel tired, even if I sleep 8-10 hours the night before. .666 I ever had a sudden attack of intense sleepiness. .716 During exams, I feel blank. .575 During exam, I feel that I may not be able to do well. .667 I feel under a lot of pressure to get good grades on tests. .711 Before taking an exam, I feel confident and relaxed. .771
While taking an exam, I feel confident and relaxed. .796
During exam, I think about how I should have prepared for it. .697 When I take exam, my nervousness causes me to make errors. .582 .318 I read through exam, I feel I don’t know any of the answers. .490 .315 I am afraid of what awaits me in future. .623 I think I’m good at dealing with assignments. .564
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.a
a. Rotation converged in 7 iterations.
4.2.6 Component Transformation Matrix
The purpose of component transformation matrix is to identify that similar or same type of questions loaded onto appropriate component.
In summary it can be concluded that factor analysis has identified 5 factors from the list of 21 variables. In the main, the factors are represented by the specific statement written to reflect 5 main categories of sleeping habits and exams anxiety.
Table 4.7: Component Transformation Matrix
Component 1 2 3 4 5 6 7
1 .627 .470 -.137 .420 .326 .209 .199
2 -.178 -.001 .825 .155 .342 -.117 .364
3 .576 -.260 .016 -.245 -.106 -.691 .227
4 .457 -.467 .371 -.018 .046 .391 -.530
5 .152 .422 .371 -.047 -.800 .132 .048
6 .056 -.453 -.144 -.075 -.167 .496 .701
7 .088 .332 .062 -.855 .310 .221 .046
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
4.2.7 Naming Factors
Table 4.8: Naming of Factor Extracted
Factors Q# Variables Loadings
inner peace 16 During exams, feel blank. .575
17 During exam, feel that may not be able to do well. .667
18 Pressure to get good grades on tests. .711
21 During exam, think about how I should have prepared for it. .697
22 When take exam, nervousness causes to make errors. .582
23 Read through exam, don’t know any of the answers. .490
24 Afraid of what awaits in future. .623
Sleep consciousness 12 Fall asleep while watching television or reading. .691
13 Feel tired, even if sleep 8-10 hours the night before. .666
14 Ever had a sudden attack of intense sleepiness. .716
Mind Alertness 6 Wake up too early and have difficulty in getting to sleep again .633
7 Wake up because of little noise. .764
10 After woke up at night, trouble in falling asleep again. .425
Mental Laziness 1 Lose sleep over worrying about examination. .645
2 Yawn a lot, feel sleepy and lazy all day. .516
5 Use sleeping pills to get good sleep. -.596
8 Feel excessive sleepiness during academic lessons. .440
9 Stress level seems high when lie down to rest at night. .638
Self Confidence 19 Before taking an exam, feel confident and relaxed. .771
20 While taking an exam, feel confident and relaxed. .796
25 Good at dealing with assignments. .564
4.2.8 Reliability Analysis of Factors
Table 4.9: Reliability Analysis
Sr. No. Factors Reliability
1 Disturbed inner peace 0.777
2 Sleep consciousness 0.756
3 Mind Alertness 0.720
4 Mental Laziness 0.689
5 Self Confidence 0.658
There are the identified factors which affects the general perception about sleeping disorder during exams.
4.3 Mann Whitney U Test
Here are several questions that are taken as grouping variable and different null hypothesis are formulated to check whether there is a difference between socio demographic status like gender and different statements regarding sleeping disorder during exams
Table 4.10: Mann Whitney U test summary of gender versus different factors
Null Hypothesis Mean Rank Z-value p-value Result
Ho1: Both male and female have same opinion regarding the factor that is disturbed inner peace Male 127.84
Female 147.02 Ho2: Both male and female have same opinion regarding the factor that is sleep consciousness -1.782
Ho3: Both male and female have same opinion regarding the factor that is mind alertness -.043
Ho4: Both male and female have same opinion regarding the factor that is mental laziness Male 128.65 -2.058
Female 148.35 Ho5: Both male and female have same opinion regarding the factor that is self confidence -.906
From Table 4.10, According to null hypothesis Ho1, both male and female respondents have the same opinion regarding the factor that is disturbed inner peace. As p-Value 0.045<0.05 so, we reject Ho1 and may conclude that male and female respondents have not same opinion regarding the factor that is disturbed inner peace. It can also be conclude that disturbed inner peace in the female is statistically significantly higher than the male.
According to null hypothesis Ho2, both male and female respondents have the same opinion regarding the factor that is sleep consciousness. As p-Value 0.075>0.05 so, we accept Ho2 and may conclude that male and female respondents have same opinion regarding the factor that is sleep consciousness.
According to null hypothesis Ho3, both male and female respondents have the same opinion regarding the factor that is mind alertness. As p-Value 0.965>0.05 so, we accept Ho3 and may conclude that male and female respondents have same opinion regarding the factor that is mind alertness.
According to null hypothesis Ho4, both male and female respondents have the same opinion regarding the factor that is mental laziness. As p-Value 0.04<0.05 so, we reject Ho4 and may conclude that male and female respondents have not same opinion regarding the factor that is mental laziness. It can also be conclude that mental laziness in the female is statistically significantly higher than the male.
According to null hypothesis Ho5, both male and female respondents have the same opinion regarding the factor that is self-confidence. As p-Value 0.365>0.05 so, we accept Ho2 and may conclude that male and female respondents have same opinion regarding the factor that is self-confidence.
Table 4.11: Mann Whitney U test summary of any sort of sleeping disorder versus different factors
Null Hypothesis Mean Rank Z value p-value Result
Ho1: There is no association between any sort of sleeping disorder and the factor that is disturbed inner peace -1.738
Ho2: There is no association between any sort of sleeping disorder and the factor that is sleep consciousness Yes 128.32 -2.169
No 149.11 Ho3: There is no association between any sort of sleeping disorder and the factor that is mind alertness -1.726
Ho4: There is no association between any sort of sleeping disorder and the factor that is mental laziness Yes 126.04 -2.803
No 153.00 Ho5: There is no association between any sort of sleeping disorder and the factor that is self confidence -.524
From Table 4.11, According to null hypothesis Ho1, There is no association between any sort of sleeping disorders and the factor that is disturbed inner peace. As p-value 0.082>0.05 so, we accept Ho1 and may conclude that there is no association between any sort of sleeping disorder and the factor that is disturbed inner peace.
According to null hypothesis Ho2, There is no association between any sort of sleeping disorders and the factor that is self-consciousness. As p-value 0.030<0.05 so, we reject Ho2 and may conclude that there is association between any sort of sleeping disorder and the factor that is self-consciousness. It can also be conclude that the sleep consciousness in the group of having no sleeping disorder is statistically significantly higher than the group of sleeping disorder.
According to null hypothesis Ho3, There is no association between any sort of sleeping disorders and the factor that is mind alertness. As p-value 0.084>0.05 so, we accept Ho3 and may conclude that there is no association between any sort of sleeping disorder and the factor that is mind alertness.
According to null hypothesis Ho4, There is no association between any sort of sleeping disorders and the factor that is mental laziness. As p-value 0.005<0.05 so, we reject Ho4 and may conclude that there is no association between any sort of sleeping disorder and the factor that is mental laziness. It can also be conclude that the mental laziness in the group of having no sleeping disorder is statistically significantly higher than the group of sleeping disorder.
According to null hypothesis Ho5, There is no association between any sort of sleeping disorders and the factor that is self-confidence. As p-value 0.600>0.05 so, we accept Ho5 and may conclude that there is no association between any sort of sleeping disorder and the factor that is self-confidence.
Table 4.12: Mann Whitney U test summary of time of the day for prefer for studying versus different factors
Null Hypothesis Mean Rank Z-value p-value Results
Ho1:There is no association between time of the day for prefer for studying and the factor that is disturbed inner peace -.698
Ho2: There is no association between time of the day for prefer for studying and the factor that is sleep consciousness -.323
Ho3: There is no association between time of the day for prefer for studying and the factor that is mind alertness -1.034
Ho4: There is no association between time of the day for prefer for studying and the factor that is mental laziness Early morning 150.05 -2.244
Late night 128.51 Ho5: There is no association between time of the day for prefer for studying and the factor that is self confidence -.358
From Table 4.12, According to null hypothesis Ho1, There is no association between time of the day for prefer for studying and the factor that is disturbed inner peace. As p-value 0.485>0.05 so, we accept Ho1 and may conclude that there is no association between time of the day for prefer for studying and the factor that is disturbed inner peace.
According to null hypothesis Ho2, There is no association between time of the day for prefer for studying and the factor that is sleep consciousness. As p-value 0.747>0.05 so, we accept Ho2 and may conclude that there is no association between time of the day for prefer for studying and the factor that is sleep consciousness.
According to null hypothesis Ho3, There is no association between time of the day for prefer for studying and the factor that is mind alertness. As p-value 0.301>0.05 so, we accept Ho3 and may conclude that there is no association between time of the day for prefer for studying and the factor that is mind alertness.
According to null hypothesis Ho4, There is no association between time of the day for prefer for studying and the factor that is mental laziness. As p-value 0.025<0.05 so, we reject Ho4 and may conclude that there is no association between time of the day for prefer for studying and the factor that is mental laziness. It can also be conclude that the mental laziness in the group who prefer studying in early morning is statistically significantly higher than the late night.
According to null hypothesis Ho5, There is no association between time of the day for prefer for studying and the factor that is self-confidence. As p-value 0.720>0.05 so, we accept Ho5 and may conclude that there is no association between time of the day for prefer for studying and the factor that is self-confidence.
Sleep is one of our basic needs. It is important for our physical, intellectual and emotional health. Sufficient sleep is required for proper functioning of nervous system. Sleep is an essential process that regenerates the body to function optimally. Therefore, the purpose of this study is to determine and assess major sleeping disorders of exams and makes an analysis of perceived impact on participants.
In this chapter, we try to summarize all the finding of our study. It provides a quick look on the topic and its analysis.
The main objective of the research is to identify the factors associated with sleep habits and exams anxiety among students. To find the association between sleeping disorder in respondents. To find out the association between any sort of sleeping disorder, time of the study and the factors of sleeping disorder.
The population for the present study is considered as all the students of university who were enrolled in 2017-18. A sample of 276 students was selected by using the most common sampling technique which is convenient sampling, as this technique is useful and technically most relevant for the present study. The results are interpreted on the SPSS (Statistical Package of Social Sciences) version 23.0.
First, descriptive analysis is used to investigate the information about the variables like gender, age, residential area, CGPA, family income, any sort of sleeping disorder, time of the study. The frequency tables are used to represent the total proportion falling in each category along with their respective percentages.
In inferential analysis, Factor analysis and Mann Whitney U test are used. Factor analysis method is used to extract factors. The value of KMO shows that we further proceed for the factor analysis. Principle component extraction method is used for obtaining rotated component matrix. Reliability test is performed for all the retained factors. By using the varimax rotation there are total 5 factors extracted from original data which were highly influence the perception of students. The name of factors are disturbed inner peace, sleep consciousness, mind alertness, mental laziness and self-confidence.
Mann Whitney U test is used to check that two independent samples come from identical population. To check the difference between gender and the different factors associated with sleeping disorder during exams. The results of Mann Whitney U test showed that there is a difference between gender and different factors like disturbed inner peace and mental laziness.
To check the significance between any sort of sleeping disorder in respondents and factors associated with sleeping disorder during exams. The result of the Mann Whitney U test showed that there is a difference between respondents not having any sort of sleeping disorders during exams and the factors like sleep consciousness and mental laziness.
To check the significance between time of the study and the factors associated with sleeping disorders in exams in respondents. The result of Mann Whitney U test show that there is a difference between time of early morning for study and the factors that is mental laziness.
It is concluded from the present study that there are some sleeping disorders during exams. The sleep hours and exam anxiety showed the direct relationship so it must be taken into consideration. There are some sleeping problems with the majority of the students related to these factors disturbed inner peace, sleep consciousness, mind alertness, mental laziness and self-confidence. The factors of sleep disorders are observed statistically significant with disturbed inner peace and mental laziness among gender. It is also concluded that disturbed inner peace and mental laziness in male are statistically significant than female. The factors sleep consciousness and mental laziness are statistically significant with any sort of sleeping disorder. The factor mental laziness is statistically significant between late nights of the study.
The following recommendations are made:
To enhance the quality of sleep, there is a need to improve the sleep habits of the students.
This study also recommends that the students should be taught the necessary proper sleep so that their quality of sleep can be greatly improved.
Students should take proper sleep because proper sleep reduces their depression.
Students should wake up and fall asleep at fix time so that their sleep can be better.
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A Statistical Study on Factors Affecting the Sleeping Disorders during Exams among the Students of University of the Punjab
Gender: Male Female
Residential Area: Urban Rural
Family Income: Less than 20,000 20,000–40,000 40,000–60,000 Above 60,000
Do you have any sort of sleeping disorder? Yes No
What time of the day do you prefer for studying?
Early Morning Late Night
During past month, how would you rate your sleep quality overall?
Very Good Fairly Good Fairly Bad Very Bad
Do you drink coffee or tea? Yes No
How long has it taken you fall asleep each night?
Less than 30 minute 30-60 minute 1-2hour 2-3hour
Do you use mobile phone or laptop before sleeping?
How much time do you sleep at night?
3-5 hours 5-7 hours 7-9 hours
Read carefully and select appropriate option
1. SD (Strongly Disagree) 2. D (Disagree) 3. N (Neutral)
4. A (Agree) 5. SA (Strongly Agree)
SECTION-1 (Sleeping Habits)
Sr. No. Statements SD D N A SA
I lose sleep over worrying about examination. I yawn a lot, feel sleepy and lazy all day. My sleeping habits disturbs my friends and family. I feel headaches or neck pain. I use sleeping pills in order to get good sleep. I wake up too early and have difficulty in getting to sleep again I wake up because of little noise. I feel excessive sleepiness during academic lessons. My stress level seems high when I lie down to rest at night. After I woke up at night, I had trouble falling asleep again. I snore I fall asleep while watching television or reading. I feel tired, even if I sleep 8-10 hours the night before. I ever had a sudden attack of intense sleepiness. I often take any sort of medicine for ailment. SECTION-2 (Exams Anxiety)
Sr. No. Statements SD D N A SA
During exams, I feel blank. During exam, I feel that I may not be able to do well. I feel under a lot of pressure to get good grades on tests. Before taking an exam, I feel confident and relaxed. While taking an exam, I feel confident and relaxed. During exam, I think about how I should have prepared for it. When I take exam, my nervousness causes me to make errors. I read through exam, I feel I don’t know any of the answers. I am afraid of what awaits me in future. I think I’m good at dealing with assignments.