Sleep Quality and Academic Performance in University Students

Sleep Quality and Academic Performance in University Students

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Introduction

Introduction

The importance of sleep cannot be gainsaid as far as enhancing the productivity of an individual is concerned. It has been acknowledged that an individual must be fully rested so that he can regain energy and allow for proper utilization of his energy. This applies both in the work industry and the academic sector. Apart from food, water and air, sleep comes as a biological necessity. It is critical for the consolidation of memory, decision making, learning, as well as critical thinking. In essence, sleep is necessary for optimal operation and functioning of fundamental cognitive functions pertaining to academic, and possibly social success in students taking higher education.

Unfortunately, the lives of many people these days have become too busy to the extent that they are not obtaining sufficient sleep. This is especially because of the numerous responsibilities that many people have in an effort to make ends meet. This applies for people in the working class, as well as individuals in higher learning institutions. Sleep deprivation or insufficient amounts of sleep and poor sleep quality, also known as non-restorative sleep have become endemic in the American society to the extent or level of being recognized as a considerable public health problem. According to research carried out by the National Commission on Sleep Disorders, about 4o million Americans have excessive sleepiness. In addition, sleepiness and numerous other measures pertaining to well-being and health are shown to have been more associated to the quality of sleep rather than its quantity. It is worth noting that once students arrive or are admitted to institutions of higher learning, the first thing that they change pertaining to their daily routines is their sleeping habits and usually for the worse. College students, more often than not shift to irregular sleep wake cycles that are characterized by short lengths of sleep on weekdays, as well as phase delays during weekends where they wake up late. As much as the general patterns are not underlined or influenced by the work and study schedules of an individual, research shows that about twice as many students as individuals in the general population exhibit symptoms that are aligned to delayed sleep phase syndrome. It, therefore, does not come as a surprise that poor quality of sleep and sleep deprivation are prominent in college student and young adult populations (Gilbert & Weaver, 2010). Recent studies have shown that university students have twice the level of sleep problems as the general population. The problem became worse in the recent times. Research shows that the duration of sleep for students in1969 averaged at 7.5 hours. This duration had decreased by 1989 to an average of 6.5 hours. As much as the normative data for 2001 did not show any variations from the 1989 as far as the frequency distribution of the number of hours slept in one night is concerned, 71% of the students were dissatisfied with their sleep, which was an increase from 1992 data that showed 68% and the 24% reported in 1978 (Gilbert & Weaver, 2010).

Although university and college psychologists are aware of the negative effects of depression on the academic performance of students and even make routine screening for it, it is extremely rare for them to screen for poor quality of sleep and sleep deprivation. This is irrespective of the negative impact of poor quality of sleep on academic performance. Studies done on college students have shown that, sleep loss leads to preference for cognitive tasks that demand minimal effort so as to maintain adequate performance. This underlines the fact that sleep loss may also incorporate a negative impact on academic, extracurricular, as well as vocational choices of some sleep-deprived students. In fact, the quality of sleep may be more crucial than psychopathology and depression for academic performance (Gilbert & Weaver, 2010). Despite controversies and uncertainties pertaining to the relative relationships between sleep, depression and academic performance, it goes without saying that sleep problems have negative effects on many students. The importance of studies pertaining to sleep problems is underlined by research studies that show that, sleep problems are more prevalent than depression in students, in higher learning institutions. Unfortunately, few university psychologists carry independent and regular assessment of whether students are sleeping poorly or are sleep deprived. There still is contention as to whether depression and sleep problems are primary or secondary. Previous studies, while linking the sleeping habits of students to decreased academic performance, have used minute, subject samples and have not evaluated the quality of sleep, as well as sleep deprivation. Moreover, they have not put any controls for depression (Gilbert & Weaver, 2010).

Purpose of study

This study aims at determining whether sleep deprivation and poor sleep quality in nondepressed university students’ samples was related to low academic performance. In addition, the current study aims at examining the relationship that exists between academic performance, sleep quality and sleep deprivation (Gilbert & Weaver, 2010).

Hypothesis

The key hypothesis in this study was that, participants with poorer quality of sleep and higher levels of sleep deprivation would show lower academic performance than participants who had little sleep deprivation and good sleep quality.

Methods

The study involved 557 undergraduate Introductory Psychology students, 35.7% (199) of whom were male while 358 (64.3%) of whom were female. However, this number was reduced to 468 participants after depressed individuals were screened out. These were 167 (35.7%) males and 301 (64.3%) females. These participants had a mean age of 19.46 years.

The subjects who participated in this study were solicited in scheduled class meeting for undergraduate psychology course. They subjects were awarded extra credit in exchange for the participation irrespective of the completion of the survey.

The participants undertook a demographic survey that included questions pertaining to their gender, GPA, age, as well as the number of courses in their transcripts that were categorized as “incomplete”, “withdrawn” or “dropped”. The drops, withdrawals and incompletes (DWIs) were solicited as the students could maintain a satisfactory GPA through withdrawal from courses. In essence, DWI was regarded as the second measure for academic performance. Higher numbers of DWIs suggest that the individual has poorer academic functioning (Gilbert & Weaver, 2010).

In addition, Goldberg Depression inventory was used in an effort to detect the level of severity of the depressive symptomatology. GDI ranks depressive symptoms in their level of severity.

The Pittsburgh Sleep Quality Index was also used to measure the quality of sleep over the last one month. It incorporates subscale scores that gauge subjective quality, duration, latency, as well as habitual sleep efficiency, medical use, disturbance, and daytime dysfunction in relation to sleep (Gilbert & Weaver, 2010). The subscales are added so as to determine the global sleep quality score. Statistical analysis of all the data obtained pertaining to PSQI, GDI and Demographic Survey was analyzed using SPSS software.

Results

The researchers obtained data from PSQI subscales and GSQ scales before undertaking statistical analysis. Only participants who had provided sufficient information on GPA and GSQ score information had their data analyzed. Final analysis was carried out on the remaining 415 participants. The results showed the existence of a significant negative correlation between the GSQ and GPA, which supported the hypothesis that lower quality of sleep is associated with lower performance in academics (Gilbert & Weaver, 2010).

Separate correlations analysis was done between GSQ and GPA for males and females. These showed a considerable correlation between the females GSQ and GPA (r =-161, p=.004). This, however, was not shown in the analyses for males.

The number of hours for the samples averaged at 7.2 (with a standard deviation of 1.2, as well as a range between 4-12 hours). Higher GSQ scores show poorer quality of sleep. 52.3% of the sample had GSQ scores that were above the mean that was reported in previous studies for participants with hypersomnia disorders. In addition, 7.6% of the sample had GSQ scores that were higher than the average GSQ scores reported in earlier studies for participants who had disorders of starting and initiating sleep (Gilbert & Weaver, 2010).

Participants who scored two standard deviations above the average GSQ from previous studies were compared to participants who scored below the mark. Independent t-test on samples showed a significant variation in the GPA score (p=.032, t(413) = 2.15), and a significant difference in the GPA to such an extent that individuals who were above 2SDs had considerably lower GPAs (M = 3.22, SD = .54) than those who were below the mark (M = 3.35, SD = .47).

Multiple regression analysis was carried out to gain an understanding of the correlation between sleep and performance in academics, with variables such as GSQ, gender, hours slept and DWI being used as predictors (Gilbert & Weaver, 2010). The results showed that the combination of variables such as GSQ scores, gender, DWI, gender and number of hours slept were a significant prediction of the GPA. As much as gender was shown to be correlated with GPA, the absence or presence of DWI when entered in regression analysis turned to be the strongest predictor of GPA while gender was not.

Discussion

The results of this research or study depicted that there was a significant negative correlation between the GSQ and GPA, which support the hypothesis as to the association of poor quality of sleep with lower performance in academics for nondepressed students. The findings, that nondepressed students who had clinically poor quality of sleep incorporated significantly lower GPAs than their nondepressed counterparts who had clinically good quality of sleep, also supported the hypothesis. In addition, the regression analysis showed that people who had fewer hours of sleep and those who have poor quality of sleep will potentially show poor academic performance. This is the same case for individuals who have a history of incompletion of course (Gilbert & Weaver, 2010).

The study, however, was limited as it did not show direct inference, rather it only showed some association between the quality of sleep and performance in academics. In addition, there exists a possibility that the suspected directionality of sleep quality causing poor academic performance is a mediated and indirect effect not a direct effect resulting from motivational and cognitive deficits that are associated with poor sleep. It is also impossible to generalize the results as only first year students participated in the study. Future research could scrutinize the possibility of predicting performance on the basis of the quality of sleep.

References

Gilbert, S.P & Weaver, C.C (2010). Sleep Quality and Academic Performance in University Students: A Wake-Up Call for College Psychologists. Journal of College Student Psychotherapy

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