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Student Perceptions of Sleep Quality and Its Effects on Academic Performance

Sleep is recognized as one of the crucial factors of health and well-being in humans. "Sleep, an important component of human homeostasis, is as essential as other human needs such as food or water" (Kaplow, 2007, p. 53). Humans spend at least 30 percent of their entire lifetime asleep (Kaplow, 2007). Still, despite the growing body of empirical literature, the role of sleep and its implications for academic performance are not well-understood. Earlier, researchers studied how sleep influences energy expenditure in humans and what role it plays in the academic performance of students. Jung et al (2011) suggested that since one the main functions of sleep is to preserve and conserve energy, it helps to restore a person's physical and emotional capacity. Therefore, any sleep difficulties are likely to have extremely negative effects on people's lives. In this sense, high school and college students are a population of concern, since they often experience the lack of sleep, particularly at the last stages of learning before graduation (Gomes, Tavares & Azevedo, 2011). At the same time, students learn much better, when they have and follow a well-developed schedule and distribute the weight of their study tasks evenly across a few days (Gillen-O'Neel, Huynh, & Fuligni, 2013).

It seems that modern researchers know everything about the way sleep deprivation impacts the quality of academic performance in students. Gillen-O'Neel et al (2013) discovered that those students who sacrificed their sleep time for studying found it difficult to understand the learning material and be effective in the classroom. Gilbert and Weaver (2010) found a direct relationship between the quality of sleep and students' grade point average. Gomes et al (2011) confirmed that the quality and frequency of sleep predicted the quality of students' academic performance. Unfortunately, the way students themselves perceive the relationship between sleep quality and their performance in the classroom remains unclear. A better understanding of students' feelings and perceptions could help the researchers to look beyond standard measures of academic performance and create a more effective picture of the ways students cope with their troubles in the last years before graduation. Therefore, the topic of this study was "Student Perceptions of Sleep Quality and Its Effects on Academic Performance."


Most students recognize that their academic performance improves when they sleep well and have enough time to take rest (Gillen-O'Neel et al, 2013). However, not all of them have sufficient opportunities to sleep and study well. High school and college students often face increased demands for socialization and work, which leave little time for sleep and relaxation (Gillen-O'Neel et al, 2013). Moreover, as students move ahead in their studies towards graduation, pressures to sacrifice their sleep habits also intensify (Gillen-O'Neel et al, 2013). As a result, it is possible to assume that senior students will experience greater difficulties with sleep and consequently, academic performance as they are approaching the moment of graduation. Simultaneously, it is not uncommon for students to change their sleep patterns as they enter college (Gilbert & Weaver, 2010). However, these changes are unique for every student. According to Gilbert and Weaver (2010), "college students typically shift to an irregular sleep-wake cycle characterized by short sleep length on weekdays and phase delays on weekends, although this general pattern is influenced by an individual's study and work schedules" (p. 296). Therefore, it is interesting to understand how sleep deprivation influences academic performance from the perspective of students.


Students generally perceive that the lack of sleep reduces the quality of their thinking and learning in the classroom, leading to lower GPA and higher incidence of course failures.



For the given study, quantitative methods were used. The philosophy underlying the quantitative method in this study was that asking questions and getting answers is one of the best ways to obtain relevant information from the study participants. Thus, the quantitative method of this study was based on the use of unstructured interviews and questionnaire/survey forms, the data from which were processed statistically to generate quantitative results. Quantitative methods are particularly useful in psychology, which relies on empirical methods of research and values measurability of the study results. Quantitative psychology remains central to all aspects of psychology research, including personality and emotional wellbeing. According to Kaplow (2007), given that sleep has far-reaching impacts on individual well-being, quantitative designs provide the most favorable opportunities for measuring its implications for academic performance.


Participants were 250 high school and college students, aged between 17 and 25 years. All participants were full-time students, 137 of them female and 113 male (M = 19.95; SD = 1.63). The students came from different educational institutions, so that a better picture of their sleep patterns and their effects on academic performance could be created. 98 percent of the sample constituted 3rd-year students, who have already tasted the difficulties of the learning process and, at the same time, have made a huge step towards graduation. Gillen-O'Neel et al. (2013) report that students are more likely to sacrifice their sleep and experience learning difficulties in the latter years of high school, when the negative relationship between the lack of sleep and academic performance becomes more pronounced. A decision was made to create a sample of 3rd-year students, who are likely to have more serious problems with sleep and academic performance than their younger peers.

The students included in the sample were enrolled in the following programs: (1) languages; (2) philosophy; (3) engineering; and (4) business administration and management. They had to meet the following sampling criteria: age between 17 and 25, full-time status (regardless of the working status), not married, without children. At the same time, according to Gomes et al (2011), the following exclusion criteria were applied: participation in college or high school sport teams, active involvement in extracurricular activities, family and parental obligations, pregnancy for female students, as well as part-time education. It was assumed that all those factors could distort the picture of sleep disturbances in students and the way students perceived their academic performance. Convenience sampling was used to engage volunteers residing in the same district, regardless of the high school or college they were attending. Convenience sampling was used to simplify the research procedure and make it easier for the researcher to reach every sample participant.


Interviews. The purpose of the interview was to clarify how students perceived the problem of sleep deprivation and how, in their view, the lack of sleep influenced their performance. Brief interviews lasting approximately 15 minutes were performed with each student in the sample, with the goal of assessing the subjective impact of sleep deprivation on their academic performance. Some of the questions asked during the interviews included: (1) "Do you feel that you do not have enough time to sleep?"; (2) "Have your sleep patterns changed over time?"; (3) "Do you think that being a student is always about sleeping less and studying more?"; (4) "Do you feel that the lack of sleep negatively influences your academic performance?"; (5) "How would you describe the negative changes in your academic performance due to insufficient sleep?", and others. Thematic analysis was used to analyze the qualitative data. The research was focused on the analysis of objective measures and the statistical relationship among them. Quantitative data were collected along several different lines, in order to evaluate the demographic and academic characteristics of the students included in the sample.


Demographic characteristics. All participants were asked to complete a short demographic survey, which included the following data: age, gender, course title, GPA, the number of course failures (zero grades), and incomplete courses (due to low grades). The data on incomplete and failed courses was included, because GPA alone can never create a full and truthful picture of student performance. Moreover, students may readily display a satisfactory GPA, by withdrawing from or dropping out from certain courses (Gilbert & Weaver, 2010). A higher number of incomplete or failed courses is the sign of poorer performance in students (Gilbert & Weaver, 2010).

Sleep Quality Index. The Sleep Quality Index was used to explore the quantitative aspects of sleep in the students included in the sample. The questionnaire included 8 different items united into one sleep quality scale. Students had to choose one of three possible answers to each item on the scale: (1) no; (2) less than three times per week; or (3) between three and seven times per week. Each response indicated the severity of the sleep deprivation problems reported by each student. Scores were assigned to each item and a total score was calculated based on student responses. Numerical results between 0 and 1 suggested that a student had a good quality of sleep. Total scores ranging between 2 and 10 indicated sleep problems of average severity. Finally, the scores that moved close to 18 confirmed that the student experienced considerable problems with sleep. The instrument was borrowed from Buboltz, Brown, and Soper (2001). The researchers report that with Cronbach's alpha level of 0.74, the scale may be regarded as reliable. The validity of the instrument is supported by the common assumption that the quality of sleep and the quality of life are directly related (Buboltz et al, 2001).

Substance use and abuse. Students had to report their substance use and abuse patterns as they could influence the nature of their sleep problems and consequently, their effects on academic performance. The substance abuse measure included several items with two possible answers: "yes" or "no." The sample participants had to provide information on whether they used alcohol, smoked cigarettes, consumed marijuana or other illicit substances, or used medicines to improve the quality of their sleep. Eventually, the students who responded positively to the question of medicines were excluded from the sample, while the use of such medicines became an exclusion criterion.


A total of 237 students completed the interviews. Their answers were recorded and analyzed. Each interview lasted between 10 and 15 minutes. All interview participants gave their permission to record and analyze their responses, as well as use them in research. Statistical methods were used to analyze the frequency of student responses and their implications for the study results. Furthermore, sleep quality scores were obtained from the students, who filled the sleep quality index form. All 237 students who had previously participated in the interview also agreed to fill in the questionnaire form. However, only the forms that were properly filled and provided answers to all questions were included in the analysis. Therefore, only 216 questionnaire forms were used as the source of primary data. Out of the remaining 11, most included missed responses. Most likely, the students found it difficult to measure their sleep patterns or statistically evaluate them.

Afterwards, statistical correlations between various aspects of academic performance, demographic characteristics, and academic performance were measured. t tests and Spearman correlations were used to measure and estimate the existing correlations between each aspect of academic performance and the academic performance itself measured as GPA reported by students. Mean values for each variable, including GPA and the number of failed courses, were compared to prioritize among the most essential influences on students' academic performance. Also, correlations among the patterns of sleep and failed courses were analyzed separately from the influences of sleep on incomplete courses. It is possible to assume that failed and incomplete courses represent two different measures of academic performance both in high school and college environments.

The results of the interview showed that 97 percent of the sample participants (N = 230) perceived their sleep as being insufficient and even misbalanced. All 100 percent of the sample (N = 237) agreed that being a student was invariably associated with the lack of sleep. Out of the 237 students participating in the interview, 89 percent (N = 211) agreed that their sleep patterns changed as a result of learning. Yet, only 144 of them (61 percent) felt that the lack of sleep negatively influenced their performance. During the unstructured interview, some students confessed that the lack of sleep was not as detrimental to their academic performance as the difficulties they faced in their relations with teachers and other students. 44 percent of the students participating in the study (N = 105) said that they did not think their academic performance deteriorated as a result of sleep disturbances they developed during their studies.

The results of the statistical questionnaire analysis showed that many students were either unaware of their sleep disturbances or did not realize the seriousness of their sleep problems. Only 8 percent of all students who had filled the questionnaire had a score of between 0 and 1. 54 percent of the questionnaire had a score ranging between 1 and 10, and the remaining 38 percent showed the score between 10 and 18. In other words, 38 percent of students in the sample displayed serious problems with sleep. When related to gender, female students were found to have more serious problems with sleep than males: the respondents with the questionnaire score higher than 10, 64 percent were represented by women. More specifically, women reported having problems with falling asleep (12 percent) and frequent awakening at night (27 percent). At the same time, male and female students showed similar levels of morning tiredness and difficulties with waking up in the morning.

Pearson correlation was used to measure the statistical relationship between the questionnaire scores, students' GPA, the number of failed and incomplete courses. As a result, a significant negative correlation between the questionnaire score and GPA was identified (r = -.42, p = 0.05). The correlation was much stronger for female students (r = -.54, p = 0.05) than for males (r = -.39, p = 0.05). The quality of sleep also greatly influenced the number of failed and incomplete courses. For those with the questionnaire score of 1 to 10, the number of failed courses did not exceed 2.4, while incomplete courses accounted for not more than 10 percent of the total time spent in the classroom. The students, whose questionnaire score ranged between 10 and 18, reported 3.7 failed courses on average, coupled with at least 25 percent of incomplete courses of all courses taken during their studies.


The results of the study do not support the hypothesis that students invariably associate the lack of sleep with poor academic performance. Only 44 percent of the students who participated in the interview agreed that their sleep disturbances were negatively correlated with the quality of academic performance. Moreover, 44 percent of the students participating in the study reported that they did not notice any problems in their academic performance as a result of poor sleep. Yet, these results raise more questions than answers. Apparently, students either do not realize the severity of their sleep disturbances or are simply unwilling to recognize them. The statistical analysis of the questionnaires showed that 54 percent of students had moderate sleep disturbances, with another 38 percent facing serious problems with sleep. The ways in which students perceive their sleep patterns differ from the ways they describe them in questionnaires. However, since both measures are self-reported, the risks of subjectivity and bias cannot be ruled out. Since the present study did include any objective measures of the sleep quality in students, it is difficult to estimate the difference between their perceptions and the actual patterns of sleep.

The results of this research support the earlier findings by Gilbert and Weaver (2010) and Gillen-O'Neil et al (2013), who confirmed the existence of a strong negative correlation between sleep disturbances and academic performance. In this case, the difference between student perceptions of their academic performance and the statistical results is more pronounced. While 44 percent of students did not suppose that their sleep problems could result in poor academic performance, the results of the statistical analysis confirm that sleep disturbances is a significant predictor of academic failures, particularly in women. Reasons why women are more susceptible to sleep disturbances and the risks of poor academic performance due to that reason are beyond the scope of this research. However, these reasons could become a good basis for future studies. Since the study was based on a convenience sample, its results may not be generalizable to other populations. Therefore, future researchers will have to focus on diverse student populations to check the validity and reliability of the given study results.


The purpose of this research was to explore student perceptions of sleep disturbances and perceived influences of poor sleep on their academic performance. The results did not support the hypothesis that students perceived their sleep disturbances to be associated with poor academic results. The statistical analysis of questionnaire responses also showed that student perceptions of sleep disturbances did not reflect the actual picture of the sleep and academic performance problems facing students. Most likely, many students did not realize that they had serious problems with sleep, which reduced the quality of their performance results in the classroom. The study was based on convenience sampling methods, which reduce the generalizability of the study results. In other words, the results of the given study may not be generalizable to other populations. Another significant limitation is the absence of objective measures of sleep quality. The severity of the respondents' sleep problems was estimated, based on the results of their interviews and self-reported questionnaire measures. Such self-reported measures are always associated with unnecessary subjectivity and bias. One of the most interesting findings is that female students display higher rates of sleep disturbances and more serious problems with learning, compared with their male peers. The results raise many questions as to the nature of academic learning, differences in sleep patterns, their perceptions among women and men, and coping mechanisms used by men and women to deal with their sleep problems. All these questions could become a topic of future studies. Future researchers should also diversify their study populations to ensure greater generalizability of their study results.

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