Biological Rhythm Research 0165-0424/01/3202-263$16.00 2001, Vol. 32, No. 2, pp. 263 270 Swets & Zeitlinger The Relationships between Sleep-Wake Cycle and Academic Performance in Medical Students Ana Ligia D. Medeiros, Denise B.F. Mendes, Patrícia F. Lima and John F. Araujo Laboratório de Cronobiologia, Depto. Fisiologia, UFRN, Natal, Brazil Abstract Survey and laboratory studies suggest that several factors, such as social and academic demands, part-time jobs and irregular school schedules, affect the sleep-wake cycle of college students. In this study, we examined the sleep-wake pattern and the role played by academic 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, SD = 2.2. 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. The relationships between sleep-wake cycle, PSQI, chronotypes and academic performance were analyzed by a multiple regression technique. The results showed that 38.9% of the students had a poor sleep quality according to the PSQI. When the medical students were evening type or moderate evening type the PSQI showed a tendency of poor sleep. The multiple regression analysis showed a correlation between sleep onset, sleep irregularity and sleep length with academic performance. These results suggest 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 6:52), influence the learning of college students. Keywords: Medical student, academic performance, sleep-wake cycle, chronotype, circadian rhythms. Introduction Survey and laboratory studies suggest that a number of factors, such as social and academic demands, affect the pattern of the sleep-wake cycle of healthy college students. Other factors, including work and study schedules, influence sleep length and sleepwake cycle regularity. The circadian pacemaker controls the sleep-wake cycle and is synchronized by light-dark cycle and by social contact. Results from Valdez et al. Address correspondence to: Partrícia F. Lima, Laboratório de Cronobiologia, Depto. Fisiologia, UFRN, Caixa Postal 1506, Natal, RN, Brazil. E-mail: patylima@mailbr.com.br
264 A.L.D. Medeiros et al. (1996) suggested that prolonged sleep during weekends are due to reduction of sleep during workdays, whereas the delay of bedtime seems to be associated with a tendency of the human circadian system to maintain a delayed phase. Machado et al. (1998) showed that the tendency of phase delay on weekends was differently expressed according to study s schedules and work. They also suggested that the waking time on weekdays is set by study schedules, working schedules and other external factors. Wever (1988) suggested that the desyncronization of circadian rhythms causes a troublesome increase of stress and Jean-Louis et al. (1998) showed that students who fell asleep in school experienced substantially greater negative mood states than those who did not. The importance of the sleep-wake cycle for the physical, mental and social health was shown by Pilcher and Ott (1998). The same study suggested that the students submitted to stress, such as academic demands, had irregular sleep-wake patterns and were presumably not as alert as they should be. In the present work, we study the sleep-wake cycle patterns of a group of students, and the role played by the irregularity of the sleep-wake patterns and individual characteristics on the quality of sleep and academic performance. Materials and Methods The subjects were 35 medical students of the UFRN, with average age of 20.54 years (SD = 2), 20 male and 15 female. They attended the same school schedules, with classes beginning at 8:00 on Mondays, Wednesdays and Fridays and at 7:00 on Tuesdays and Thursdays. There were also classes from 14:00 to 17:00 on Mondays, Wednesdays and Fridays. In the first day of the study, every student filled out an identification form with personal information, including their daily activities and health problems, if they had any. All students were volunteers. They signed a term agreeing to participate in the research and no monetary compensation was given. For two weeks, the students recorded their sleeping and waking up schedules, as well as their naps. The subjective sleep assessment, self-reported data on sleep diary and sleep habits are frequently used in sleep-related research and have been highly correlated with polygraphic measures of the sleep and wrist-worn activity monitor, the actigraphy (Lockley et al., 1999; Usui et al., 1999). It is important to know that all methods that attempt to measure sleep, measure different things, i.e., subjetive recolletion of sleep, electrical activity of the brain or motor activity. A Portuguese version of the Horne & Östberg questionnaire (Horne & Östberg, 1976) was used to classify the participants of the research in morning type, evening type or indifferent type, differentiating the moderate and extreme types, based on the obtained value: 16 30: extreme evening type 31 41: moderate evening type 42 58: indifferent type 59 69: moderate morning type 70 86: extreme morning type
Sleep-Wake Cycle and Academic Performance 265 The subjects completed the Pittsburgh Sleep Quality Index (PSQI) questionnaire, which consists of 10 questions related with the normal sleep habits (Buysse et al., 1989). It was applied during the second week of the data collection. Sleep quality was considered bad for individuals who obtained a score higher than 5. Sleep onset and sleep length were studied, as well as its deviation pattern. As qualitative variables, the chronotype and the quality of the sleep were analyzed. The results of an exam taken during the collection of data were used to analyze the students academic performance. The standard deviation of sleep onset was used as an index of irregularity of the sleep-wake cycle. For the statistical analysis of the data, a linear regression test was applied with ANOVA to detect correlation among the several studied variables. Results Our volunteers had a normal distribution of morningness-eveningness scoring range (Fig. 1A), which was 25 indifferent types, 5 moderate morning types, 4 moderate evening types and 1 extreme evening type. The average of the sleep onset was 0:03 ± 93 min, and female students (23:44 ± 98 min) went to sleep earlier than male students (0:17 ± 90 min). The average sleep length was 6:52 ± 93min, which is less than the general population, suggesting that our samples had partial sleep deprivation. The relationship between chronotype and sleep onset was statistically significant (p < 0.04, Fig. 1B), which confirms that the data obtained in the Horne & Östberg questionnaire are coherent. There was no statistically significant relationship between chronotype and sleep length (p > 0.8), showing that, in spite of the difference in sleep schedules, sleep length was similar among morning and evening types. The standard deviation of the sleep onset of each student was used as an index of irregularity of the sleep-wake cycle. The results showed a negative correlation between irregularity of the sleep and score of the chronotype (p < 0.001), revealing that the students who presented values tending to eveningness had a more irregular sleep. The analysis of the PSQI showed that 38.9% of the students had a poor sleep quality during the study period. This high percentage is a result of the contribution of the components 1 and 3 of the PSQI (subjective sleep quality and sleep length). 42.8% of the students had an irregular pattern of sleep-wake cycle (Fig. 2). A correlation was also found between the irregularity of sleep and the PSQI (p < 0.05), proving that irregularity of sleep implies bad quality of sleep. The regression test also showed a correlation between sleep onset and academic performance (p < 0.001) (Fig. 3A), between sleep length and academic performance (p < 0.02, Fig. 3B) and between irregularity of sleep and academic performance (p < 0.03, Fig. 3C), implying that the students with a more irregular sleep-wake cycle and a shorter length of the sleep presented worse academic performance.
266 A.L.D. Medeiros et al. Figure 1. Distribution of morningness-eveningness scoring range and the relationship between the chronotype and the sleep onset of subjects. Discussion Other studies have shown that students without sleep deprivation (with sleep length of 7:30 h), but with an irregular pattern of the sleep-wake cycle presented sleepiness during the day (Manber et al., 1996). Jean-Louis et al. (1998) showed a relationship between day sleepiness and poor mood states in college students. Billiard et al. (1987) showed that 13.6% of the students self-reported snoring. Ficker et al. (1999) reported that 11.9% of the students snore frequently and are more likely than non-snorers to have lower examination scores or even to fail their exams. In our study, 13.8% of the students reported snoring but we did not find any relationship between snoring and academic performance. The decrement of academic performance on students who have an irregular sleepwake cycle could be explained by the internal desynchronization of the subjects rhythms. We are unable to demonstrate that these students are internally desynchro-
Sleep-Wake Cycle and Academic Performance 267 Figure 2. Graphic of regular (a) and irregular (b) pattern sleep-wake cycle of subjects. nized, but the irregularity of the sleep-wake cycle suggests this. Furthermore, these students are under academic pressure. The irregularity of the sleep-wake cycle and, perhaps, the internal desynchronization could be causing an increase of stress, and the stress could be influencing their academic performance (Wever, 1988). Several measures of human performance are controlled by circadian system and recent research has proposed an endogenous two-oscillator model of the human circadian system, with one oscillator indicated by the core body temperature rhythm and a second oscillator responsible for the daily sleep-wake cycle. When the subjects are under altered sleep-wake pattern, the temperature rhythm and the sleep-wake cycle may be separated from one another and run with different periods. This condition can decrease performance efficiency, like in jet-lag and shift-work.
268 A.L.D. Medeiros et al. Figure 3. The linear regression shows a relationship between sleep onset (A), sleep length (B), sleep irregularity (C) and academic performance. Students who showed a more regular sleep-wake cycle and longer sleep length reported better academic performance. This is an evidence of the consequences of insufficient sleep and irregular sleep-wake cycle. Although these consequences seem obvious, unfortunately they are still often ignored. The results that showed worse academic performance in students who had irregular sleep-wake cycle and shorter sleep length could reveal only one part of the consequences. Jean-Louis et al. (1998) proposed a cascade into catastrophic events, such as decrement in academic performance, disturbance of mood and behavior, and increased vulnerability to substance use. Several published data appear to indicate that sleep deprivation or sleep fragmentation may impair the consolidation of newly learned information and the formation
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