Adolescent sleep and working memory performance

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1 Sleep and Biological Rhythms 2008; 6: doi: /j x ORIGINAL ARTICLE Adolescent sleep and working memory performance M GRADISAR, G TERRILL, A JOHNSTON and P DOUGLAS School of Psychology, Flinders University, Adelaide, South Australia, Australia Abstract Several studies have reported a link between poor adolescent sleep and academic achievement. Evidence suggests that particular intellectual abilities that are integral in academic achievement may be susceptible to sleep loss. One such ability is working memory. The aim of the present study was to investigate the link between adolescent sleep loss and working memory performance. A total of 143 adolescents (aged years, mean age = years, 43% boys) volunteered for the study. All participants completed an online sleep questionnaire and the working memory tasks of letter number sequencing and operation span task. Participants were grouped into sufficient sleepers (i.e. more than 9 h; n = 43), borderline sleepers (8 to 9 h; n = 57) and insufficient sleepers (less than 8 h sleep; n = 43), based on their self-reported total sleep time on school nights. The adolescents reporting insufficient sleep performed worse on both letter number sequencing and operation span task (both P = 0.03; medium to large effect sizes) compared with borderline sleepers, but not compared with sufficient sleepers. No other significant differences between groups were found. Compared to the other groups, insufficient sleepers reported going to bed later (P < ), taking longer to fall asleep (P < ) and experiencing greater daytime sleepiness (P < 0.05). These findings suggest between 8 to 9 h of sleep on school nights is sufficient for optimum working memory performance. Future experimental studies are needed to support the current study s findings. Key words: adolescence, daytime functioning, sleep, total sleep time, working memory. INTRODUCTION Many international studies now report that up to 45% of adolescents (aged 11- to 18-years old) experience sleep problems. 1 6 With increasing age, adolescents appear to go to bed later on school nights, 1 4 with many still experiencing difficulty falling asleep. 1,2,6 Due to school commitments, adolescents need to rise at a set time, even if they have had less than the optimal amount of sleep (i.e. 9 h). 1,7 In fact, on school nights many adolescents experience an insufficient amount of sleep (i.e. less than 8 h). 1,8 With this pattern occurring across the Correspondence: Dr Michael Gradisar, Flinders University, School of Psychology, GPO 2100, Adelaide, SA 5001, Australia. grad0011@flinders.edu.au Accepted for publication 4 May school week, adolescents gradually accumulate a significant sleep debt. 9 As a result, most them will typically sleep in on weekends, most likely in an attempt to obtain more sleep. 1,10,11 This sleeping in reduces their accumulated sleepiness over the weekend, and as a result they may begin to have considerable difficulty falling asleep and get insufficient sleep at the start of the following school week; and so the cycle continues. Despite the significant array of acute, short-term consequences resulting from insufficient sleep (e.g. daytime sleepiness), of potentially greater concern for adolescents are findings of more long-term consequences, in particular poor academic achievement. Many studies have found that poor adolescent sleep is associated with poor school performance, lower grades, lower grade point averages, arriving late to class due to oversleeping, and poor school attendance (for review see Curcio et al., The Authors

2 Adolescent sleep and working memory 2006). 12 For instance, in the recent 2006 Sleep in America Poll of 1602 adolescents, adolescents reporting an insufficient amount of sleep were more likely to obtain lower grades. 1 However, what is not clear is how sleep loss in adolescents results in their poor academic performance. In order to learn and perform well at school, students are required to use a range of intellectual abilities. Some of these abilities are highly linked to academic achievement, and in addition, are vulnerable to sleep loss. One such ability is working memory performance. Working memory can be defined as the ability to temporarily store and manipulate information while performing complex cognitive tasks, 13 and is identified as a narrow intellectual ability under the umbrella of the broader short-term memory ability in contemporary intelligence theory. 14 Neuro-imaging studies indicate that performing working memory tasks requires the use of the prefrontal cortex of the brain 15 the same area that is demonstrated in separate studies as being affected by sleep loss. 16 Several studies have investigated the link between sleep disturbance and working memory performance in school-aged children. At present there is a consistent finding that there is no relationship between various sleep parameters (i.e. total sleep time (TST) and sleep efficiency) and performance on simple measures of working memory in school-aged children (7 14 years of age) These simple measures include the digit span backwards task (a task requiring children to recall increasingly long sequences of numbers in reverse order), 20 and the Sternberg memory scanning test. 21 Although the Sternberg test involves a dual-task procedure whereby children are required to switch their attention back and forth from maintaining a representation and processing new information, it is not as demanding as more complex working memory performance measures. One example of the latter is the n-back task paradigm where the demand on the memory load increases when children are required to store and process more pieces of information. A study by Steenari et al. in 2003 found that children aged 6 to 13 years with sleep disturbance performed worse than children with normal sleep patterns on the n-back task paradigm. 22 Specifically, a longer sleep latency and reduced sleep efficiency were associated with poorer performance at all load levels of the n-back task, whereas less TST was related to poorer performance at only the highest load level. It therefore appears that sleep loss in children affects their performance on demanding working memory tasks, and similar findings have been demonstrated for adult insomniacs. 23 The association between poor adolescent sleep and performance on challenging working memory tasks has not been investigated. Considering that academic achievement in the adolescent years is crucial in their access to increased opportunities for further education and employment, and their overall well-being, as well as eventually influencing their own children s level of academic achievement, 24 understanding the intellectual abilities integral to academic performance that are also vulnerable to sleep loss, is of consequence for millions of adolescents around the world. Thus, it is the purpose of the present study to investigate the relationship between adolescents sleep and working memory performance. Specifically, it was predicted that adolescents experiencing insufficient sleep on school nights (less than 8 h/night) will perform worse than both those experiencing borderline sleep (between 8 to 9 h sleep), and those experiencing sufficient steep (at least 9 h). METHODS Participants A total of 174 adolescents recruited from 10 schools from the Adelaide metropolitan area participated in the study. Exclusion criteria included having English as a second language (n = 10) due to the working memory tasks reliance on remembering words and letters of the alphabet, as well as for performance on the vocabularycontrol measure. As performance on working memory measures can also be influenced by aspects of attention-deficit/hyperactivity disorder, 25 adolescents scoring equal to and above the clinical cut-off score of 7 on the hyperactivity subscale of the strengths and difficulties questionnaire 26 were also excluded (n = 19). Two participants did not provide their TST data. This resulted in a final dataset of 143 participants (62 boys, 81 girls) ranging in age from 13 to 18 years (mean age = years; age distribution: 13-years old (n = 26); 14-years old (n = 40); 15-years old (n = 25); 16-years old (n = 28); 17-years old (n = 20); 18-years old (n = 4). The sample was further separated into three groups based upon their self-reported TST on school nights: insufficient sleepers (those getting less than 8 h/night; 30.1%, n = 43), borderline sleepers (those getting more than 8 but less than 9 h/night; 39.8%, n = 57), and sufficient sleepers (those getting at least 9 h/night; 30.1%, n = 43). The distribution of sleep duration was as follows: less than 6 h (n = 8), 6 7 h (n = 8), 7 8 h (n = 27), 8 9 h (n = 57), 9 10 h (n = 35), and more than 10 h (n = 8). All the parents/caregivers of 2008 The Authors 147

3 M Gradisar et al. the participants provided written informed consent for their child to participate in the current study. The study was approved by the Flinders University Social and Behavioural Ethics Committee and the Department of Education and Children Services of South Australia. Materials Sleep measure An online sleep questionnaire was used to measure the participants subjective sleep parameters and sleeprelated daytime functioning. Questions assessing the sleep parameters included items measuring going to bed time, sleep latency, TST, final waking up time, and getting up time. These sleep parameters were measured for both the school week and the weekend. Six questions assessed sleep-related daytime functioning. These included tiredness, sleepiness, feeling moody and irritable, lack of motivation, difficulty concentrating and worries about sleep. The participants were asked to rate the frequency with which they experienced these daytime feelings, from 0 never, to 3 always, over the previous two weeks. Working memory measures Two working memory measures were used in the current study. An automated, online version of letter number sequencing (LNS) was derived from a previous task. 27 LNS requires participants to temporarily store and perform cognitive operations on pieces of information. The participants were given a sequence of jumbled numbers and letters (e.g. J-8-E-5), one at a time, on their computer screen at a rate of one per second. They were instructed to reorganize these by typing the letters alphabetically first, then the numbers numerically (e.g. E-J-5-8). The participants were presented with 24 sequences of alternating letters and numbers, beginning with three characters and gradually increasing in difficulty to eight characters. Correct responses were scored 1 and incorrect responses scored 0. The possible range of scores was 0 to 24. The reliability coefficient (Cronbach s alpha) for LNS in the present study was The second working memory measure used was the operation span task (Op Span). Originally devised by Turner and Engle in 1989, 28 Op Span is a dual-task procedure that assesses the storage and processing components of working memory. Op Span requires participants to shift their attention from maintaining a representation of word list items to interchangeably processing mathematical equations. 29 An important aspect of this task is maintaining information (word list items) through the delay in which a distraction (solving maths equations) occurs. Since the original version of Op Span was intended to be used with adults, it was thought necessary to simplify the words and mathematical equations for the adolescent participants. The words in the original task were one-syllable concrete nouns with four to six letters and the mathematical equations involved two arithmetic operations. 28 For the current study, onesyllable concrete nouns with just four letters (e.g. palm) were derived from a psycholinguistic database accessible to the public via its website ( edu.au/mrcdatabase/uwa_mrc.htm). New mathematical equations that required only one arithmetic operation (e.g = 42) were sourced from a school-based workbook. 30 The participants accessed an automated online version of Op Span. They were initially given two practice trials with feedback on their responses before beginning their assessment trials. In each assessment trial a series of alternating words and mathematical equations were presented. The participants were required to indicate whether the mathematical equation was correct or not. Of the 20 equations, half were correct. In between each equation, one word appeared on the screen for 1 s. After the presentation of all the equations and words, the participants were required to type as many words as they could remember from the series in order of their presentation. Five assessment trials were presented, ranging from a sequence of two words and two equations, up to a sequence of six of each. To reduce the participants ability to predict the number of items in a given trial, the sequences were randomly presented. 31 As the participants may have made a trade-off between remembering words (storage) and solving the equations (processing), an 85% accuracy for solving the equations was set. 31 The assessment trials were scored by dividing the number of words correctly recalled in order by the number of words in that trial. The total scores were computed by averaging the individual trial scores and ranged from 0.00 to The Op Span for the current study had an internal consistency (Cronbach s alpha) of General cognitive ability measure As the present study used a correlational design, the lack of randomization raised the possibility that one group could perform better on the working memory measures by virtue of their general intellectual ability. In order to The Authors

4 Adolescent sleep and working memory control statistically for such an event, the participants completed an online vocabulary test, since a brief measure was required that possessed a high general intelligence (g) loading, 32 as well as being a measure resistant to sleep loss. 33 The vocabulary test consisted of 20 words that were presented one at a time. The participants were instructed to consider each word (e.g. artery ) and select another word or phrase similar in meaning from four alternatives (e.g. muscle tissue, blood vessel, throat, spring). Items were scored 1 if correct and 0 if incorrect, with total scores ranging from 0 to 20. The Cronbach s alpha for the vocabulary test was Procedure Various schools in the Adelaide metropolitan area were approached to participate in the study. With the permission of the principal and relevant teacher, information about the study and consent forms were sent to the students homes. The response rate for the study was 45%. Students whose parents/guardians did not provide consent performed a quiet activity while their classmates participated in the study during designated class time. Testing sessions were conducted in the school computer laboratories during the school day (i.e. between and hours). After a briefing from the researchers (GT and AJ), the participants accessed the research website after entering a username and password. After logging onto the website, the measures were completed in the following order: the LNS, vocabulary, Op Span, sleep questionnaire, hyperactivity subscale of the strengths and difficulties questionnaire, and their socioeconomic information. The participants generally completed these measures in 30 to 45 min. Statistical analysis To test differences between the amount of TST on school nights and working memory performance, analyses of covariance (ANCOVA) were performed. 34 The independent variable was group (i.e. insufficient sleepers [TST < 8 h], borderline sleepers [TST = 8 9 h], and sufficient sleepers [TST 9 h]). The dependent variables were LNS and Op Span, and the covariates were age, gender and vocabulary score. Significance was set at P < When a significant main effect for group was found, pairwise comparisons were performed with Bonferroni corrections applied. Where differences between groups were found, effect sizes (i.e. Cohen s d) were calculated and reported. To test differences in various sleep parameters (e.g. going to bed time) and daytime functioning (e.g. tiredness) between all three groups, a series of one-way ANOVAs were performed with pairwise comparisons. 34 RESULTS Sleep and daytime functioning of the adolescents Table 1 presents the subjective sleep and daytime functioning parameters of the participants from the various sleeper groups. On school nights, differences were found between the groups on all sleep parameters: going to bed time, F(2, 142) = 40.12, P < ; sleep latency, F(2, 142) = 21.69, P < ; waking up time, F(2, 142) = 8.04, P < ; getting up time, F(2, 141) = 3.11, P < Compared to sufficient sleepers, insufficient sleepers went to bed later (P < ), took longer to fall asleep (P < ), woke up earlier (P < ) and got up earlier (P < 0.05). Insufficient sleepers also went to bed later and took longer to fall asleep compared to borderline sleepers (both P < ). However there were no differences in the final waking up and getting up times between these two groups (both P > 0.05). Compared to sufficient sleepers, the borderline sleepers went to bed later (P = 0.001) and woke up significantly earlier (P = 0.02), with no significant differences on the other sleep parameters. On weekends differences were found between the groups on the time they went to bed, F(2, 142) = 7.41, P = 0.001, TST, F(2, 142) = 4.77, P = 0.01 and sleep onset latency, F(2, 142) = 5.17, P = However, no differences were found in their final waking up time, F(2, 141) = 1.68, P > 0.05, or getting up time, F(2, 142) = 2.40, P > 0.05, on weekends. Insufficient sleepers went to bed significantly later (P = 0.003), took longer to fall asleep (P 0.03), and obtained less TST (P 0.03) than both borderline and sufficient sleepers. No significant differences were found between borderline and sufficient sleepers on any weekend sleep parameters. Analyses of the daytime functioning parameters of the three groups indicated significant differences in feelings of tiredness, F(2,140) = 5.42, P = 0.005; sleepiness, F(2,140) = 4.94, P = 0.008; feeling moody and irritable, F(2,140) = 2.18, P = 0.04 and lacking motivation, F(2,140) = 6.81, P = Specifically, insufficient sleepers reported significantly greater daytime sleepiness (P < 0.05), and lack of motivation (P < 0.05) than both borderline and sufficient sleepers, but only 2008 The Authors 149

5 M Gradisar et al. Table 1 Means (SD) values for sleep and daytime functioning parameters, and intelligence tasks as a function of adolescent sleep duration on school nights Sleep Insufficient Borderline Sufficient (<8 h TST) (8 9 h TST) ( 9 h TST) School week Going to bed (time) hours (121.7), hours (61.0) hours (63.7) Sleep onset latency (min) 66.3 (52.3), 30.8 (22.8) 21.6 (18.0) Waking up (time) hours (51.2) hours (47.0) hours (48.6) Getting up (time) hours (66.8) hours (59.7) hours (58.7) Weekend Going to bed (time) hours (174.1), hours (150.8) hours (169.0) Sleep onset latency (min) 44.3 (54.5), 25.0 (29.8) 20.2 (21.2) Total sleep time (h) 8.3 (2.2), 9.2 (1.6) 9.4 (1.5) Waking up (time) hours (182.7) hours (146.3) hours (143.8) Getting up (time) hours (174.9) hours (150.4) hours (157.1) Daytime functioning (0 3) Tiredness 2.2 (0.7) 1.9 (0.7) 1.7 (0.8) Sleepiness 2.1 (0.9), 1.6 (0.9) 1.5 (0.8) Moodiness and irritability 1.5 (0.9) 1.2 (0.8) 1.0 (0.8) Lack of motivation 1.7 (0.9), 1.3 (0.9) 1.0 (0.9) Difficulty concentrating 1.7 (1.0) 1.5 (0.8) 1.3 (0.9) Worrying about sleep 1.1 (1.0) 0.8 (0.9) 0.6 (0.9) Intelligence tasks Letter-number sequencing (0 24) 10.7 (4.0) 13.2 (3.4) 11.7 (4.7) Operation span task (0 1) 0.63 (0.19) 0.79 (0.17) 0.76 (0.19) Vocabulary (0 20) 11.3 (3.4) 12.3 (2.8) 11.0 (2.9) P < 0.05 between insufficient and borderline sleepers; insufficient and sufficient sleepers; borderline and sufficient sleepers. Values in parentheses for time variables (e.g. going to bed) are in min; values in parentheses in left-hand column (e.g. daytime functioning) represent range of possible scores. significantly greater daytime tiredness (P = 0.004) and moody and irritability (P = 0.04) than sufficient sleepers. Interestingly, no significant difference was found in the subjective reports of difficulties concentrating among the three groups, F(2, 140) = 2.18, P > There was a trend though, for a significant difference on worrying about sleep, with insufficient sleepers tending to report higher scores than sufficient sleepers, F(2, 140) = 2.90, P = Cognitive functioning of adolescents Table 1 also presents the means and standard deviations for the various cognitive tasks (i.e. vocabulary and working memory). Surprisingly the mean vocabulary value for the borderline sleepers was higher than the other groups, but this observed difference was not significant, F(2, 138) = 2.54, P > A complete analysis of the working memory measures is presented in the next section. Adolescent sleep duration and working memory performance Analysis on the LNS data revealed a significant main effect for group, F(2, 129) = 3.56, P = Pairwise comparisons indicated that insufficient adolescent sleepers scored significantly worse on LNS than borderline sleepers, P = 0.03; Cohen s d = 0.56, but not than sufficient sleepers. No significant differences were found between borderline and sufficient sleepers. Similarly, in the analysis of the Op Span data a significant main effect was found for group, F(2, 88) = 3.66, P = Pairwise comparisons showed again that adolescent insufficient sleepers scored significantly worse on Op Span than borderline sleepers, P = 0.03; Cohen s d = However, there were no significant differences between insufficient and sufficient sleepers, nor between borderline and sufficient sleepers The Authors

6 Adolescent sleep and working memory DISCUSSION Independent studies have shown that up to 45% of adolescents experience sleep problems, with many of the same studies also reporting associated daytime impairment. 1,2,4 The present study has demonstrated that adolescents who obtain insufficient sleep on school nights (i.e. less than 8 h/night) have impaired working memory performance for challenging tasks. However, unexpectedly, this impairment occurs relative to adolescents who obtain between 8 to 9 h sleep. Although 9 h of sleep has been viewed as the required amount for the optimal functioning of adolescents, 1,7 the findings from the present study suggest this is the case for particular daytime functioning parameters (e.g. daytime sleepiness), but it is not the case for working memory performance. Insufficient sleep patterns and daytime consequences On school nights insufficient sleepers appeared to spend less time in bed compared to borderline and sufficient sleepers. Not only did they go to bed later, but they also woke up and got up earlier. Moreover, while they were in bed insufficient sleepers also took significantly longer to fall asleep. All these factors would contribute to their reduced TST on school nights. On weekends, insufficient sleepers again went to bed later and took longer to fall asleep compared to borderline and sufficient sleepers. Although there were no differences in their final waking up or getting up times, insufficient sleepers nevertheless still obtained less sleep on weekends compared to their borderline and sufficient sleeping peers. Thus, overall it appears that insufficient sleepers are obtaining less sleep across the 7-day week. This reduced sleep appeared to also impact on these adolescents daytime functioning. Specifically, insufficient sleepers reported feeling daytime sleepiness and a lack in motivation more than both borderline and sufficient sleepers, as well as experiencing more tiredness and feeling more moody and irritable than sufficient sleepers. These findings are similar to other studies that have demonstrated that adolescents reporting insufficient amounts of nocturnal sleep also report associated daytime impairment (e.g. daytime sleepiness, tiredness and irritability), 1 and mirror some of the symptoms of insomnia. 35 There was also a trend for insufficient sleepers to report being more concerned about their sleep than sufficient sleepers another hallmark of insomnia in adults. 35 No significant differences were found between the groups on their self-reported frequency of concentration problems. Although it is intuitive that adolescents experiencing insufficient sleep also suffer from concentration problems, 36 the literature is surprisingly sparse, with few studies finding a link between poor adolescent sleep and self-reported concentration difficulties. 37,38 However, the objective working memory measures that tapped into it did show that attentional and higher-order memory functions were related to sleep duration in these adolescents. The association between adolescent sleep and working memory performance Previous studies have shown no relationship between simple measures of working memory (e.g. digit span backwards) and sleep problems in school-aged children. 18,19 The current study attempted to expand on this previous research by using relatively more complex measures of working memory on an adolescent sample. LNS is a slighter more difficult task than previous measures such as digit span backwards. Although digit span backwards requires individuals to hold numbers in their short-term memory and apply a relatively simple cognitive operation on them (i.e. place them in reverse sequence), LNS requires more operations that are more complex (i.e. arrange numbers numerically and arrange letters alphabetically). It appears that such complex cognitive operations are sensitive to the sleep loss experienced by adolescents. Specifically, insufficient sleepers performed significantly worse on this task compared to borderline sleepers, but not compared to sufficient sleepers. This is in contrast to what would be expected. That is, it would be expected that the more sleep, the better the performance. Although no significant difference was found between borderline and sufficient sleepers, the mean values indicate that obtaining between 8 to 9 h of sleep may produce optimal performance on working memory performance. Interestingly, this near inverted-u relationship between sleep duration and working memory performance is somewhat similar to the type of non-linear relationship found between sleep duration with adolescent mental health 39 and adult mortality. 40 Memory impairments associated with insufficient adolescent sleep were also detected with the Op Span Task, thus supporting previous work using more demanding dual-task working memory measures. 22 Specifically, adolescents who reported having borderline sleep were able to recall more words in order 2008 The Authors 151

7 M Gradisar et al. than adolescents reporting insufficient sleep. Similarly, Steenari et al. found that TST was associated with working memory performance as measured by their complex n-back task paradigm. 22 However, no differences were found between insufficient and sufficient sleepers, suggesting again that for adolescents, between 8 to 9 h of sleep may be the optimal amount of sleep for optimal working memory performance. Although similar findings were found for both working memory measures, a larger effect was found for the Op Span task (large effect size) than LNS (medium effect size). This may be because the Op Span task is a more complex task than LNS. For the Op Span task, adolescents were presented with a four-letter word for 1 s, and then required to decide whether a mathematical problem was correct, then presented with another word, and so on. They were therefore required to retain more information (i.e. four-letter words vs single characters), process more information (i.e. interchangeably solve a mathematical problems vs re-arrange letters and numbers, which created a greater interference on the storage of previously presented information), and were likely to have held onto encoded information for longer. Thus, it appears such memory processes are quite sensitive to sleep loss in adolescents. Although adolescent sleep duration was related to demanding aspects of working memory performance, there was no such finding with the vocabulary measure. Although the mean vocabulary value for the borderline sleepers was higher than that for the other groups, this difference was not significant. Vocabulary is a measure that loads significantly onto crystallized and global intelligence (g). 32 The findings from the present study suggest this aspect of crystallized intelligence is more resistant to sleep loss than working memory performance. Limitations and directions for future research The current study employed online visual working memory tasks, thus the effects of adolescent sleep loss on auditory working memory are not currently known. This is important in an ecological sense, as although almost two-thirds of teachers now using computerassisted learning in the school environment, 41 the remaining teacher instruction is typically performed verbally. Therefore, future research needs to determine adolescents vulnerability to auditory working memory tasks. Unfortunately, the current study did not assess adolescents grades, which many other studies have found are lower for adolescents who do not sleep well than for those who do. 1,42 This makes it difficult to conclude that there is a link between adolescent sleep loss, working memory performance and overall academic achievement. Thus, future studies investigating the effects of adolescent sleep problems on intellectual abilities would do well to simultaneously assess academic achievement (i.e. grades, grade point average and standardized achievement tests). As working memory is only one of the 76 narrow intellectual abilities identified in contemporary intelligence theory, 14 further research is needed to identify which abilities are vulnerable (and resistant) to sleep disturbance, as well as their impact on school performance and academic achievement. As previously mentioned, it appears that adolescents in the insufficient sleeping group were experiencing many symptoms of insomnia, including a mean sleep latency over 1 h long, and several daytime consequences (tiredness, sleepiness, moody and irritable, and lacking motivation). Although the present article focuses on the relationship between school night sleep duration and working memory performance, future research should not discount exploring relationships between insomnia symptomatology in adolescents and their working memory performance. Finally, causal conclusions are limited in the present study due to its non-experimental design. This research area presents an elusive task: to test experimentally for the effect of sleep disturbance on intellectual functioning, yet to generalize such findings to the school setting and overall school performance. Nonetheless, such a task may be possible, as evidenced by the Minnesota school start time research. 43 Summary Sleep disturbance occurs in up to 45% of adolescents. The present study found a link between adolescent sleep loss and working memory performance. This has implications for adolescents who have an insufficient amount of sleep in terms of their ability to encode, store and retrieve information. Further research is required to determine how this reduced ability impacts on academic achievement, as well as identifying what other intellectual abilities are susceptible to sleep loss in adolescents. ACKNOWLEDGMENTS The authors wish to thank Mr Corey Durward and Mr Jonathan Wheare for their valuable assistance with the The Authors

8 Adolescent sleep and working memory development of the online sleep questionnaire and Mr Jeff Stotter from the Department of Education and Children s Services of South Australia. This study was supported by an Establishment Grant from the School of Psychology, Flinders University. REFERENCES 1 National Sleep Foundation Sleep in America Poll. National Sleep Foundation: Washington, DC, Ohida T, Osaka Y, Doi Y et al. An epidemiologic study of self-reported sleep problems among Japanese adolescents. Sleep 2004; 27: Roberts RE, Roberts CR, Chen IG. Impact of insomnia on future functioning of adolescents. J. Psychosom. Res. 2002; 53: Russo PM, Bruni O, Lucidi F, Ferri R, Violani C. Sleep habits and circadian preference in Italian children and adolescents. J. Sleep Res. 2007; 16: Andrade MM, Menna-Barreto L. Sleep patterns of high school students living in Sao Paulo, Brazil. In: Carskadon MA, ed. Adolescent Sleep Patterns. Cambridge University Press: London, 2002; Liu X, Uchiyama M, Okawa M, Kurita H. Prevalence and correlates of self-reported sleep problems among Chinese adolescents. Sleep 2000; 23: Carskadon MA, Harvey K, Duke P, Anders TF, Litt IF, Dement WC. Pubertal changes in daytime sleepiness. Sleep 1980; 2: Carskadon MA, Acebo C, Jenni OG. Regulation of adolescent sleep: implications for behavior. Ann. N. Y. Acad. Sci. 2004; 1021: Van Dongen HPA, Rogers NL, Dinges DF. Sleep debt: theoretical and empirical issues. Sleep Biol. Rhythms 2003; 1: Andrade MM, Benedito-Silvia AA, Domenice S, Arnhold IJ, Menna-Barreto L. Sleep characteristics of adolescents: a longitudinal study. J. Adolesc. Health 1993; 14: Millman RP. Excessive sleepiness in adolescents and young adults: Causes, consequences, and treatment strategies. Pediatrics 2005; 115: Curcio G, Ferrara M, De Gennaro L. Sleep loss, learning capacity and academic performance. Sleep Med. Rev. 2006; 10: Mather N, Wendling BJ. Linking cognitive assessment results to academic interventions for students with learning disabilities. In: Flanagan DP, Harrison PL, eds. Contemporary Intellectual Assessment: Theories, Tests, and Issues, 2nd edn. Guilford Press: New York, 2005; Alfonso VC, Flanagan DP, Radwan S. The impact of the Cattell Horn Carroll theory on test development and interpretation of cognitive and academic abilities. In: Flanagan DP, Harrison PL, eds. Contemporary Intellectual Assessment: Theories, Tests, and Issues, 2nd edn. Guilford Press: New York, 2005; Jonides J, Smith EE, Koeppe RA, Awh E, Minoshima S, Mintun MA. Spatial working memory in humans as revealed by PET. Nature 1993; 363: Harrison Y, Horne JA. Sleep loss impairs short and novel language tasks having a prefrontal focus. J. Sleep Res. 1998; 7: Randazzo AC, Schwitzer PK, Walsh JK. Cognitive function following 3 nights of sleep restriction in children Sleep 1998; 21: Sadeh A, Gruber R, Raviv A. Sleep, neurobehavioral functioning, and behavior problems in school-aged children. Child Dev. 2002; 73: Sadeh A, Gruber R, Raviv A. The effects of sleep restriction and extension on school-age children: What a difference an hour makes. Child Dev. 2003; 74: Lezak MD, Howieson DB, Loring DW, Hannay HJ, Fischer JS. Neuropsychological Assessment, 4th edn. Oxford University Press: New York, Sternberg S. Memory scanning: new findings and current controversies. Q. J. Exp. Psychol. 1975; 27: Steenari MR, Vuontela V, Paavonen EJ, Carlson S, Fjallberg M, Aronen ET. Working memory and sleep in 6- to 13-year-old schoolchildren. J. Am. Acad. Child Adolesc. Psychiatry 2003; 42: Varkevisser M, Kerkhof GA. Chronic insomnia performance in a 24-h constant routine study. J. Sleep Res. 2005; 14: Australian Bureau of Statistics. Australian Social Trends. Australian Bureau of Statistics: Canberra, Sheridan MA, Hinshaw S, D Esposito M. Efficiency of the prefrontal cortex during working memory in attentiondeficit/hyperactivity disorder. J. Am. Acad. Child Adolesc. Psychiatry 2007; 46: Goodman R. The strengths and difficulties questionnaire: a research note. J. Child Psychol. Psychiatry 1997; 38: Gold JM, Carpenter C, Randolph C, Goldberg TE, Weinberger DR. Auditory working memory and Wisconsin card sorting test performance in schizophrenia. Arch. Gen. Psychiatry 1997; 54: Turner ML, Engle RW. Is working memory capacity task dependent? J. Membr. Lang 1989; 28: Engle RW. What is working memory capacity? In: Roediger HL III, Nairne JS, Neath I, Suprenant A, eds. The Nature of Remembering: Essays in Honor of Robert G. Crowder. American Psychological Association: Washington, DC, 2001; Patilla P, Broadbent P. Ten-Minute Maths: Oral and Written Mental Maths. Addison Wesley and Longman: Melbourne, Unsworth N, Heitz RP, Schrock JC, Engle RW. An automated version of the operation span task. Behav. Res. Methods 2005; 37: The Authors 153

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