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Time of Day, Intellectual Performance, and Behavioral Problems in Morning Versus Evening Type Adolescents: Is There a Synchrony Effect?

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We administered measures of fluid and crystallized intelligence to Morning- and Evening-type adolescents who were tested either during a morning session or an afternoon session, at times chosen to reflect the limits of the average school day schedule. For the fluid intelligence measures, there was a synchrony effect, with better performance at times that matched individuals' preferences. A composite measure of the subtests used (block design, digit span, and vocabulary) computed to a 6 point difference in IQ estimates. We also assessed the behavioral adjustment of these participants and found heightened levels of maladaptive behavior for Evening-type adolescents. Adolescents tested at their nonoptimal times of day and adolescents who are Evening-types appear to be at risk for poor academic performance and Evening-types appear to be at risk for behavioral adjustment problems.
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Time of day, Intellectual Performance, and Behavioral Problems
in Morning Versus Evening type Adolescents: Is there a
Synchrony Effect?
David Goldsteina,*, Constanze S. Hahna, Lynn Hashera,b, Ursula J. Wiprzyckaa, and Philip
David Zelazoa
aUniversity of Toronto, Psychology, 100 St. George Street, Toronto, Ont., Canada M5S 3G3
bThe Rotman Research Institute of Baycrest Centre, Toronto, Ont., Canada M6A 2E1
Abstract
We administered measures of fluid and crystallized intelligence to Morning- and Evening-type
adolescents who were tested either during a morning session or an afternoon session, at times chosen
to reflect the limits of the average school day schedule. For the fluid intelligence measures, there was
a synchrony effect, with better performance at times that matched individuals’ preferences. A
composite measure of the subtests used (block design, digit span, and vocabulary) computed to a 6
point difference in IQ estimates. We also assessed the behavioral adjustment of these participants
and found heightened levels of maladaptive behavior for Evening-type adolescents. Adolescents
tested at their nonoptimal times of day and adolescents who are Evening-types appear to be at risk
for poor academic performance and Evening-types appear to be at risk for behavioral adjustment
problems.
Keywords
Chronotype; Intellectual performance; Adolescence; Time of day; Synchrony effect
1. Introduction
Articles in the popular press suggest that the school day starts too early for adolescents. The
scientific evidence for such claims is limited and typically ignores the potential importance of
the synchrony between an individual’s time of day preference, or ‘chronotype,’ and the time
at which cognitive operations are performed. This is likely nontrivial because recent research
with adults suggests that performance on a number of school relevant tasks (such as attention
and memory) varies in synchrony with chronotype, with better performance in the morning
than later in the day for Morning-types and better performance later in the day than in the
morning for Evening-types (e.g., Hasher, Goldstein, & May, 2005; Intons-Peterson, Rocchi,
West, McLellan, & Hackney, 1998; May, 1999; Yoon, May, Goldstein, & Hasher, in press).
Of particular interest for school performance is the fact that children move away from being
Morning-types towards being Evening-types early in adolescence (e.g., Kim, Dueker, Hasher,
& Goldstein, 2002; Roenneberg et al., 2004), a change that when coupled with an early start
to the school day and potential sleep deficits (e.g., Andershed, 2005; Carskadon, Wolfson,
Acebo, Tzischinsky, & Seifer, 1998), may create special problems for Evening-type teens.
Research on sleep, for example, suggests that for adolescent girls in Brazil, school performance
*Corresponding author. Tel.: +1 416 978 3405; fax: +1 416 978 4811. E-mail address: dgoldst@psych.utoronto.ca (D. Goldstein).
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improves through the school day while self-reported sleepiness decreases (Andrade & Menna-
Barreto, 1996). There is also evidence that rising early for school, even for as few as two days
a week, results in greater complaints about difficulties in attention and concentration in the
classroom by fifth grade children (Epstein, Chillag, & Lavie, 1998; see also Wolfson &
Carskadon, 1998). There is also some evidence that behavioral problems are more common in
poor sleepers than in control age mates (Sadeh, Gruber, & Raviv, 2002).
In the present study, we explore the potential importance of the age-related shift from
Morningness to Eveningness for school performance. To this end, we assessed intellectual and
behavior patterns for Morning- and Evening-type adolescents aged 11-14 who were tested in
the morning versus in the afternoon, at times that were in synchrony with their preferred time
of day versus at times that were not. Because IQ is a reasonably good predictor of classroom
performance (Wechsler, 1991), we assessed intellectual potential using three subtests of a
widely used measure of intelligence, the Wechsler Intelligence Scale for Children-III (WISC-
III). Behavior patterns were assessed using the Child Behavior Checklist (CBCL), a widely
used instrument that assesses social competence and behavior problems (Achenbach &
Rescorla, 2001).
Based on evidence in the young adult literature showing synchrony effects in fundamental
executive processes (e.g., Hasher, Zacks, & May, 1999; May, 1999; Yoon et al., in press), we
predicted that adolescents tested at times that are in synchrony with their preferred time of day
would perform significantly better on fluid intelligence measures than adolescents tested at
their non preferred time of day. In contrast and again based on previous studies with adults
(e.g., Hasher et al., 2005), we expected no differences on a measure of well established
knowledge (i.e., vocabulary test). Also, we predicted that Evening-type adolescents would be
more likely to manifest behavioral and school related problems compared to their Morning-
type peers. The results are dramatic: IQ assessments varied greatly (the equivalent of about 6
IQ points) as a function of the match between optimal time of day and testing time. As well,
data from the CBCL suggest that Evening-type adolescents are differentially likely to be at
risk for academic, social, and behavioral/emotional problems.
2. Method
2.1. Participants and Recruitment
Using a telephone interview protocol, we administered the Children’s Morningness-
Eveningness Preferences scale (CMEP; Carskadon, Vieira, & Acebo, 1993) to 259 young
adolescents (132 males, 127 females) ranging in age from 11-14 years (M = 12.48, SD = 1.07).
From this pool, the scores of 80 young adolescents (41 males, 39 females) at ages 11 (n = 20),
12 (n = 21), 13 (n = 19), and 14 (n = 20) years fell into the two outer quartiles on the CMEP
and, as a result, they were classified as Morning- or Evening-types.
2.2. Design
Twenty participants were assigned to each of four conditions created by crossing chronotype
(Morning- or Evening-type) and testing time (morning or afternoon), with comparable numbers
of males and females in each. There were no significant differences between those assigned to
optimal and nonoptimal testing times in age, gender, grade in school, self-reported amount of
sleep, or parental education levels. All participants were tested during the summer.
2.3. Materials
2.3.1. Children’s Morningness-Eveningness Preferences (CMEP) scale—This 10-
item, multiple-choice scale was adapted by Carskadon et al. (1993) from the widely used
Horne-Ostberg Morningness-Eveningness Questionnaire (MEQ; Horne & Ostberg, 1976).
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Scores range from 10 (Extreme Evening preference) to 42 (Extreme Morning preference). Cut-
off scores for Morningness and Eveningness, based on the outer quartiles of CMEP scores of
the telephone sample, were 32 and above for Morning-type and 24 and below for Evening-
type. The CMEP is known to have good reliability (Kim et al., 2002), a finding which we
confirmed with the present sample (see below).
2.3.2. Child Behavior Checklist (CBCL)—This inventory assesses social competence and
behavioral problems relevant to classroom performance; it is highly reliable and valid and can
be completed by parents or guardians (Achenbach & Rescorla, 2001). Scores on three scales
(Activities, Social, and School) make up the Total Competence score. A Total Problems Score
is comprised of Internalizing (Anxious/Depressed, Withdrawn/Depressed, and Somatic
Complaints), Externalizing (Rule-Breaking Behavior and Aggressive Behavior), and neither
(Social Problems, Thought Problems, Attention Problems, and Other Problems) syndrome
groupings. T-scores (converted from raw scores) provide cut-off points for borderline/clinical
range criteria, which help identify scores of concern for behavioral/emotional problems. The
cut-off point is 37 for the Total Competence score, 65 for syndrome scores, and 60 for the
Internalizing, Externalizing, and Total Problems scores.
2.3.3. WISC-III Subtests—Following standard procedures, we administered the
Vocabulary, Block Design, and Digit Span subtests from the WISC-III (Wechsler, 1991).
Vocabulary provides a highly reliable estimate of verbal ability, an aspect of crystallized
intelligence (Kaplan & Saccuzzo, 2005), and correlates well with Verbal and Full Scale IQ
(Wechsler, 1991). Block Design provides a reliable measure of nonverbal reasoning and is a
reasonable proxy for Performance IQ. Digit Span (Forward and Backward) provides a measure
of short-term (auditory) memory. Together with Block Design, Digit Span correlates well with
Full Scale IQ and provides a reasonable estimate of fluid intelligence (Kaplan & Saccuzzo,
2005). Age based standardized scores (range 1-19) are available for all three subtests and were
used as dependent variables.
2.3.4. Procedure—Participants who obtained extreme telephone CMEP scores were invited
to participate in a laboratory-based session. Participants were randomly assigned to either a
morning session (8-10 am) or an afternoon session (1-3 pm). These times were chosen to reflect
the limits of the average school day schedule. Testing was individually administered.
Parents or guardians completed the CBCL while adolescents completed the CMEP for the
second time and reported their bedtime and wake-up time for the previous night. The WISC-
III subscales were administered in the following order: Block Design, Vocabulary, Forward
Digit Span, and Backward Digit Span. Participants were compensated $5 and reimbursed for
transportation.
3. Results
3.1. Chronotype Preferences
3.1.1. Telephone interview assessment—Mean CMEP scores declined consistently
with age: age 11 (M = 29.69; SD = 4.96; n = 59); age 12 (M = 27.84; SD = 4.57; n = 73); age
13 (M = 27.30; SD = 5.49; n = 70); age 14 (M = 26.23; SD = 4.08; n = 57). The movement
away from Morningness associated with increasing age was reliable, F(3, 255) = 5.30, p = .
001, ν2 = .06, replicating other findings (e.g., Kim et al., 2002; Roenneberg et al., 2004).
In order to assess the reliability of the telephone-based CMEP scores we re-administered the
CMEP to the 80 adolescents who came into the lab. The correlation between the telephone and
laboratory CMEP scores was highly reliable (r = .93, p < .001). We used the initial CMEP
scores assessed through the telephone interviews to conduct all subsequent analyses. The
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CMEP scores for the 80 laboratory study participants were as follows: age 11 (M = 29.80; SD
= 6.88; n = 20); age 12 (M = 28.48; SD = 6.23; n = 21); age 13 (M = 26.79; SD = 7.56; n =
19); age 14 (M = 25.50; SD = 6.42; n = 20).
3.1.2. Laboratory assessment—Because our goal was to assess performance as a function
of the synchrony between chronotype and time of testing independent of the age of the
participants, we first conducted a 2 (Chronotype: Morning-type vs. Evening-type) × 2 (Testing
Time: morning vs. afternoon) ANOVA with age as the dependent variable. Consistent with
norms reported in previous research (e.g., Kim et al., 2002), Evening-type adolescents (M age
= 12.75, SD = 1.10) were older than Morning-type adolescents (M age = 12.23, SD = 1.10), F
(1, 76) = 4.45, p = .04, ν2 = .06. Despite considerable effort, we were unable to recruit sufficient
Evening-type younger children and Morning-type older children to reduce this difference.
Nevertheless, this finding does reflect the representation of chronotypes in the population. For
interpretation of the subsequent results, it is critical to note that no other effects were reliable
(Fs < 1). Thus, the average ages of participants tested in the morning versus the afternoon did
not differ, nor did the average ages of the Morning-types tested in the morning differ from
those tested in the afternoon and similarly for Evening-types at the two testing times. Therefore,
all further analyses were collapsed across age. As well, because of the distribution of ages, we
used standard scores for both the WISC-III subtests as well as for the CBCL scores.
An additional goal was to assess performance as a function of the synchrony between
chronotype and time of testing independent of sleep duration of the participants. To this end,
we conducted a 2 (Chronotype: Morning-type vs. Evening-type) × 2 (Testing Time: morning
vs. afternoon) ANOVA with amount of sleep prior to the study as the dependent variable. This
score was computed as the difference between self-reported sleep and rising times on the night
before and morning of the laboratory session. Morning-type adolescents (M = 9.40 h, SD =
1.11) reported longer sleep times than Evening-type adolescents (M = 8.72 h, SD = 1.91), F
(1, 76) = 3.97, p = .05, ν2 = .05. Also, adolescents tested in the morning (M = 8.71 h, SD =
1.41) reported shorter sleep times than adolescents tested in the afternoon (M = 9.41 h, SD =
1.70), F(1, 76) = 4.11, p = .05, ν2 = .05. The interaction between chronotype and time of testing
was not significant (F < 1), confirming that adolescents tested at their optimal time of day
(M = 9.00 h) did not differ in the amount of sleep from those tested at their nonoptimal time
of day (M = 9.12 h). Despite this critical equivalence, we entered reported sleep duration as a
covariate into the intellectual performance analyses. Controlling for sleep duration did not alter
any conclusions.
3.2. WISC-III Tasks
Two separate 2 (Chronotype) × 2 (Testing Time) ANOVAs were conducted on the standard
scores on Vocabulary and for the mean of the combined Block Design and Digit Span standard
scores, with the latter measure providing a reasonable estimate of fluid intelligence (Kaplan &
Saccuzzo, 2005). No main effects were found (all ps > .45); neither chronotype alone nor testing
time alone could account for differences between adolescents tested at their optimal and
nonoptimal times of day on any of these measures. The Chronotype × Testing Time interaction
was not significant for the Vocabulary subtest, F < 1 (see Fig. 1a), replicating findings
suggesting that access to semantic knowledge and other forms of crystallized intelligence does
not change across the day (Hasher et al., 2005).
For the fluid intelligence measure, the Chronotype × Testing Time interaction was significant,
F(1, 76) = 5.16, p = .03, ν2 = .06. Adolescents tested at their optimal times of day (M = 12.08,
SD = 2.49) significantly outperformed adolescents tested at their nonoptimal times (M = 10.86,
SD = 2.24), t(78) = 2.29, p = .03, d = .52 (see Fig. 1b).
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3.3. CBCL
Checklists were completed by 78 parents (66 mothers and 12 fathers) and 2 relatives. We
compared T-scores from Morning- and Evening-type adolescents on those scales most relevant
to behavior and school performance (see Table 1). Analyses were also carried out using
standard scores (M = 100, SD = 15) as the dependent variables on the relevant CBCL scales,
computed as recommended by Achenbach and Rescorla (2001). Overall, the findings did not
differ substantively from those obtained using T-scores. Therefore, it was decided to use the
more conservative T-scores.
3.3.1. Competence scales—Relative to Evening-type adolescents, Morning-type
adolescents received higher scores on the Social scale, t(78) = 2.27, p < .05, d = .51, on the
School scale, t(67) = 2.22, p < .05, d = .50, and on the Total Competence scale, t(78) = 2.84,
p < .01, d = .64.
3.3.2. Syndrome scales—Relative to Evening-type adolescents, Morning-types scored
lower on the Attention Problems scale, t(58) = 2.44, p < .05, d = .55, and on the Aggressive
Behavior scale, t(58) = 2.41, p < .05, d = .54, suggesting that Evening-type adolescents have
greater behavioral problems at home and school.
3.3.3. Normal and borderline/clinical ranges—Using the composite Total Problems
scale, we assessed whether chronotype discriminates between scores falling into the normal
versus borderline/clinical range of the composite. A 2 (Chronotype) × 2 (Range: Normal vs.
combined Borderline and Clinical) chi-square test yielded significant results, χ2(1) = 6.65, p
= 0.01, ω = .74. For Evening-types, 12 of the 40 (30%) were in the borderline/clinical range,
while for Morning-types 3 of the 40 (7.5%) were in the borderline/clinical range. Thus,
Evening-type adolescents were four times more likely than Morning-type adolescents to exhibit
behaviors that place them within the borderline/clinical range for serious behavioral problems.
4. Discussion
There have been many attempts to assess the way in which the performance of children and
adolescents varies across the day, with a decidedly mixed pattern of results (e.g., Dunn, Dunn,
Primavera, Sinatra, & Virostko, 1987; Klein, 2001; Morton & Kershner, 1985). However, none
of these studies systematically assessed the performance of children or young adolescents as
a function of their individual Morningness or Eveningness preference and the time at which
testing occurred. We report the first such study and we note that the times of testing we used
were consistent with school hours.
Our findings confirm a synchrony effect for adolescents: measures of fluid intelligence (Digit
Span and Block Design) vary such that performance is better at optimal compared to
nonoptimal times of day. Like others (e.g., Hasher et al., 2005), we found no differences across
the day for well established (crystallized) knowledge, here vocabulary. Using an estimate of
the Full Scale IQ score and collapsing across the fluid and crystallized measures reported here,
we found approximately a 6 point difference in Full Scale IQ equivalents as a function of the
match between an individual’s circadian arousal pattern and the time of testing. In the
intervention literature (for a review, seeBrooks-Gunn, 2003), successful programs report
changes of no more than 3-4 IQ points. For example, even extensive training with music lessons
for one year (Schellenberg, 2004) showed smaller IQ differences than those reported here.
We note two important limitations to the current study. The first is that this study was conducted
in the summer when adolescents may have more control over their sleep schedules than they
do during the school year. The synchrony effects seen here may then actually underestimate
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those seen during the school year, particularly for Evening-types, who likely suffer from sleep
deficits on school nights (Carskadon et al., 1998; Sadeh et al., 2002).
The second limitation stems from our use of subjective estimates of sleep duration. Of course,
these are not likely to be as reliable as more objective estimates that assess activity patterns
across the day. Although the present findings suggest that the synchrony between chronotype
and time of testing is important over and above differences in sleep, no strong conclusion should
be drawn without objective measures of duration and quality of sleep.
We note that the present findings are useful in establishing the existence of a synchrony effect
in the cognitive performance of adolescents, as has been found before in young and older adults
(e.g., Hasher et al., 2005). We note particularly that for those adolescents close to meeting the
criteria for access to special education or gifted courses, the IQ synchrony effect reported here
is the kind of a difference that could have serious consequences. This, of course, remains to be
determined by future research. The current results are also useful in confirming the reliability
of the CMEP, and particularly of a telephone administration of the test.
The mechanisms that underlie the adolescent shift away from Morningness may have
environmental, social, and biological underpinnings (Carskadon et al., 1993; Kim et al.,
2002; Roenneberg et al., 2004). Whatever the source of this shift, our evidence suggests that
Evening-type adolescents are far more likely than Morning-types to fall into the borderline/
clinical category of the most widely used behavioral assessment instrument. A recent study by
Andershed (2005). That study suggests that Evening-type adolescents are more likely to have
difficult family relations, as well as poorer relations with peers and teachers than non Evening-
types. It is possible that Evening-type adolescents may have particular difficulties adjusting to
the typical early morning start to the school day found in many parts of the world, and over
time these difficulties may be compounded to create very substantial problems for academic
and social success.
Acknowledgements
This research was supported by National Institute of Aging Grant NIA R37 AGO 4306 awarded to Lynn Hasher and
by grants from the Natural Sciences and Engineering Research Council (NSERC) and the Canada Research Chairs
Program to Phil Zelazo. For assistance with data collection we thank Silvia Celucci, Sarah Douglas, Anoop Ganda,
Nicole Recel, and David Vitale. The authors also thank Sunghan Kim and Martin Ralph for helpful suggestions in the
design of the study.
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Fig. 1.
Means (+SE) for (a) crystallized intelligence (Vocabulary) and (b) fluid intelligence (Block
Design and Digit Span combined) by chronotype and testing time.
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Goldstein et al. Page 9
Table 1
Mean Scores (and Standard Deviations) for CBCL scales by Chronotype
Variable Chronotype p valueb
Morning (n = 40) Evening (n = 40)
CBCL Competence scalesa
Activities scale 53.50 (9.37) 50.05 (9.05) ns
Social scale 51.83 (9.36) 47.13 (9.16) *
School scale 50.85 (5.34) 47.38 (8.33) *
Total Competence scale 53.93 (9.94) 47.65 (9.81) **
CBCL Syndrome scalesa
Anxious/Depressed scale 55.48 (6.33) 56.63 (7.24) ns
Withdrawn/Depressed scale 54.83 (5.69) 54.48 (5.88) ns
Somatic Complaints scale 54.98 (6.02) 55.83 (6.08) ns
Social Problems scale 54.85 (5.97) 54.93 (6.51) ns
Thought Problems scale 54.83 (5.96) 56.80 (7.12) ns
Attention Problems scale 53.88 (4.33) 57.58 (8.55) *
Rule-Breaking Behavior scale 52.23 (2.61) 54.00 (5.73) ns
Aggressive Behavior scale 52.30 (3.82) 55.53 (7.57) *
Internalizing grouping 51.98 (10.00) 52.90 (10.10) ns
Externalizing grouping 47.03 (8.11) 50.38 (10.96) ns
Total Problems Score 49.00 (9.55) 52.23 (10.68) ns
Note: ns = not significant.
aAll reported means are based on CBCL T-scores (Achenbach & Rescorla, 2001).
bIndependent samples t—tests.
*p < .05.
**p < .01.
Pers Individ Dif. Author manuscript; available in PMC 2007 February 1.
... Given the significant physiological and psychological changes that occur during adolescence, it is plausible that these factors could influence daily variations in physical and cognitive performance within this age group [6]. In this context, Goldstein et al. [7] highlighted the impact of time-of-day on adolescents' cognitive performance and behavior, emphasizing variability influenced by individuals' circadian preferences. Ouergui et al. [8] indicated that both dynamic and isometric judo chin-up tests show time-of-day variations, with adolescents performing better in the afternoon than in the morning. ...
... [37] and Goldstein et al. [7] have shown that cognitive performance and behavioral issues vary according to circadian preferences. Finally, we acknowledge some limitations in the present study. ...
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Previous studies investigating the diurnal variation of physiological and psychological variables during exercise have yielded conflicting results. The present investigation was designed to assess the impact of time-of-day on short-term repetitive maximal performance [i.e., single and two consecutive bouts of 5m shuttle run test (5mSRT), long jump test] as well as cognitive ability and psychological variables [i.e., mood states (POMS) and Hooper questionnaire] in male and female adolescents. In a randomized study design, 21 healthy adolescents (12 females and 9 males; age: 15.9±1.04 years) performed at 08h00 and 16h00 two consecutive 5mSRT (with 20 min of rest interval in-between), to assess the greatest distance (GD), the total distance (TD), the average distance (AD) and the fatigue index (FI), and the long jump test (LJT). Perceived exertion (RPE) was recorded immediately after each 5mSRT. The POMS and Hooper questionnaires and the digit-cancellation test (i.e., attention) were realized during each session. The results showed that TD and AD were greater in the morning than in the afternoon during the 1st (p = 0.048 and 0.048, respectively) and the 2nd (p = 0.0016 and 0.0017, respectively) 5mSRT; while GD was time-of-day independent (p = 0.16). For the FI, results demonstrated a significant time-of-day effect with highest values recorded in the afternoon compared to the morning during the 2nd 5mSRT (p = 0.017). In contrast, attention scores and the long jump test performance recorded before and after each 5mSRT were time-of-day independent for all measures (p > 0.05). Likewise, POMS parameters [anxiety (p = 0.15), depression (p = 0.71), anger (p = 0.23), fatigue (p = 0.07), confusion (p = 0.58), vigor (p = 0.16), TMD (p = 0.06) and interpersonal relationships (p = 0.19)], RPE [1st (p = 0.22) and 2nd (p = 0.43) 5mSRT] and delayed onset muscle soreness (p = 0.34) were time-of-day independent; while, fatigue (p = 0.03), sleep (p = 0.01) and stress (p = 0.027) estimated by the Hooper questionnaire were higher in the afternoon compared to the morning. In conclusion, morning is more effective than afternoon session for improving short-term repetitive maximal performance and reducing fatigue during the 5mSRT for adolescents. However, regarding psychological parameters and cognitive function and contrarily to previous researches, there is no time-of-day effects.
... Aiello (2022) found similar results: DT performance was higher around lunchtime and afternoon than morning for both originality and effectiveness. Explanations for the effect of time of day typically focus on cognitive or mental fatigue (Boksem et al., 2005;Goldstein et al., 2007;Mullette-Gillman et al., 2015), and sometimes attention as it may suffer after students have worked for several hours, doing their academic work (Lufi et al., 2011;Sievertsen et al., 2016). There are practical implications, if time of day is indeed associated with performance on tests of creative potential. ...
... The second objective of the current study was to test whether or not there was a difference in DT performance related to the time of the school day (first vs. second half). Previous studies using various cognitive tests have uncovered such differences, and it was possible that DT would also differ (Boksem et al., 2005;Goldstein et al., 2007;Mullette-Gillman et al., 2015;Sievertsen et al., 2016). Interestingly, Sievertsen et al. (2016Sievertsen et al. ( , p. 2621 reported that ''for every hour later in the day, test performance decreases by 9% when administering standardized tests.'' ...
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... population is evident only for cognitive tasks involving fluid intelligence, which refers to the ability to think abstractly and reason quickly regardless of prior knowledge. Crystallized intelligence, which reflects accumulated knowledge acquired over time, is unaffected by daily fluctuations in circadian rhythms (Goldstein et al. 2007). ...
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... This is of concern because adequate sleep is critical for optimal brain development (Tarokh et al., 2016). Also, eveningness is consistently associated with problems in the emotional (e.g., Fares et al., 2015), cognitive (e.g., Goldstein et al., 2007;Short et al., 2013a), behavioral (e.g., Adan et al., 2010;Negriff et al., 2011), social, and physical health domains (e.g., Miller et al., 2015;Schlarb et al., 2014). Hence, eveningness may be an important intervention target among adolescents. ...
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