How many diurnal types are there? A search for two further “bird species”

Personality and Individual Differences 72 (2015) 12–17

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How many diurnal types are there? A search for two further ‘‘bird species’’ Arcady A. Putilov ⇑, Olga G. Donskaya, Evgeniy G. Verevkin Research Institute for Molecular Biology and Biophysics, Siberian Branch of the Russian Academy of Sciences, 2, Timakova Street, Novosibirsk 630117, Russia

a r t i c l e

i n f o

Article history: Received 19 June 2014 Received in revised form 30 July 2014 Accepted 5 August 2014

Keywords: Morningness–eveningness Chronotype Sleepiness Alertness Sleep–wake regulation Overt circadian rhythm Wake drive

a b s t r a c t Morning and evening types (‘‘larks’’ and ‘‘owls’’) are most alert in the morning and in the evening, respectively. Because they are also characterized by preference for early awakening–early bedtime and late awakening–late bedtime, respectively, two questions arise: Is it possible to distinguish two additional types preferring early awakening–late bedtime and late awakening–early bedtime? If yes, are they similar to the types of habitual short and long sleepers? One hundred and thirty healthy participants of sleep deprivation experiments were subdivided into four (2  2) types depending upon self-assessed preferences for morning and evening earliness/lateness. The differences between these types in self-assessed morning/evening earliness/lateness were associated with the differences in levels of morning/evening– early night sleepiness. However, self-reports on their pre-experimental wakeups/bedtimes showed that the two additional types were not identical to the types of short and long sleepers. It seems that the fourtype classification of morning/evening preference represents pairwise combinations of low/high levels of waking ability during the morning/evening–early night hours, and that such variation in waking ability is irrelevant to individual differences in sleep ability, i.e., variation in sleep need, sleep capacity, sleep quality, napping propensity, etc. Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction Two diurnal types or chronotypes nicknamed ‘‘larks’’ and ‘‘owls’’ represent two poles of the dimension of morning/evening preference (Adan et al., 2012; Di Milia, Adan, Natale, & Randler, 2013; Horne & Ostberg, 1977; Kerkhof, 1985). A ‘‘lark’’ or morning type is most alert in the morning, whereas an ‘‘owl’’ or evening type is most alert in the evening. These types are also characterized by preference for early awakening–early bedtime and late awakening–late bedtime, respectively. Two questions then arise: Is it possible to recognize two more diurnal types characterized by preference for early awakening–late bedtime and late awakening–early bedtime? If yes, are they similar to the types of habitual short and long sleepers? The reviews of the earliest scientific literature on morning/ evening preference (Horne & Ostberg, 1977; Kerkhof, 1985) mentioned the publication of Leopold-Levi who as early as in 1932 added ‘‘late to bed–early to rise’’ and ‘‘early to bed–late to rise’’ types to ‘‘early to bed–early to rise’’ and ‘‘late to bed–late to rise’’ types that were suggested by Wuth in 1931. However, the majority ⇑ Corresponding author. Address: 11, Nipkowstr, 12489 Berlin, Germany. Tel.: +49 30 61290031/53674643; fax: +49 30 53674643. E-mail address: [email protected] (A.A. Putilov). http://dx.doi.org/10.1016/j.paid.2014.08.003 0191-8869/Ó 2014 Elsevier Ltd. All rights reserved.

of further studies of morning/evening preference in the field of chronobiology interpreted this individual trait as a uni-dimensional rather than two-dimensional construct. The major reason for popularity of strictly uni-dimensional approach might be the widely accepted believe in close association of the self-reported chronotypological differences with underlying uni-dimensional individual variation in the entrained circadian phase that might be set on a relatively earlier or a relatively later clock time (Adan et al., 2012; Kerkhof, 1985). Consequently, the oldest and still most respected questionnaire instruments for chronotypological self-assessment were proposed in the form of uni-dimensional scales. When factor analysis and other conventional psychometric methods were employed for evaluation of these scales, they yielded 2–3 orthogonal factorial dimensions (Brown, 1993; Larsen, 1985; Monk & Kupfer, 2007; Moog, Hauke, & Kittler, 1982; Neubauer, 1992; Smith, Reilly, & Midkiff, 1989). For instance, even factor analysis of a shortened version of such kind of morning/evening scale, the Diurnal Type Scale (Torsvall & Åkerstedt, 1980), sorted out its 7 items into two rotated factors representing morning and evening habitual traits (Torsvall & Åkerstedt, 1980). Furthermore, similar multi-dimensionality was again reported in the studies of more recently suggested revisions of earlier developed questionnaires. Particularly, three factors were revealed by factor analyzing the 13-item modi-

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fication of earlier proposed morningness–eveningness scales named the Composite Scale of Morningness (Caci et al., 2005; Randler, 2009; Smith et al., 1989), and the analysis of its reduced (7-item) version yielded two factors (Randler, 2009). Only the shortest questionnaire tool for self-assessment of diurnal type, the 5-item Reduced Version of Morningness–Eveningness Questionnaire (Adan & Almirall, 1991), was shown to be uni- rather than multi-dimensional, but its satisfactory reliability contrasts with high levels of reliability (>0.80) consistently reported for larger questionnaires (reviewed by Di Milia et al., 2013). A fundamental issue of factor models is the correct specification of the number of factors, and this number might be seriously overestimated in factor analysis. However, some other lines of evidence support the suggestion of multi-dimensionality of morningness– eveningness trait. For instance, Martynhak, Louzada, Pedrazzoli, and Araujo (2010) drew attention to a possible additional type of morning/evening preference that can be differentiated from morning, evening, and neither/intermediate types on the pattern of responses to items of chronotypological questionnaires. These ‘‘bimodal’’ types tend to answer some questions as morning types, but answer others as evening types, which in sum provides the same result as for intermediate types (Martynhak et al., 2010; Randler & Vollmer, 2012). More direct evidence for multi-dimensionality of morning/ evening preference was found in two independent studies applying the conventional psychometric procedures (i.e., such as item response analysis) to development of a new chronobiological questionnaire. Both these studies led to construction of two separate – morning and evening – scales for self-assessment of morningness– eveningness (Putilov, 1990, 1993; Roberts, 1998). Nevertheless, the results of such questionnaire studies had not yet stimulated the attempts to find more solid experimental evidence for plausibility of two-dimensional representation of morningness–eveningness trait. It is widely accepted that, to assess validity of morningness– eveningness scales, such external criteria as self-ratings of alertness–sleepiness and self-reports of wakeup/bedtime can be used (i.e., Díaz-Morales, Dávila, & Gutiérrez, 2007; Kerkhof, Korving, Willemse-v.d. Geest, & Rietveld, 1980; Natale & Cicogna, 1996; Randler, 2009; Vidacek, Kaliterna, Rodosevic-Vidacek, & Folkard, 1988). Therefore, our goal was to provide experimental support for two-dimensional (four-type) approach to structural representation of morningness–eveningness trait. In order to achieve this goal and to explain the possible causes of two-dimensionality of individual variation in morning/evening preference, we analyzed self-reports collected prior to and in the course of experiments on 24-h sustained wakefulness. We hypothesized that four (2  2) chronotypes predicted by the two-dimensional classification of morning/evening preference are also significantly different in the 24-h fluctuations of self-reported alertness–sleepiness levels. We also quantitatively simulated the regulatory processes underlying these 24-h fluctuations of alertness–sleepiness to provide a better understanding of the chronophysiological underpinning of the observed individual variation.

2. Materials and methods The experimental study was performed in accordance with the ethical standards laid down in the Declaration of Helsinki. Its protocol was approved by the Ethics Committee of the Siberian Branch of the Russian Academy of Sciences. Informed written consent was obtained from each of the study participants. One hundred and thirty healthy individuals were studied as paid volunteers. The median and mean ages of 54 male participants were 23 and 27.4 years (Standard Deviation or SD = 10.1), respectively. For 76

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female participants, the mean and median ages were 24 and 30.8 years (SD = 13.4), respectively. In the experimental morning (between 08:00 and 8:30 o’clock), the participants were admitted to a research unit of the institute and remained there until approximately 11:00 the next morning. Over the next 24 h they completed 9 electroencephalographic (EEG) recording sessions divided by 3-h intervals and 5 performance trials. The participants also completed several questionnaires at the time intervals between the performance and EEG measurements. If they did not participate in the research procedures, they were engaged in such activities as reading, writing, playing board and computer games, surfing the Internet, watching TV, listening to music, consuming light snacks and drinks (but not alcohol or caffeinated beverages), etc. The participants were asked to avoid any medications, vigorous physical activity, and exposure to light brighter than 500 lux. The study personnel ensured that they always remained awake. The 72-item Sleep–Wake-Pattern Assessment Questionnaire or SWPAQ (Putilov, 2007, 2011) was administered twice: prior to the experiment and soon after arriving in the research unit. Two 12item scales of the SWPAQ, M or Morning Lateness and E or Evening Lateness, allow separate self-assessment of sleep–wake behavior in the morning and evening–early night hours. Four remaining 12item scales of the SWPAQ were designed to self-assess waking and sleep abilities (W and V or Anytime and Daytime Wakeability, and F and S or Anytime and Nighttime Sleepability). Scorings on two Lateness scales (M and E) were used for subdivision of the study participants into four (2  2) predicted diurnal types. The participants with lower than averaged score were sorted into type 0, and the remaining participants were sorted into type 1. By combining M and E typologies, four chronotypes (i.e., 0–0, 0–1, 1–0, and 1–1) were distinguished (see also Tables 1 and 2). Study participants were asked to keep their regular sleep–wake schedule during a week prior to the experimental day and to report their sleep history for each of these pre-experimental days. The individual mean clock times for going to bed (bedtime) and awakening (wakeup) were averaged over 5 pre-experimental days and used for calculation of midsleep and sleep duration (see the notes to Table 1). Sleep history also included some other self-reports including times of nap episodes, sleep latency (the self-perceived time interval between going to bed and falling asleep), sleep satisfaction (scored from 1 = ‘‘was not satisfied at all’’ to 5 = ‘‘was excellent’’), etc. Right after each EEG recording, the participants were asked to determine their self-perceived alertness–sleepiness on the 9-point Karolinska Sleepiness Scale or KSS (Åkerstedt & Gillberg, 1990). Four chronotypes were compared on KSS self-scorings provided for two morning time points (the 1st and 9th at 9:00) and two evening–early night time points (the 5th and 6th at 21:00 and midnight; Table 1). The 24-h time courses of KSS alertness–sleepiness were expressed as deviations from the averaged KSS score (Fig. 1). All statistical analyses were performed with the Statistical Package for the Social Sciences (SPSS) version 20.0 (IBM, Armonk, NY, USA). To examine differences between four chronotypes on the time course of KSS score, two-way repeated measure ANOVA (rANOVA) was performed with repeated measure ‘‘Time of day’’ (9 clock times), the independent factor ‘‘Chronotype (types 0–0, 0–1, 1–0, and 1–1), and age and sex as covariates. Huynh–Feldt correction of the degrees of freedom was used to control for type 1 error associated with violation of the sphericity assumption, but the original degrees of freedom are reported in the legend to Fig. 1. The Bonferroni multiple comparison test was used in the post hoc analysis to reveal significant pairwise differences between chronotypes in daily mean KSS score. Table 1 illustrates significance of the results yielded by one-way ANOVAs of chronotyperelevant self-reports with the independent factor ‘‘Chronotype’’ and two covariates, and it gives the results of the Bonferroni multi-

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Table 1 Differences between four diurnal types in self-reports. Self-report

Mean ± SEM for 4 chronotypes (N = 130 in total) 0–0, N = 29

0–1, N = 32

F(3, 124) 1–0, N = 25

1–1, N = 44

KSS self-scorings for morning and evening–early night hours KSSm1 0.86 ± 0.32c⁄ 0.94 ± 0.30e⁄ KSSe5 0.78 ± 0.28 1.50 ± 0.26e⁄ a⁄⁄c⁄⁄ KSSe6 0.73 ± 0.34 0.78 ± 0.31a⁄⁄d⁄ KSSm9 1.16 ± 0.36 0.73 ± 0.33e⁄

0.31 ± 0.34 0.42 ± 0.29f⁄ 0.50 ± 0.36d⁄f⁄ 1.89 ± 0.38

0.36 ± 0.26c⁄e⁄ 1.43 ± 0.22e⁄f⁄ 0.73 ± 0.27c⁄⁄f⁄ 1.94 ± 0.29e⁄

4.5⁄⁄ 3.8⁄ 6.3⁄⁄⁄ 3.1⁄

Initial time point for decline phase (simulation of individual time course of KSS score) t2 21.0 ± 0.4a⁄⁄c⁄⁄⁄ 22.7 ± 0.4a⁄⁄

21.8 ± 0.4f⁄

23.2 ± 0.3c⁄⁄⁄f⁄

7.2⁄⁄⁄

Sleep times averaged for 5 pre-experimental days Wakeup 8.11 ± 0.34c⁄ Bedtime 0.12 ± 0.27c⁄ Midsleep 4.12 ± 0.28c⁄ Duration 8.00 ± 0.24

8.26 ± 0.31 0.83 ± 0.25 4.54 ± 0.26 7.44 ± 0.22

8.74 ± 0.35 0.76 ± 0.28 4.75 ± 0.29 7.99 ± 0.25

9.30 ± 0.26c⁄ 1.22 ± 0.21c⁄ 5.26 ± 0.22c⁄ 8.09 ± 0.19

3.2⁄ 3.3⁄ 3.5⁄ 2.0

12-item waking and sleep ability scales of the SWPAQ W scale 1.20 ± 1.13a⁄⁄ V scale 2.09 ± 1.00b⁄ F scale 0.53 ± 1.25 S scale 2.98 ± 1.14

7.36 ± 1.01a⁄⁄d⁄⁄⁄e⁄⁄⁄ 4.74 ± 0.92d⁄⁄⁄e⁄⁄⁄ 1.19 ± 1.14 2.96 ± 1.04

1.29 ± 1.18d⁄⁄⁄ 2.34 ± 1.05b⁄d⁄⁄⁄ 2.80 ± 1.30 3.85 ± 1.19

1.14 ± 0.89e⁄⁄⁄ 0.46 ± 0.79e⁄⁄⁄ 0.86 ± 0.98 3.93 ± 0.90

11.9⁄⁄⁄ 8.9⁄⁄⁄ 2.1 0.3

Notes: Major results of one-way ANOVA with the independent factor ‘‘Chronotype’’ and age and sex as covariates. SEM: Standard error of the mean; 0–0: A combination of 0 (early)-morning with 0 (early)-evening earliness/lateness; 0–1: 0-morning and 1 (late)-evening earliness/lateness; 1–0: 1 (late)-morning and 0-evening lateness; 1–1: 1morning and 1-evening lateness. KSSm1, KSSe5, KSSe6, and KSSm9: KSS scores for morning (1st and 9th) and evening–midnight time points (5th and 6th); Wakeup and Bedtime: Clock times for awakening and going to bed from sleep history self-reports averaged over 5-day interval; Midsleep: A half of the distance between Wakeup and Bedtime in clock hours; Duration: A difference between clock times for Wakeup and Bedtime in hours; W, V, F and S scales: Scales of the SWPAQ for self-assessment of waking and sleep abilities; ⁄⁄⁄P < 0.001, ⁄⁄P < 0.01, ⁄P < 0.05: Level of significance of F(3, 124)-value for main effect of factor ‘‘Chronotype’’ and t-value for post hoc pairwise comparisons of 4 types with Bonferroni adjustment for the number of comparisons (a, b, and c 0–0 vs. 0–1, 1–0, and 1–1, respectively, d and e 0–1 vs. 1–0 and 1–1, respectively, and f 1–0 vs. 1–1).

Table 2 Parameters of the chronotype-averaged 24-h time courses of alertness–sleepiness. Parameter

Initial value (range from, to)

Time courses for 4 chronotypes (N = 130 in total) 0–0, N = 29

0–1, N = 32

1–0, N = 25

1–1, N = 44

0.10 1.8

0.58 2.8

0.10 2.5

0.10 3.9

Wake-promoting homeostatic process, X(t): t1 4.0 (4.0, 8.0) t2 20.0 (20.0, 24.0) Xd 0 (3, 2) Xb 2 (3, 2) Xl 4 (8, 1) Tb 20 (1, 60) Td 20 (1, 60)

5.7 21.7 0.79 2.54 3.62 6.09 5.49

6.7 22.7 1.88 1.64 2.48 7.41 4.23

6.4 22.4 0.26 2.66 4.52 7.64 8.36

7.8 23.8 1.09 2.40 3.11 6.21 4.49

Sleep-promoting homeostatic process, Xu(t): Xu1 5 (4, 7) Xlu 1 (3, 4) Tdu 20 (1, 60) Sum of squares

4.00 1.59 20.17 0.06

4.00 0.48 15.00 0.05

4.00 2.57 19.91 0.04

4.00 1.80 23.63 0.13

Circadian process, C(t): A u(M)

1 (0.1, 3) 6.0 (0.0, 4.0)

Notes: Simulations based on Eqs. (1a) and (1b) and (2a) and (2b) (see Section 2). Sum of squares: Resulting sum of the squares of the residuals after its minimizing by least squares method. See also the actual and simulated time courses in Fig. 1.

ple comparisons of significance of pairwise differences between types. The model-based simulations were performed using a rhythmostat model that was earlier used to simulate alertness–sleepiness rhythms of morning- and evening-oriented types in order to explain 5-h difference between these types in the timing of alertness peak (Putilov, 2014b; Putilov, Donskaya, & Verevkin, 2014). This model was originally suggested as a modification of the ‘‘classical’’ two-process (somnostat) model of sleep–wake regulation (Borbély, 1982; Daan, Beersma, & Borbély, 1984). The major postulate is that an overt circadian rhythm can be viewed as a homeostatic process which parameters are modulated by a circadian process (Putilov, 1995a). The circadian process is represented by a sine function that accounts for the influence of the circadian

pacemaker and, thus, can be regarded as a simpler analogue of the circadian process in the two-process model (Borbély, 1982; Daan et al., 1984). The homeostatic process was suggested to be fully identical to the homeostatic process of the two-process model in its mathematic formulation (Borbély, 1982; Daan et al., 1984). However, it was additionally proposed that this formulae can be used not only for the description of the sleep–wake cycle homeostasis or somnostat (Putilov, 1995a), but also for explanation of chronophysiological mechanism underlying any other particular process representing a homeostatically regulated body function, i.e., the circadian rhythm of core body temperature or body thermostat (Putilov, 1995b), the ultradian sleep cycle or ultradian somnostat (Putilov, 2014a), the alertness–sleepiness rhythm (Putilov, 2014b, 2014), etc. If t1 and t2 are the initial time points for the

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Fig. 1. Chronotype-averaged 24-h time courses of self-scored alertness–sleepiness. Time courses (diamonds and thin solid lines) with 95% Confidence Interval (vertical bars) and their simulations based on Eqs. (1a) and (1b) and (2a) and (2b) (dotted lines). To obtain actual time courses of KSS scores, they were expressed as deviations from the general mean KSS score and subjected to two-way rANOVA with repeated measure ‘‘Time of day’’ (9 time points), the independent factor ‘‘Chronotype’’, and age and sex as covariates. ‘‘Chronotype’’ significantly interacted with ‘‘Time of day’’ (F24/992 = 2.8, P < 0.001). Moreover, the major effect of the independent factor was significant (F3/124 = 3.3, P < 0.05) with the only significant pairwise difference (0.84 score) between types 0–1 and 1–0 (P < 0.05 after Bonferroni adjustment for the number of comparisons). See the parameters’ estimates in Table 2.

buildup and decline phases of the alertness-regulating process, the formulae for two (daytime and nighttime) parts of 24-h fluctuations of alertness–sleepiness describe two exponential curves:

XðtÞ ¼ ½X u þ CðtÞ  f½X u þ CðtÞ  X b g  eðtt1 Þ=½T b kCðtÞ ;

ð1aÞ

XðtÞ ¼ ½X l þ CðtÞ  f½X d  ½X l þ CðtÞg  eðtt2 Þ=½T b kCðtÞ ;

ð1bÞ

where CðtÞ ¼ A  sinð2p  t=24 þ /0 Þ is a periodic function with 24-h period (Putilov, 1995a, 2014a,b). Since alertness demonstrates a gradual declining trend from one day to another in the course of prolonged wakefulness, we also suggested a possibility that the upper asymptote, Xu, cannot remain constant throughout the buildup (daytime) phase as it is suggested in Eq. (1a). Instead, it can exponentially decline (Eq. (1b)) under influence of the corresponding phase of another homeostatic process, Xu(t):

 X u ðtÞ ¼ ½X lu þ CðtÞ  X u1  ½X lu þ CðtÞ  eðtt1 Þ=½T du kCðtÞ ;

ð2aÞ

where Xu1 is a value for the initial time point t1, whereas Xlu and Tdu are an asymptote and a time constant, respectively, of the declining upper asymptote Xu(t). As for the course of the following (decline) phase of the homeostatic process (Eq. (1b)), its upper asymptote Xu can remain constant during this phase, because the level of the process fails to recover during night hours due to prolongation of wakefulness at expense of sleep:

X u ðtÞ ¼ X u2 ;

ð2bÞ

where Xu2 is a value of Xu(t) for the initial time point t2 (Putilov, 2014a,b). In this model, the primary regulatory process X(t) was interpreted as the homeostatic process governed by a wake drive, while the secondary regulatory process Xu(t) was postulated to represent the influence of a sleep drive (i.e., a wake-promoting process regulating wake–sleep pressure, and a sleep-promoting process associated with accumulation of sleep debt during wakefulness). This interpretation supports the conceptualization of the drives for wake and sleep as the opponent sleep–wake regulating processes (Dijk & Czeisler, 1995; Edgar, Dement, & Fuller, 1993).

The least-squares method was used to perform simulations of individual (Table 1) and chronotype-averaged time courses of alertness–sleepiness (Table 2 and Fig. 1). Since the master clock (circadian pacemaker) can control all three phase parameters of the model, t1, t2, and /0 (the initial time point for the buildup phase, the initial time point for the decline phase, and the initial phase of circadian modulation, respectively), these parameters were suggested to be closely interrelated. In the present simulations, a shift in one of the phase parameters (e.g., t2 from 22.00 to 22.50) causes the corresponding shift of two other parameters (e.g., t1, from 6.00 to 6.50). Moreover, the same durations of buildup and decline phases were suggested (16 and 8 h, respectively) due to the absence of significant difference between four diurnal types in sleep duration (Table 1). The major results on parameters’ estimates for chronotype-averaged time courses are given in Table 2 and illustrated in Fig. 1. 3. Results The rANOVA yielded significant differences between four chronotypes on both mean KSS score and its 24-h variation as indicated by and the significant main effect of the independent factor and highly significant interaction of the repeated measure with the independent factor ‘‘Chronotype’’ (see the legend to Fig. 1). In particular, the results suggested that the difference in the time courses of KSS score was significant for ‘‘traditional’’ chronotypes (early–early and late–late types, 0–0 and 1–1) and that the difference between mean scores was significant for two additional chronotypes (early–late and late–early types, 0–1 and 1–0). Level of significance of pairwise differences between chronotypes depended upon clock time (Table 1). It was revealed for KSS self-scoring obtained during morning and evening–early night hours (1st, 5th, 6th, and 9th time points), but not on the intervals characterized by the highest and lowest alertness levels (i.e., other 5 time points). The pairwise comparisons of sleep timing data yielded significant difference between two ‘‘traditional’’ chronotypes on wakeup, bedtime, and midsleep. Such findings were supported by the results of simulation of individual time courses of alertness–sleepiness that revealed significant phase difference between ‘‘traditional’’ rather than additional chronotypes (Table 1).

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However, the analysis of sleep history also suggested the absence of the significant chronotypological differences in sleep duration (Table 1). The results of ANOVAs performed for scores on SWPAQ’s scales (Table 1) indicated that the diurnal types were significantly dissimilar on waking ability assessed with W and V scales but not on sleep ability assessed with F and S scales. The most remarkable differences were found between the two additional types (Table 1). Finally, we did not find that four chronotypes were significantly different in sleep-associated self-reports, such as sleep latency, sleep satisfaction, nap habits, etc. (the results are not shown). Quantitative simulations of time curses suggested a link between the self-reported chronotypological differences and the underlying individual variation in the parameters of alertness-regulating processes. The simulations confirmed the existence of highly significant circadian phase difference between ‘‘traditional’’ types 0–0 and 1–1, but not between types 0–1 and 1–0 (Table 1). The difference between these additional types in both morning and evening–midnight KSS scorings (Fig. 1 and Table 1) can be related to variation in other than phase parameters of the model (Table 2). Such variation can explain the observed lowering the levels of alertness in types 0–1 as compared to those in types 1–0 both before and after nighttime sleep. 4. Discussion Although different reports (see Introduction) had questioned uni-dimensionality of morningness–eveningness construct, experimental evidence for validity of the two-dimensional (four-type) classification of morning/evening preference has not been yet provided. Statistical analysis and simulation of experimental data on the time course of alertness–sleepiness demonstrated that the two-dimensional (2  2) classification of morning/evening preference allows distinguishing between four diurnal types, and each of these types can be also differentiated from any of three other types on self-scorings of alertness–sleepiness levels in the course of 24-h sleep deprivation. As one can expect, two ‘‘traditional’’ chronotypes (early–early and late–late types) were found to be different in the circadian phase parameters, such as t1, t2, and /0 . The estimates of these parameters revealed more than 2-h phase difference that is in agreement with earlier published experimental results on melatonin and temperature rhythms (i.e., Duffy, Dijk, Hall, & Czeisler, 1999). In accord with such expectations, we also did not reveal significant phase difference between two additional chronotypes, i.e., they do not belong to the circadian types with either extremely early or extremely late entrained phase of alertness–sleepiness rhythm (Fig. 1, Tables 1 and 2). This result is in line with the reports pointing on heterogeneity of neither/intermediate group of individuals that was detected through applying uni-dimensional tools for self-assessment of morningness–eveningness trait (Martynhak et al., 2010; Randler & Vollmer, 2012). According to the results on model-based simulation and preexperimental sleep history, these two additional chronotypes were unrelated to the types of short and long sleepers. Instead, types 0–1 (early–late) differed from types 1–0 (late–early) on mean alertness levels (Fig. 1). Particularly, self-scored alertness of types 0–1 was lowered and that of types 1–0 types was heightened both during morning and evening–early night hours (Table 1). This finding was supported by the results on significant differences between chronotypes in scores on W and V (waking ability) scales. Such results on the significant differences between types 0–1 and 1–0 in self-reported alertness level and self-assessed waking ability fully agree with the Roberts’ conceptualization of these two chronotypes named ‘‘high energetic’’ and ‘‘lethargic’’ types, respectively (Roberts, 1998).

The present results indicate that individual variations in the parameters of the underlying wake-promoting and sleep-promoting processes can be unrelated one to another. The former variation can be mostly responsible for the self-reported differences between chronotypes in waking ability, and, hence, it can explain the link between this variation and individual differences in scores on alertness-associated scales, such as the KSS, W and V (Table 1). In contrast, the latter variation can determine the differences in sleep ability that were not fully examined in our sleep deprivation study. Therefore, future research can be aimed on testing the prediction that individual variation in the parameters of the sleeprather than wake-promoting process is closely associated with scorings on F and S scales, as well as with self-reports on sleep length, sleep quality, sleep flexibility, nap habits, sleep satisfaction, etc. 5. Conclusion The four type (two-dimensional) classification of morning/ evening preference was validated with data on the 24-h time course of alertness–sleepiness scores. The differences in selfassessed morning/evening lateness were found to predict the differences in morning/evening–early night alertness–sleepiness levels. The questionnaire, experimental and simulating results indicate that four chronotypes can represent pairwise combinations of low/high levels of waking ability in the morning/evening–early night hours. References Adan, A., Archer, S. N., Hidalgo, M. P., Di Milia, L., Natale, V., & Randler, C. (2012). Circadian typology: A comprehensive review. Chronobiology International, 299, 1153–1175. Adan, A., & Almirall, H. (1991). Horne & ostberg morningness–eveningness questionnaire: A reduced scale. Personality and Individual Differences, 12, 241–253. Åkerstedt, T., & Gillberg, M. (1990). Subjective and objective sleepiness in the active individual. International Journal Neuroscience, 52, 29–37. Borbély, A. A. (1982). A two process model of sleep regulation. Human Neurobiology, 1, 195–204. Brown, F. M. (1993). Psychometric equivalence of an improved Basic Language Morningness (BALM) scale using industrial population within comparisons. Ergonomics, 36, 191–197. Caci, H., Adan, A., Bohle, P., Natale, V., Pornpitakpan, C., & Tilley, A. (2005). Transcultural properties of the composite scale of morningness: The relevance of the ‘‘morning affect’’ factor. Chronobiology International, 22, 523–540. Daan, S., Beersma, D. G. M., & Borbély, A. A. (1984). Timing of human sleep: Recovery process gated by a circadian pacemaker. American Journal of Physiology: Regulatory, Integrative and Comparative Physiology, 246, R161–R178. Díaz-Morales, J. F., Dávila, M. C., & Gutiérrez, M. (2007). Validity of the morningness–eveningness scale for children among Spanish adolescents. Chronobiology International, 24, 435–447. Dijk, D. J., & Czeisler, C. A. (1995). Contribution of the circadian pacemaker and the sleep homeostat to sleep propensity, sleep structure, electroencephalographic slow waves, and sleep spindle activity in humans. Journal of Neuroscience, 15, 3526–3538. Di Milia, L., Adan, A., Natale, V., & Randler, C. (2013). Reviewing the psychometric properties of contemporary circadian typology measures. Chronobiology International, 30, 1261–1271. Duffy, J. F., Dijk, D. J., Hall, E. F., & Czeisler, C. A. (1999). Relationship of endogenous circadian melatonin and temperature rhythms to self-reported preference for morning or evening activity in young and older people. Journal of Investigational Medicine, 47, 141–150. Edgar, D. M., Dement, W. C., & Fuller, C. A. (1993). Effect of SCN lesions on sleep in squirrel monkeys: Evidence for opponent processes in sleep–wake regulation. Journal of Neuroscience, 13, 1065–1079. Horne, J., & Ostberg, O. (1977). Individual differences in human circadian rhythms. Biological Psychology, 5(3), 179–190. Kerkhof, G. A. (1985). Inter-individual differences in the human circadian system: A review. Biological Psychology, 20, 83–112. Kerkhof, G. A., Korving, H. J., Willemse-v.d. Geest, H. M., & Rietveld, W. J. (1980). Diurnal differences between morning-type and evening-type subjects in selfrated alertness, body temperature and the visual and auditory evoked potential. Neuroscience Letters, 16, 11–15. Larsen, R. L. (1985). Individual differences in circadian activity rhythm and personality. Personality and Individual Differences, 6, 305–311.

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