Daytime sleepiness and its evaluation

Sleep Medicine Reviews, Vol. 6, No. 2, pp 83–96, 2002 doi:10.1053/smrv.2002.0191, available online at http://www.idealibrary.com on

SLEEP MEDICINE reviews

THEORETICAL REVIEW

Daytime sleepiness and its evaluation Raymond Cluydts1, Elke De Valck1, Edwin Verstraeten1 and Paul Theys2 Department of Cognitive and Physiological Psychology, Vrije Universiteit Brussel, Brussels 2Sleep Disorders Centre, Universitair Psychiatrisch Centrum St. Jozef, Kortenberg, Belgium KEYWORDS sleepiness, somnolence, wakefulness, attention, evaluation, measurement, conceptualization

Summary Basic models of sleepiness, focusing on the homeostatic and circadian components of sleepiness, are able to predict important fluctuations of sleepiness. However, they fail in explaining certain sleepiness phenomena, as for instance in insomnia patients. To meet this shortcoming, modern models incorporate the arousal component of sleepiness, in addition to the sleep drive. While these models mainly concentrate on short-term changes in sleepiness, “state” sleepiness, there are indications that a stable characteristic level of sleepiness, “trait” sleepiness, is also an important determinant of a person’s level of sleepiness. This leads to a conceptualization of sleepiness in which situational factors modify a basal level of sleep drive and arousal. It implies that sleepiness is not a unitary concept and can reflect essentially different states. Multiple sleepiness assessment tools have been proposed in the past. The majority of them offer valuable information, but they do not grasp all aspects of sleepiness. We should bear in mind that tools for assessing sleepiness are always operationalizations reflecting the theoretical framework the investigator has on sleepiness. Hence, rather than searching for a gold standard for the measurement of sleepiness, future research effort should be aimed at linking the various measurement techniques with the hypothesized underlying components of sleepiness on a sound empirical basis.  2002 Published by Elsevier Science Ltd

INTRODUCTION Whereas empirical measurement is much more straightforward in comparison with the measurement of a “hypothetical construct” [1], the latter needs an operationalization which has a strict relationship with the concept it is supposed to grasp. The concept of sleepiness can be considered as one such hypothetical construct. Although it may at first glance seem intuitive and the existence of sleepiness is not questioned, its operationalization, however, Correspondence should be addressed to: Raymond Cluydts, PhD, Department of Cognitive and Physiological Psychology, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussel, Belgium. Tel: ++32 (0) 2 629 25 29; Fax: ++32 (0) 2 629 24 89; E-mail: [email protected]

is a complex task. Laboratory experiments as well as clinical description of the different phenomena of sleepiness provide us with data and evidence who in turn become input to the validation of a proposed theoretical model of sleepiness. As the term is often used for essentially different phenomena, we will make a distinction in this manuscript between sleepiness as a theoretical construct and its operationalization, whenever possible. One behavioural operationalization that is often used considers sleepiness as the subject’s tendency to doze off or to fall asleep, also known as sleep propensity [2–4]. In this context, at a theoretical level, sleepiness is considered to reflect a physiological need for sleep, in analogy to hunger reflecting the physiological need for food. It is proposed that a shortage of sleep causes sleepiness and sleeping

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reverses the sleepy state, as is the case for eating and the hungry state. One operationalization, used in the multiple sleep latency test (MSLT) (see below), infers the degree of sleepiness from the speed with which one tries to satisfy the need for sleep and, thus, the ease of falling asleep as well as other parameters such as the delta power. It has been mentioned that the need for sleep is independent of the feeling of sleepiness, as this can be masked by motivation or other physiological needs [5]. This operational definition that is somewhat generally accepted can be disputed. Healthy adults fall asleep faster during the day as a result of lack of nightly sleep. However, a subgroup of insomnia patients who have problems in attaining enough sleep at night have difficulties falling asleep during the day, despite their subjective feeling of being in need of sleep [6]. This certainly raises questions about the interrelation of sleepiness, sleep drive and sleep propensity. At least in insomnia this relationship is not clear. As a consequence, alternative definitions of sleepiness have been proposed. A˚kerstedt [7] considered sleepiness to be an attempt to turn the central nervous system on to sleep and thus it reflects an effort to resist sleep. This would imply that someone who does not fight back sleep will not experience any sleepiness. In an attempt to clarify the complex concept of sleepiness, some classifications of different “types” of sleepiness have been proposed. “Normal occurring” sleepiness has been distinguished from “pathological” sleepiness, the former being the result of the circadian rhythm, the latter being the result of altered sleep scheduling, e.g. as a consequence of a sleep debt [8]. Within pathological sleepiness, a further distinction between “habitual” and “occasional” sleepiness can be made. Habitual sleepiness represents a more or less stable condition, as is the case for hypersomnia disorders such as the obstructive sleep apnoea syndrome. Occasional sleepiness on the contrary is the result of a specific provoking factor, e.g. jet lag or medication. Other authors distinguish “optional” from “excessive” sleepiness. Optional sleepiness is described as the ease of falling asleep at socially acceptable moments, whereas excessive sleepiness points to sleepiness that occurs at a time the individual would normally be expected to be awake [4] or at a time one wants to be awake [5]. Finally, a frequently mentioned division is made between physiological sleepiness or sleep propensity, as already described,

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and “subjective” sleepiness. The latter term refers to the subjective perception of a signal for the need for sleep [5] or, in other words, the feelings and symptoms associated with the drowsy state [3]. The differentiation between sleepiness and related concepts such as fatigue is often emphasized. Acute fatigue is generally considered as a condition resulting from physical effort and prolonged activity. Moments of rest, without sleep, will ameliorate it. On the contrary, sleepiness does not imply any prior physical effort per se and decreases as a consequence of a sleep period. A straightforward definition of sleepiness that covers the complexity of the phenomenon is not available today. The conceptualization of sleepiness requires a broader theoretical framework.

MODELS OF SLEEPINESS Basic models of sleepiness The two-process model of sleep regulation, developed by Borbe´ly [9], implies a basic model of sleepiness that is still broadly adhered to. The model delineates the processes involved in the regulation of waking and sleeping and stipulates that sleepiness arises from the combined action of two components: a homeostatic–monotonic and a circadian– rhythmic component. The circadian component, process C, leads to a dip in alertness in the early morning hours. The homeostatic component, process S, represents the amount of prior wake and the amount of prior sleep. As prior wake time increases and prior sleep time decreases, sleepiness augments. Empirical support for this basic model has been obtained in several studies: subjective, performance and physiological measures of sleepiness have been shown to be sensitive to both time of day and sleep deprivation, reflecting respectively circadian and homeostatic effects [10–12]. Further validation of the S and C components was offered by a study of A˚kerstedt and Folkard [13]. They used a quantitative model based on both components, for predicting sleepiness on a scale between 1 and 16. A regression analysis, with sleepiness-related electroencephalogram (EEG) parameters as criteria, showed that sleepiness could be predicted with considerable accuracy (r2 >0.70) in truck and train drivers and volunteers studied in laboratory conditions. In addition, criteria for interpretation of

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the predictions were established, identifying critical levels of alertness, which offer a tool for predicting safety risks in specific situations, such as traffic or shift work. It has been empirically confirmed that the homeostatic and circadian components are generated by separate brain mechanisms and neurotransmitter systems and that both of them influence sleep and vigilance states. As to process S, recent data point to the neuromodulator adenosine as the mediator of sleepiness following prolonged wakefulness, namely adenosine levels in the basal forebrain progressively increase with prolonged wakefulness and slowly decrease in recovery sleep [14]. In addition, brain activity is found to be organized in a very specific way during non-rapid eye movement and rapid eye movement (REM) sleep. The former is supposed to be related to a deactivation in the upper brainstem, thalamic nuclei and basal forebrain and the latter to activation in specific regions of the pons and the thalamic nuclei [15]. The anterior hypothalamus appears to control the circadian processes [16]. In the original framework, S and C are presented as two independent processes, with S oscillating between two thresholds that are modulated by the circadian process. An alternative conceptualization suggests that sleepiness results from the continuous interaction of the two components, so it can be represented as a single process [17]. Even though current data do not allow excluding one of these two options, continuous interaction of the circadian and the homeostatic components of sleepiness seems more plausible from a physiological point of view. A third factor, process W, has been proposed to be added to the original two-process model of sleep regulation [18]. It represents sleep inertia or the drop in alertness in the first few hours after awakening and is considered to be a significant contributing factor to sleepiness. This has given rise to the threeprocess model of alertness regulation. Some shortcomings are inherent to both the two- and the three-process models of sleepiness– alertness. Firstly, it is evident that other factors than the model parameters influence sleepiness in a substantial way. These include the ultradian rhythms, which provoke afternoon sleepiness. Secondly, the model applies to mean group data and large interindividual differences can be expected [19]. Thirdly, the effect of various contributing factors of sleepiness, such as processes S and C, seems

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plausible, but it is still not clear which factors are of decisive importance and which are only secondary. There are some indications that under normal conditions the rhythmic processes are principal constituents of sleepiness [20]. The homeostatic influence would be relatively small, but constantly present. Its contribution to sleepiness is expected to become more important in sleepdeprived conditions. A more fundamental criticism to the proposed models concerns the exclusive emphasis on the sleep drive. Strong indications of a decisive role of arousal or a wake drive on the likelihood of falling asleep are available. Secondly, it can be argued that “state” aspects or acute, situational changes in sleepiness have been accentuated too much in the past, whereas “trait”- or person-specific aspects of sleepiness have been largely ignored. These issues will be discussed in more detail in the following sections.

The arousal component of sleepiness–alertness Whether somebody will fall asleep, feel sleepy, experience vigilance problems or show physiological signs of sleepiness appears to depend on the level of sleep need or sleep drive, as well as on the level of arousal or wake drive. The idea of two opponent processes in sleep–wake regulation was formally stated for the first time by Edgar et al. [21] and can be summarized as follows. Sleep propensity depends on the relative strength of two mutually inhibiting drives, the wake and the sleep drives. The sleep drive consists of the C and S components of the two-process model; the wake drive is composed of chronobiological factors as well and of environmental factors, such as posture and physical activity [5]. The relative preponderance of the wake or the sleep drive will cause respectively wakefulness or sleep. Johns [2] incorporated this line of thought in his four-process model of sleep and wakefulness and stressed the importance of environmental contributors, such as the soporific nature of a situation, to the wake drive which was largely ignored previously. Further in the text, sleep need or sleep requirement are used as synonyms for the sleep drive; the wake drive is called arousal and we refer to the tendency to fall asleep as sleep propensity, generally considered as the operationalization of sleepiness. Although the wake drive has been less studied

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in detail compared with the sleep drive and is missing in the two- and three-process models of alertness regulation, convincing arguments of its significant influence on sleepiness exist. The absence of a simple relation between sleep quality and sleep propensity can be interpreted as an argument in favour of the arousal component of sleepiness. Generally, an increase in sleep propensity during the day is noticed after sleep deprivation. However, studies showing an association between a smaller total sleep time and worse nocturnal sleep quality on the one hand and smaller daytime sleep tendency on the other hand in normals as well as in insomniacs are available [22, 23]. Introducing the arousal concept can solve this apparent contradiction. A high level of arousal is supposed to interfere both with sleep and with the daytime ability to fall asleep, even though the sleep drive may be high. In insomniacs it can be concluded that their problem is one of hyperarousal, making it more difficult to initiate sleep, but not decreasing their sleep drive [6, 23]. On the other hand, the model also is able to explain the general sleep deprivation effect. When the arousal component is at a baseline level, sleep deprivation leads to an increase in sleep propensity, because of an increase in sleep drive. A study of Bonnet and Arand [24] empirically supports the existence of the sleep drive and an arousal component of sleepiness. Sleep drive and arousal were separately manipulated, the former by partial and total sleep deprivation, the latter by physical activity. Both factors independently influenced the ability to stay awake (maintenance of wakefulness test (MWT)) and the tendency to fall asleep (MSLT). The effect of activity—the arousal effect—was even more robust than the sleep deprivation effect. In line with this, multivariate methods showed that physiological distress, which can be interpreted as an indicator of chronic psychophysiological arousal, and nocturnal motor activity, probably caused by a high general activation, are significant predictors of sleep latency measures [25]. As is the case for the homeostatic and the circadian components, an anatomical substrate can be identified for the arousal factor; that is, the ascending reticular activating system is designated to be the cortical waking system [26]. Arousal, operationalized as the EEG activation, seems to be mediated by not a single but various neuro-

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transmitter systems in both brainstem and basal forebrain. In this context, the neurotransmitter orexin has been found to play a specific role. It promotes arousal via a direct excitatory action on the basal forebrain arousal system, as shown in orexin II receptor knockout mice [27]. Regarding the relative importance of the different components of sleep propensity or sleepiness, some advocates of the dominant effect of arousal [24] and more specifically of the decisive role of environmental factors [2] can be found. Unequivocal evidence for these statements is not yet obtained. There is some external validation for this innovative conceptualization of sleepiness. For instance, the conceptualization offers a more comprehensive insight into sleep disorders [6]. At first sight, it may seem difficult to explain why some patients with patterns of chronic sleep restriction develop complaints of falling asleep at inappropriate times and places, while others with similar sleep patterns compensate well. Here, an underactive arousal system, in conjunction with a normal sleep system, provides a reasonable explanation. As for insomniacs, it can be supposed that their daytime fatigue is secondary to hyperarousal, preventing them from fulfilling their sleep need, as already mentioned. The model even allows some insight to be acquired into the problem of sleep state misperception. This might represent an extremely high sleep requirement, combined with a high level of arousal. The arousal prevents the patient to satisfy his extreme sleep need, even after one night of sleep. In conclusion, sleepiness or sleep propensity can be conceptualized as consisting of two independent factors, an arousal and a sleep component. The sleep propensity of a particular person can be presented as the result of the person’s position on a continuum ranging from hypoarousal to hyperarousal and on a second, independent, continuum indicating the level of sleep need. How these two factors combine to result in a sleep propensity level has yet to be untangled. At the moment, it implies that a high level of sleepiness can reflect a high sleep drive, a low arousal level or a combination of both. In other words, it supports the idea of the existence of qualitatively different states of sleepiness, proposed as early as the beginning of the 1980s [28], but only recently further explored [2], instead of a single unitary phenomenon of varying degrees.

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Trait sleepiness:

State sleepiness:

-Basal level of sleep drive

-Situational sleep drive: Process S Process C Process W Modified by

-Basal level of arousal

-Situational arousal: Process C Extero- and enteroceptive input (posture, physical activity, soporific nature of the situation)

Figure 1 Conceptual model of sleepiness.

State and trait sleepiness (Fig. 1) The influence of long-term trait-like physiological variables, besides process S, time of day (process C), drugs, the external situation and the physiological activity level, on sleep propensity has been suggested now and then, but most of the time only as a marginal remark. In our opinion, trait aspects of sleepiness deserve more explicit scientific attention. In adults without recognizable sleep disorders clear individual differences in daytime sleep propensity have been noticed. Some adults seem to fall asleep in less than 5 min on an MSLT, which is usually labelled as a pathological level of sleepiness. Here it cannot be interpreted in this way as it considered people without any alertness or sleepiness problem [23]. In a basal study of Carskadon and Dement [29] it was clear that such a low sleep latency could not always be explained as resulting from chronic partial sleep deprivation, often seen in young adults, as it was quite stable over seven days of 8 h time in bed. This raised the possibility that it reflects a stable characteristic sleep onset latency. On the one hand, this phenomenon can be related to a particular baseline level of sleep drive in each individual. During chronic partial sleep deprivation to 5 h time in bed each night, some healthy subjects reached a pathological level of sleepiness, while

others obtained scores in the borderline range or even had an “alert” profile [29]. Thus, it seems that the amount of sleep required to achieve an adequate level of alertness clearly varies among individuals and can be considered as a “trait”. On the other hand, it can be hypothesized that individuals are characterized by a specific level of arousal. Again, the idea was raised from insomnia studies, where a relatively stable physiological hyperarousal was hypothesized to be the underlying cause of this sleep disorder. The concept of a traitlike arousal level seemed to apply to normal subjects as well. In a general population, good sleepers who can easily fall asleep at any moment without having any sleepiness problems have been observed. So, a baseline level of arousal, separate from the sleep drive trait, can be hypothesized. More direct evidence of this line of thought is available, but limited. Scores on the MSLT, a standard measure of sleep latency, have a high test–retest reliability over 4–14 months (r=0.96–0.97 [30], r= 0.70–0.73 [31]), indicating a stable individual characteristic of sleep propensity. A factor analysis of the individual sleep propensity measured with the Epworth sleepiness scale (ESS), a self-report measure of the chance of falling asleep in different situations of daily life, showed that sleep propensity involves three components of variation,

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other than short-term changes [32]. These form a general characteristic of the subject or a personal trait, the soporific nature of a situation and the specific response of a subject to a specific situation. Lastly, we suggest, with all proper reserve, that it is possible that these hypothesized arousal and sleep drive traits are in part determined genetically. Animal studies have shown the existence of genetic factors regulating the intensity of sleepiness after partial sleep deprivation [33]. In insomnia and hypersomnia, genetic components account for 33– 60% of the variance in sleep pattern [34]. Practice Point Sleepiness can reflect essentially different states. It can result from a high sleep drive, an arousal level that is too low or a combination of both. A distinction between these different sleepiness states has important clinical implications, such as for treatment.

Research Agenda 1. Experimental validation of the concepts “trait” and “state” sleepiness is needed. 2. Further studies on the relationship between the trait factors of sleepiness, such as basal sleep need and arousal level, and other determinants of sleepiness, such as sleep debt, are required. Are they interactive or additive factors?

EVALUATION OF SLEEPINESS Measuring sleepiness is a complex task. Multiple conceptual frameworks of sleepiness and different putative underlying mechanisms gave rise to many different operationalizations. As a consequence, a lot of assessment tools have been developed over the years (see Table 1), but they show little agreement and most of them have a limited scope, owing to the need for technical simplicity and to constraints on duration of the tests. On the other hand, some have been validated extensively. Roughly, three classes of methods have been proposed: 1. inferring sleepiness from behavioural measures; 2. self-evaluation of sleepiness by rating scales; 3. direct electrophysiological measures.

Behavioural measures Behavioural observation Simple behavioural observation can give indications of sleepiness. Yawning is the best known. Its major function is maintenance or increase in arousal when the environment provides relatively little stimulation [50]. Its value as a sleepiness measure is relatively small, as yawning frequency seems to be predictive of an increase—rather than a decrease—in arousal and is unrelated to prior amount of sleep [35]. Moreover, yawning appears to be associated with other states than sleepiness as well, such as hunger and boredom. Secondly, sleepiness is associated with specific variations of spontaneous oculomotor activity. Some eye movement parameters seem to be impaired only when levels of sleepiness are maximal; others are more sensitive to increasing levels of sleepiness [36]. The frequency of eye closure, rated by trained observers, reliably predicts hypovigilance as reflected in the performance on a psychomotor vigilance task (see below) [37]. Like head movements, closing of the eyes is a rather late phenomenon in the transition to drowsiness and sleep, sensitive only to high levels of sleepiness [38, 51]. They are variably present, as they are influenced by motivation and activity [3] and require continuous visual monitoring. Co-registration of eye movements with EEG activity gives more sensitive and specific data, as described below. Evaluation of the level of sleepiness by trained observers on the basis of the facial expression of the subject has been shown to be reliable and consistent. Ratings co-vary with other known indicators of sleepiness. However, the number of studies evaluating the technique is very limited [39] and its application in an experimental setting is difficult. Actigraphic monitoring, measuring the activity level by attaching a small monitor on the wrist of a subject, is usually used to discriminate between sleep and wakefulness to estimate sleep duration. Its ability to predict polysomnographically defined alertness states is very limited [40], since actigraphic accuracy declines as the likelihood of sleep decreases [52].

Performance tests These tests are used to measure the effect of sleepiness on different aspects of functioning. As a

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result, a specific decline in performance can be considered as an indication of the level of sleepiness. Performance decrements associated with experimentally induced sleepiness are frequently observed [53–57]. Different cognitive functions may be impaired, such as sustained attention (lapsing and time-on-task decrements), visual encoding [58, 59], and short-term and long-term memory. However, performance is not always impaired by sleep loss. The performance of short (i.e. less than a few minutes), or interesting, stimulating and engaging tasks is less susceptible. If the task is difficult or complex (e.g. tasks of long duration and/or with high signal load, or tasks with a high memory load), sleepiness effects are likely to increase. However, higher task complexity may lead to compensatory effort that maintains the level of performance through increased motivation, either internally or externally induced by incentives or knowledge of results [57, 60]. Therefore the test results do not always closely reflect the degree of somnolence, especially when the duration of the test is short or when vigorous physical activity is inherent to the test conditions [3]. When too long, these tests measure fatigue, motivation and boredom in addition to effects of sleepiness. Variants of reaction time tests are very popular measures of performance [28]. One of the most frequently used performance tests in the context of sleepiness is the psychomotor vigilance task, measuring sustained attention. It has been shown to be sensitive to partial sleep deprivation and circadian rhythm [47, 61]. Lapses in attention are poorly correlated with most currently accepted measures of sleepiness, but the tendency to fall

asleep or to stop responding during non-stimulating tasks seems very relevant to many real-world situations [62]. Ideally, the test conditions should evaluate aspects of performance that are relevant to target daily activities. Driving, known to be sensitive to sleepiness, is a typical example. Because of the increased risk for traffic accidents in sleepy persons, multiple attempts were made to simulate driving [48, 63–65], as a link between the performance on a driving simulator and real driving performance is more obvious than for reaction time tests. Moreover, driving simulators offer the opportunity to evaluate driving performance in a controlled, standardized and safe manner, making it possible to study experimentally the effect of sleepiness on this complex performance task. The psychometric properties of these systems are not yet well established. Current knowledge suggests that qualitative changes in driving behaviour are ecologically valid, but that quantitative extrapolation is not justified, as performance decreases seem to appear earlier and to be more pronounced in a simulated than in a real environment [65]. In addition, the results cannot be extrapolated yet to predict safety risk before or after treatment in individual cases, although the outcome of the test of patient groups shows significant deviations from normal controls [63] and improves with treatment [48]. As social standards for maximal alcohol intake are already established, a promising research direction is the comparison of performance decrements following a specific alcohol intake and those after various sleep deprivation periods [66].

Table 1 Overview of the assessment tools for sleepiness Behavioural measures Behavioural observation • Yawning frequency [35] • Oculomotor activity [36] • Eye closing [37] • Head movements [38] • Facial expression [39] • Actigraphy [40] Performance tests • Reaction time tests [28] • Psychomotor vigilance test [47] • Driving simulator [48]

Subjective rating scales Acute level of sleepiness • Stanford Sleepiness Scale (SSS) [41] • Karolinska Sleepiness Scale (KSS) [42] • Visual analogue scales of sleepiness/ alertness

Global level of sleepiness • ESS [19] • Sleep–wake activity inventory (SWAI) [49]

Electrophysiological measures • MSLT [3] • MWT [43] • Polysomnography [44] •Pupillometry [45] • Cerebral evoked potentials [46]

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Research Agenda Further neurocognitive research is required to study whether or not experimentally induced sleepiness and pathological sleepiness have similar effects on higher executive functioning.

Self-evaluation by rating scales Using self-evaluation of sleepiness by rating scales is the cheapest, simplest and fastest method to measure hypersomnolence, but it encounters some drawbacks inherent to self-report measurements, such as unintended bias and purposeful falsification. Roughly these assessment tools can be divided into two categories: simple self-report of the experienced level of sleepiness and the assessment of a more global level of sleepiness on the basis of the estimated sleep propensity in various daily-life situations. Scales from the first category can be used to follow short-term changes in sleepiness, in other words to assess “state” sleepiness. The second category of tests gives an indication of a subject’s global level of sleepiness, possibly approaching a more “trait”-like aspect of sleepiness.

Acute level of sleepiness: Stanford Sleepiness Scale [41], Karolinska Sleepiness Scale [42] and Visual Analogue Scales These assessment tools seem to be well suited to measure the acute sleepiness level, as they are sensitive to both sleep deprivation and time of day [11, 62]. In using the scales, one should be aware of two main problems inherent to them. Firstly, people often misinterpret symptoms of fatigue and tiredness as sleepiness. Secondly, the severity of sleepiness is typically underestimated, especially in narcoleptics [8], owing to a lack of insight in one’s own sleepiness state. A study by Pilcher et al. [67] indicated that the higher the level of sleepiness, the less accurate subjects are in estimating their own sleepiness level.

Global level of sleepiness: the Epworth Sleepiness Scale [19] and the sleep–wake activity inventory [68] In the ESS, subjects are instructed to rate the chance of dozing off or falling asleep in eight different

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situations varying in their soporific nature using an evaluation window of a few weeks. Two of the subscales of the SWAI are of importance here. One measures the degree of daytime sleepiness in a similar way as the ESS. The other considers nocturnal sleep onset. The ESS and the SWAI are, as intended, independent of short-term variations in sleepiness with the time of day and of interday variations [32]. They are aimed at measuring a general level of daytime sleepiness, seen as a stable individual characteristic. The validity of the ESS as a measure of “trait” sleepiness is further supported by its satisfactory test–retest reliability 5 months apart [49]. The scores on the SWAI show differences in the average amount of sleep and the internal consistency of the instrument is good [69]. Next, both scales are able to discriminate between normal and pathological levels of sleepiness [19, 68]. A recent study, using receiver operator characteristic curves, a robust statistical analysis method, indicated that the ESS even is a more discriminating test for narcolepsy than the MWT and MSLT (see below) [70]. According to the developers of the ESS, the test results would be easy to extrapolate, as it is an estimate of the average sleep propensity over different daily-life situations [2]. It should be mentioned that the accuracy of the ESS and the SWAI is dependent on the awareness of subjects of their falling asleep. This is not always the case, as has been shown in a study by Reyner and Horne [64], where 20% of the subjects clearly underestimated the risk of dozing off. It is further supported by a study which found that in linear regression models the ESS score only correlated with the MSLT result when it was completed by significant others, not when subjects themselves answered it [71]. It offers an explanation for the lack of a strong correlation of the ESS with the MSLT [70, 72]. Johns [70] cited from nine reports a mean correlation of 0.30 between the two tests, although in most cases, but not all, the relationship was statistically significant. Finally, this clear discrepancy between subjective rating scales and the objective measurements of sleepiness [62, 73], described in the following section, has been emphasised frequently. In this context, one should keep in mind that sleepiness is not at all a unitary concept, as discussed in the first part of the article, and that such discrepancies are rather expected.

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Electrophysiological measures Multiple sleep latency test The underlying concept of the MSLT is that of sleepiness as a physiological need for sleep. Hence, an increased tendency to fall asleep reflects greater sleepiness. The methodology was first described in 1977 [74], fine tuned in the 1980s and later a few recommendations regarding the pre-test conditions were proposed [24]. The procedure requires subjects to lie down in a quiet darkened room and not to resist falling asleep. Sleep latency is determined by standard electrophysiological means and is defined as the elapsed time from lights-out to the first epoch of any sleep stage. If sleep does not occur, the test is discontinued after 20 min. Both the mean sleep onset latency and the number of REM onset trials are important outcome variables. The test involves a polysomnographic setting, implying that it is expensive in terms of both registration facilities and technical staff. On the other hand, the thorough standardization enables comparison of research results between sleep centres around the world in normals in experimental settings and in patients with sleep disorders. The interrater reliability [75] and the test–retest reliability over time lapses between 4 and 14 months [30, 31] are good to excellent. The test has been validated in a wide variety of experimental and clinical conditions known to affect sleepiness. It has been shown to be sensitive to factors that increase sleepiness, such as acute and chronic partial and total sleep deprivation [29], sleep disruption, circadian rhythm, hypnotic and alcohol intake, narcolepsy, obstructive sleep apnoea [3] and idiopathic hypersomnia [76]. Especially in the differential diagnosis of narcolepsy, the MSLT can give information that enhances both the sensitivity and the specificity, at least after the exclusion of sleep-disordered breathing [77]. Next, the test appeared to be responsive to manipulations that reduce sleepiness, such as sleep extension [29] and caffeine ingestion [3]. Nevertheless, there are some limitations to the accuracy of the MSLT as a measure of sleepiness. Sleep latency on the MSLT does not correlate well with a number of variables expected to influence sleepiness, for example the frequency of respiratory disturbances during sleep [76]. Occasionally short latencies can be seen in normal subjects [22]. Finally, the test is not well suited for monitoring the treatment of patients with hypersomnolence [78]. Partly, this can be attributed to a floor effect in the MSLT,

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meaning that discrimination among various extreme levels of sleepiness is prevented when subjects fall asleep immediately once given permission [79]. However, some re-examination of the underlying concepts of the MSLT seems necessary, as was already mentioned in the first part of the article. It was pointed out rather early that the test fails to separate ability to fall asleep from the need for sleep [80]. Not being able to fall asleep quickly cannot be equated to not being in need for sleep, as reflected in feelings of tiredness, mood and performance. On the other hand, ability to fall asleep easily is not necessarily problematic. These inconsistencies can be linked to our conclusion stated in the previous section, being that sleep latency probably is a function of both the level of sleep need and the level of arousal. The influence of the arousal factor on sleepiness was largely ignored in the MSLT. The test environment was designed to remove as many of the alerting factors as possible and so it was assumed that the impact of arousal was negligible. However, the arousal factor can never be completely excluded, as part of it is generated internally, quite independent of the environment. This should be kept in mind, when interpreting MSLT results. This conceptual matter has consequences for the ecological validity of the test. Sleep propensity in one test situation, including the MSLT, may not be a valid indicator of a subject’s average sleep propensity in daily life, where arousal does play an important role. In conclusion, the MSLT is reliable, accurate and valid within its own context and offers unique information, but it does not grasp all aspects of sleepiness.

Maintenance of wakefulness test The methodology of this test resembles that of the MSLT, except that subjects are instructed to attempt to stay awake sitting in a dark room [81, 82] for 20 or even 40 min without taking extraordinary measures, such as vigorous mental or physical activity, to remain awake. It results in a test score that corresponds better than the MSLT with the main problem of sleepy patients, namely resist sleep in monotonous circumstances [78]. This suggests that, in those cases where there is clinical concern about activities that require sustained attention for

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safety, the use of the MWT is preferred to that of the MSLT. The latency on the MWT decreases with sleep deprivation [83] and artificial sleep fragmentation in normal subjects [43]. An increase in sleep latency is found after caffeine intake by sleep-deprived subjects [84]. Both in narcolepsy [81] and in obstructive sleep apnoea syndrome (OSAS) [78] the values are lower than in controls and the latency correlates inversely with the respiratory arousal index.

MSLT versus MWT MSLT and MWT data do not always correspond: in one study a 3 h nap had a clear effect on the MWT but not on the MSLT [78]. Secondly, the MWT is a better indicator of beneficial treatment effects in patients suffering from narcolepsy [3] and OSAS [78]. So, the MWT is able to discriminate between highly increased levels of sleepiness [85], while it has problems in discriminating lower levels of sleepiness, as a result of a ceiling effect clumping the alert subjects together. The MSLT, on the other hand, is better at showing differences among people who are more alert, while sleepy patients are clumped together as a result of a floor effect, as mentioned previously. However, in our opinion and as is generally argued, the differences between the MSLT and MWT involve more than this ceiling and floor effect and rather indicate that the tests assess different aspects of functioning [8, 86]. Although both the MSLT and the MWT measure simultaneously the physiological arousal and the sleep drive—the two main components of sleepiness—it has been shown that the ability to stay awake, as measured with the MWT, and the ability to fall asleep, as measured with the MSLT, are not intercorrelated substantially [79, 86]. This discrepancy was studied empirically by Sangal et al. [86]. A factor analysis of the two tests pointed out that 91% of all variance could be explained by two factors, these being alertness and sleepiness. It indicates that the tests measure substantially different abilities, probably with different brain mechanisms responsible for them (see above). The MWT appears to measure in particular the strength of the arousal system; in the MSLT the role of the sleep drive is more prominent [24]. This stresses that neither test is “more correct” than the other one but that, on the contrary, each is best depending on the experimental question being

asked. Finally, when considering the state trait sleepiness theoretical framework, we hypothesize that the MSLT and MWT both measure trait sleepiness and trait arousal, because of the stability of the test scores over time. In addition, the MWT measures the effects of state arousal, which the MSLT tries to minimize.

Other physiological parameters Polysomnography Apart from the use of polysomnography—consisting of an EEG, electro-oculogram and electromyogram—to measure sleep, this technique can also be valuable to identify different wake states. Indeed, the polysomnography parameters have been found to be reliable indicators for ambulatory recording of sleepiness in real-life situations [87]. Episodes of drowsiness or sleep during monotonous work tasks are reflected by increasing alpha and theta activity and slow eye movements during the minutes before misses in a task and dozing off [88]. With this methodology Torsvall et al. were able to detect sleep episodes in 20% of the subjects during night work [89]. In contrast to the EEG, a slow rolling eye movement index, shown to be sensitive to sleepiness, cannot be scored reliably in ambulatory conditions [42, 51]. The usefulness of polysomnographic recordings for the detection of sleepiness is somewhat restricted by large individual differences in the parameters. Also, the variety of algorithms used to trace sleepiness in the EEG impedes comparison of different research results. In one experiment the EEG recorded when falling asleep at night of a specific subject was used the next day using an expert system which searched continuously for similar EEG sequences during an in vivo 8 h driving trip [90].

Pupillometry With this technique the spontaneous variation of the pupil diameter and the pupil light reflex are measured. Hypersomnolence reduces these parameters, as can be evidenced in narcoleptics [44] and sleep apnoea [91] or with increased sleep disruption [45]. The technique is, though more convenient than polysomnographic recordings, rather complicated and expensive. This probably precludes the use of pupillometry in the routine evaluation of hypersomnia.

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Cerebral evoked potentials Research shows that the late components of cerebral evoked potentials, especially for the auditory system, are altered in the drowsy state in healthy subjects and that they have a lower amplitude in narcoleptics in comparison with normals [28]. Further studies demonstrated that longer auditory and visual P300 latencies are seen in narcolepsy patients as compared with healthy subjects [92]. Again, a high variability in the results limits the value of the technique as a sleepiness measure [46]. Practice Point Sleepiness assessment tools need to be carefully selected in accordance to the assessment goal. Each test has its own strengths, weaknesses and specific sensitivities to the different components of sleepiness, making it more or less suitable and valid within a specific testing context.

Research Agenda Future research effort should be aimed at linking various sleepiness assessment tools with the hypothesised underlying components of sleepiness. It should be determined to what extent a specific test is relatively more sensitive to acute changes in sleepiness or reflects a global, person-specific level of sleepiness. Secondly, the impact of the sleep drive on the one hand, the wake drive on the other hand, on the different sleepiness scores should be studied.

CONCLUSION The theoretical concept of sleepiness might benefit from some reconsideration on the basis of all data gathered during the last 20 years, even when different operationalizations of the concept were used in these studies. Certainly, valuable conceptual models of sleepiness have been developed in the past. They are useful and adequate to explain and predict aspects of this complex phenomenon, but many intriguing questions remain. Among these are explaining some apparent paradoxical findings in insomniacs, the influence of environmental factors on the tendency to fall asleep and the observed marked

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interindividual differences in sleep latency in healthy subjects As a result, more recent models stress the importance of arousal in the expression of sleepiness [2]. In this domain, further empirical studies are needed, as the wake drive has been less studied in detail compared with the sleep drive and is even missing in the two- and three-process models of alertness regulation. This conceptual matter has some clinical implications as well. For instance, to what extent a sleepiness problem is related to a low level of alertness on the one hand, a high level of sleepiness on the other hand, will have implications for the treatment of the complaint. Secondly, suggestions were made to adapt current models to include “trait” aspects of sleepiness. Earlier models focused on “state” sleepiness and ignored the “trait” component, although there are clear indications of the existence of such a personal characteristic, both for the sleep and for the wake drive. In conclusion, qualitatively different states of sleepiness exist. The search for a gold standard for the assessment of sleepiness seems meaningless at this time, as sleepiness cannot be considered as a unitary phenomenon. We repeat that the different assessment tools for sleepiness are always operationalizations reflecting the theoretical framework the investigator has on sleepiness. It might be more fruitful to attempt to find out which tests are better suited to assess specific aspects of sleepiness. Regarding the MSLT, the sleep drive was found to play a prominent role. The MWT on the contrary appeared to measure above all the strength of the arousal system. Next, acute changes in sleepiness seem to be better reflected on the SSS as compared with the ESS, while the latter turns out to be a good indicator of the general level of sleepiness. This could be interpreted as the SSS assessing “state” sleepiness, the ESS measuring “trait” sleepiness. Probably, the majority of the tests offer valuable information on sleepiness, but only when interpreted correctly and within a specific context. The optimum method for any given application depends on the nature and requirement of the test situation. Research effort is needed to link on a sound empirical basis the available assessment tools with the suggested components of sleepiness. In this way, an integrative theoretical model of sleepiness is

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promising to attain a more comprehensive insight into the vast amount of available scientific data in the domain of sleepiness.

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