Sleepiness at work: a review and framework of how the physiology of sleepiness impacts the workplace.

Journal of Applied Psychology 2014, Vol. 99, No. 6, 1096 –1112

© 2014 American Psychological Association 0021-9010/14/$12.00 http://dx.doi.org/10.1037/a0037885

INTEGRATIVE CONCEPTUAL REVIEW

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Sleepiness at Work: A Review and Framework of How the Physiology of Sleepiness Impacts the Workplace Heather M. Mullins and Jose M. Cortina

Christopher L. Drake

George Mason University

Sleep Disorders and Research Center, Henry Ford Hospital, Detroit, Michigan

Reeshad S. Dalal George Mason University Sleepiness, the biological drive to sleep, is an important construct for the organizational sciences. This physiological phenomenon has received very little attention in the organizational science literature in spite of the fact that it influences a wide variety of workplace behaviors. In this article, we develop a framework through which sleepiness can be fruitfully studied. We describe (a) what sleepiness is and how it can be differentiated conceptually from related concepts such as fatigue, (b) the physiological basis of sleepiness, (c) cognitive and affective mechanisms that transmit the effects of sleepiness, and (d) the behavioral manifestations of sleepiness in the workplace. We also describe (e) job demand characteristics that are antecedents of sleepiness and (f) individual differences that moderate the aforementioned relationships. Keywords: sleepiness, job performance, job demands, affect, physiology

Schaubroeck and Ganster (1993) used a physiological framework to explain connections between work demands on experienced stress. Several other articles in the organizational sciences also have drawn from physiology to explain workplace phenomena (see Canli, 2004; Dimotakis, Conlon, & Ilies, 2012; Watson, Wiese, Vaidya, & Tellegen, 1999). With the present article, we hope to follow in this tradition by using this integrated approach. Specifically, we utilize a physiological framework to explain how changes that occur within the brain—in conjunction with sleep– wake processes—in turn influence workplace outcomes. That is, we demonstrate how these physiological changes inherently tied to sleep and wakefulness are ultimately responsible for changes in performance and other important workplace outcomes. Sleep research has shown that sleep problems are quite common. According to the 2008 Sleep in America Poll, at least 65% of people experience sleep problems a few nights a week (Swanson et al., 2011). Moreover, this research has shown that sleep problems including voluntary sleep restriction are linked to the nature of one’s employment, and full-time workers seem to be at greatest risk. The amount of sleep that full-time workers get has been decreasing over the past 30 years as the number of hours worked has increased (Knutson, Van Cauter, Rathouz, DeLeire, & Lauderdale, 2010). Furthermore, full-time workers are more likely than part-time workers to be at risk for sleep disorders and are more likely to report having driven while drowsy in the recent past (Swanson et al., 2011). Individuals who curtail the number of hours that they sleep are using the extra time for personal activities (Basner & Dinges, 2009; Basner et al., 2007; Biddle & Hamermesh, 1990), including

Workplace psychology has expanded its focus to include research aimed at understanding the impact of nonwork variables on workplace outcomes. One area of particular interest is the role of sleep in workplace outcomes. Most people spend the majority of their time as adults either working (⬃7 hr/weekday, ⬃2 hr/weekend day; Basner et al., 2007) or sleeping (6.68 hr/night; Barnes, Wagner, & Ghumman, 2012). Despite the significant amount of time people spend engaging in these two activities, organizational psychologists know very little about the relationship between them. Sleep is inherently a physiological phenomenon. Thus, when one is studying the relationship between sleep and work variables, physiology provides useful models with which to examine connections among such variables. The approach taken in the present article is similar to that adopted by previous influential articles that have used a physiological framework in order to explain relationships among workplace variables. For example, Heaphy and Dutton (2008) used a physiological framework to explain the role of social interactions on physical health and work engagement.

Heather M. Mullins and Jose M. Cortina, Department of Psychology, George Mason University; Christopher L. Drake, Sleep Disorders and Research Center, Henry Ford Hospital, Detroit, Michigan; Reeshad S. Dalal, Department of Psychology, George Mason University. The authors would like to thank Tom Roth for his many insightful comments throughout the development of this article. Correspondence concerning this article should be addressed to Heather M. Mullins, Department of Psychology, George Mason University, 4400 University Drive, 3F5, Fairfax, VA 22030. E-mail: [email protected] 1096


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television watching (Basner & Dinges, 2009; Hamermesh, Myers, & Pocock, 2008) and family obligations (Barnes et al., 2012). When full-time workers perceive that there is not enough time for personal and family obligations, they tend to choose to reduce the amount of time spent sleeping. One of the most common and disabling immediate consequences of sleep problems is sleepiness (e.g., Pack et al., 2006; Swanson et al., 2011). In the most basic sense, sleepiness can be defined as “a craving or desire for sleep” (Dement & Carskadon, 1982, p. S57). Although related to the common notion of fatigue, sleepiness is a more precise term that reflects a universal physiological homeostatic need state, comparable to hunger or thirst, that is associated with increased sleep pressure and that leads to decrements in function (Drake, 2011; Roehrs, Carskadon, Dement, & Roth, 2011). Sleepiness in the general population results from reductions in quantity or quality of sleep, circadian rhythms, drugs that act upon the central nervous system (CNS), or the presence of a CNS disorder (Roehrs et al., 2011) and is associated with memory lapses, decreases in performance, and increases in the rate of accidents (Carskadon et al., 1986; Drake et al., 2010). The amount of sleepiness one experiences can range from full alertness on one extreme to a debilitating state known as excessive daytime sleepiness (EDS) on the other. Roughly half of patients seen by physicians in sleep centers and at least 11% of the general population experience EDS (Carskadon et al., 1986; Drake, 2011). Although many sleep researchers and clinicians focus their efforts on studying the EDS extreme of the sleepiness spectrum, the sleep research community recognizes that subclinical sleepiness, which affects an additional 33% of the general population, deserves empirical attention as well (Drake et al., 2010). The importance of sleepiness in the general population and workforce was perhaps best expressed by Dinges (1995): “As a daily biological curtain on waking function, sleepiness is the most ubiquitous regulator of performance capability experienced by our species” (p. 12). Because individuals are often unaware of the impairments in neurobehavioral functioning that result from sleepiness, it is wrongly assumed that sleep restriction is benign (Banks & Dinges, 2007; Van Dongen, Maislin, Mullington, & Dinges, 2003). Survey research has shown that sleepiness has a significant impact on organizations. For example, when asked with regard to the past month, 29% of respondents reported having fallen asleep or become significantly drowsy at work, 12% were late to work as a result of sleepiness, 4% left work early, and 2% did not go to work as a result of sleepiness and sleep problems (Swanson et al., 2011; see also Léger, Massuel, Metlaine, and the SISYPHE Study Group, 2006). Furthermore, reduced sleep duration contributes to many health-related outcomes such as obesity and metabolic disturbance (Spiegel, Leproult, & Van Cauter, 1999; Wolk & Somers, 2007) as well as hypertension, heart disease, and cardiovascular mortality (Newman et al., 2000). The combined effects of lateness, absenteeism, health problems, and the aforementioned increase in accident rates and decreased performance provide compelling evidence that sleep loss and resulting sleepiness have a substantial financial impact on organizations (Culpepper, 2010). The economic burden of sleepiness in the United States is estimated annually at $14 billion in medical expenses (Walsh & Ustun, 1999), between $53 billion and $69 billion in vehicle accidents, and between $18 billion and $24 billion in work-related accidents (Léger, 1994). Thus, organizations have a vested interest in pre-

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serving human capital, as well as monetary capital, by minimizing sleepiness experienced by employees. Many have concluded that work itself is leading to the increase in sleepiness. The sleep literature has made some links to sleepiness from work variables, most notably in the areas of shift work (Drake, Roehrs, Richardson, Walsh, & Roth, 2004; Paech, Jay, Lamond, Roach, & Ferguson, 2010), nontraditional work schedules (Luckhaupt, Tak, & Calvert, 2010), and long working hours (Basner & Dinges, 2009; Virtanen et al., 2009). Furthermore, reduced sleep quality (e.g., disturbed sleep) has been linked to job demands and stress (Nordin, Knutsson, Sundborn, & Stegmayr, 2005) and workplace bullying (Niedhammer, David, Degioanni, Drummond, & Philip, 2009). Workplace psychology research has only recently begun to examine the effects of sleep. For example, Scott and Judge (2006) found that fluctuations in self-reported sleep quality within an employee over time are linked to fluctuations in mood and job satisfaction. One of the most common causes of sleepiness is sleep loss. Recent work by Christopher Barnes has shown that sleep loss is related to an increase in workplace injuries (Barnes & Wagner, 2009), an increase in unethical conduct (Barnes, Schaubroeck, Huth, & Ghumman, 2011), and a decrease in self-regulation (Wagner, Barnes, Lim, & Ferris, 2012). Barnes (2012) presented a model of the work-related consequences of two distinct sleep constructs, sleep loss and poor sleep quality, that are driven by self-regulation. Specifically, Barnes proposed that work withdrawal, goal level, incivility, and defection in workplace social dilemmas are all impacted by sleep loss or reduced sleep quality through self-regulation (Barnes, 2012). In the present article, we build on the work of Barnes (2012) in three ways. First, the focus of this article is on sleepiness—which is the more immediate cause, compared with sleep loss or sleep quality— of sleep-related workplace outcomes and covers a physiological state that can have little to do with sleep per se (e.g., circadian rhythm, sedating medication, CNS disorder). Second, we go beyond self-regulation to consider the effects of sleepiness through a comprehensive physiological framework. Third, whereas Barnes (2012) focused solely on the consequences of sleepiness, in this article we examine not just the work-related manifestations but also the workrelated antecedents of sleepiness. To reduce overlap with Barnes (2012), only those constructs for which there is evidence emanating from theoretical frameworks beyond self-regulation are discussed here. Although the findings from sleep research may be unfamiliar to most of us in the organizational sciences, they are well established in sleep literature. For this reason, we offer these initial conclusions as lemmas (i.e., well supported statements used as intermediary components for future propositions). The bulk of the article is devoted to explanations of the links between sleepiness and workplace variables, accompanied by propositions typical of a review article. Although there is empirical evidence supporting the conclusion that sleepiness impacts the workforce, organizational researchers have not yet delineated a comprehensive framework through which sleepiness and workplace variables can be fruitfully researched. The purpose of this article was twofold: to describe such a framework based in the physiological changes that occur in association with sleepiness and to provide a clear research agenda. This article is organized utilizing a problem–solution format. Spe-

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cifically, (a) sleepiness can be a problem for individuals and organizations, and (b) by understanding the organizational antecedents of sleepiness, researchers can devise interventions to provide solutions that will reduce sleepiness. The problem is described first in the manifestations portion, and the way forward to a solution is presented second in the antecedents portion. We present two key take-away messages that are directly tied to understanding the manifestations and antecedents of sleepiness. The first key take-away message is that sleepiness has the potential to significantly influence workplace outcomes, largely through physiological changes that manifest through information processing and affective mediating mechanisms. To illustrate this first take-away message, we provide a series of lemmas and propositions that explain how sleepiness impacts workplace outcomes. We start by (a) presenting the construct of sleepiness and differentiating it conceptually from related concepts such as fatigue; this is followed by (b) a description of the physiological changes that occur in the brain of a sleepy individual. Next, we build on this description by illustrating (c) how these physiological changes affect two processes that are key in the organizational sciences and are important transmitters of the effects of sleepiness: information processing and affect. Then, we offer propositions that are supported by findings and rationale consistent with the sleep literature (but are still not well understood). Specifically, these propositions provide a clear agenda for future research exploring the effects of sleepiness on workplace outcomes by describing (d) the subsequent behavioral manifestations of acute sleepiness transmitted through information processing and affect (reduced job, task, adaptive, and contextual performance; increased accidents; and withdrawal and deviant behaviors; see Figure 1). The second key take-away message is that there are organizational antecedents that can influence individual employees’ sleepiness, and by understanding the relationships between these antecedents and sleepiness, organizational scientists can develop policies and interventions aimed at reducing the sleepiness of employees. The series of propositions that follow aim to guide future research in this direction. Specifically, we focus on (e) job demands such as work schedules, time pressure, work load, and perceived control for two reasons. First, each of these demands is likely to be related to subsequent sleepiness and the relationship between these demands and sleepiness is not well understood and

Figure 1.

has not yet been tested. Second, organizational policies and interventions can potentially be developed to reduce these demands and subsequently reduce sleepiness. Finally, we describe (f) the individual differences that likely moderate the aforementioned relationships.

Sleepiness Sleepiness Defined Sleepiness can result from (a) low sleep quality, (b) low levels of sleep quantity, (c) circadian rhythms, (d) CNS-acting drugs, or (e) the presence of a CNS disorder (Dinges, 1995; Roehrs et al., 2011). Although sleepiness can be measured as a subjective feeling (i.e., self-report), objective measures of sleepiness that are rooted in physiology, specifically electrophysiology, are considered the gold standard (e.g., the Multiple Sleep Latency Test, or MSLT; see Carskadon et al., 1986). The definition of sleepiness presented here and the propositions that follow are based on objective measures of sleepiness. Sleep researchers usually define quantity of sleep as the amount of total sleep per 24-hour day (Roehrs et al., 2011). Reductions in the quantity of sleep include not only partial and total short term sleep deprivation but also the accumulation of sleep loss from longer term restriction of the number of hours slept (Van Dongen, Masilin, et al., 2003). Sleep debt, the “increased pressure for sleep that results from an inadequate amount of physiologically normal sleep” (Van Dongen, Rogers, & Dinges, 2003, p. 6), can result from restriction of sleep over a period of days; the accumulation of sleep debt results in sleepiness (Durmer & Dinges, 2005). Reductions in sleep can occur through reduced sleep opportunity (i.e., sleep deprivation and sleep restriction) as well as reduced sleep quality. One way in which sleep quality may be reduced is through sleep fragmentation, which represents brief arousals that occur during sleep. Fragmentation can occur both in the presence of a sleep disorder (e.g., sleep apnea) and in nonclinical populations such as older adults (Roehrs et al., 2011). Furthermore, sleep quality may be reflected by the amount of slow wave sleep, such that a reduced quantity of slow wave sleep may indicate reduced sleep quality (e.g., see Bonnet, 1987). Subjective sleep quality refers to “tiredness on waking and throughout the day, feeling

Framework of relations among sleepiness, its manifestations, and its antecedents.


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rested and restored on waking, and the number of awakenings in the night” (p. 392; Harvey, Stinson, Whitaker, Moskovitz, & Virk, 2008). Thus, sleep quality objectively can refer to fragmented sleep or reduced slow wave sleep or subjectively can refer to the experience of nonrestorative sleep and awakenings during the night. Depending on severity and chronicity, both objectively and subjectively defined reduced sleep quality can result in increased sleepiness. Circadian rhythms are the naturally occurring rhythms that mediate the timing of daily cycles of alertness, sleep, and many other physiological systems that humans experience; these endogenous rhythms can be slightly longer or shorter than 24 hr but are typically entrained to 24 hr through exposure to the daily light– dark cycle (Czeisler et al., 1999). The circadian cycle is marked by changes in nearly all physiological variables including the hormone melatonin, plasma cortisol, urinary potassium, and body temperature (Mohawk, Green, & Takahashi, 2012; Moore, 1997). For normal day-sleeping individuals, the most alert portion of the circadian cycle occurs during the evening, and the least alert portion, which coincides with severe sleepiness, occurs during the night approximately between 4 a.m. and 6 a.m. (Dijk & Czeisler, 1994). Åkerstedt (1995) and Åkerstedt and Folkard (1997) described a three-process model of alertness that provides a relevant complementary framework through which to understand the circadian component of sleepiness. In this model, alertness is a function of sleepiness due to circadian rhythms, time since awakening, and sleep inertia, which is the brief period of time (less than 30 min) between awakening from sleep and becoming fully alert (Jewett et al., 1999). Alertness increases from the time since awakening until the evening hours due to an active circadian alerting signal that opposes the build-up of sleepiness with increasing time awake. The dissipation of this circadian alerting signal coincides with the onset of the nocturnal hormone melatonin and facilitates sleep onset and sleep consolidation throughout the night. In the absence of nocturnal sleep (i.e., sleep deprivation), the circadian nadir in alertness (maximal sleepiness) is revealed to be in the early morning hours. With increasing time awake in the 24-hour cycle, the circadian alerting signal rises, again counteracting (partially) the build-up of homeostatic sleep drive, thereby attenuating sleepiness despite continued wake without sleep (Åkerstedt & Folkard, 1997). Finally, substances and CNS disorders both influence sleepiness. For example, substances that depress the CNS can increase sleepiness (e.g., alcohol or sleeping medication), and CNS disorders such as narcolepsy and Parkinson’s disease are characterized by increased sleepiness (Roehrs et al., 2011). In summary, the combined effects of sleep quantity and sleep quality, circadian rhythms, and chemical and biological factors that influence the CNS produce fluctuations in sleepiness. One of the only natural ways to reverse sleepiness is the restorative process of sleep itself (Sonnentag, Binnewies, & Mojza, 2008), and the restoration experienced from regular good sleep has positive long-term effects (Rupp, Wesensten, & Balkin, 2010). Some additional factors can influence the expression of underlying sleepiness. For example, changes in physical activity, food intake, and posture can have effects on sleepiness (enhance or decrease). However, it is important to note that these effects are generally short lived and, in the case of increasing alertness, are thought to “mask” sleepiness rather than produce a fundamental

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change in underlying state (Bonnet, 2011). In addition, there is some evidence to suggest that exposure to bright light can enhance alertness during the early morning hours (Badia, Myers, Boecker, Culpepper, & Harsh, 1991; Campbell & Dawson, 1990), a finding likely attributable to the suppression of melatonin by bright light (Wright, Myers, Plenzler, Drake, & Badia, 2000). Thus, if environmental conditions require physical activity, contain bright lights, are loud, and require the individual to stand, then the effects of sleepiness may be temporarily impacted in important ways. Of the primary causes of sleepiness, sleep quantity, sleep quality, and circadian rhythms are the most likely sources of sleepiness in the working population. Throughout this article, we draw on research that includes both the primary causes of sleepiness as well as sleepiness itself. A clear distinction has been made throughout as to the source of the sleep construct. Future researchers in the organizational sciences should take an approach to the conceptualization of sleep variables such that they are consistent with the definitions found in the sleep literature.

Sleepiness and Fatigue The sleep literature draws a clear distinction between sleepiness and fatigue. Fatigue can be defined as “an overwhelming sense of tiredness, lack of energy and a feeling of exhaustion, associated with impaired physical and/or cognitive functioning” (Shen, Barbera, & Shapiro, 2006, p. 70). The primary difference between fatigue and sleepiness involves the respective antecedents of each. Sleepiness is an increase in the propensity for sleep (increased pressure for sleep) and can be brought on by reduction or fragmentation of sleep, the nadir of the circadian rhythm in alertness, or factors that affect the CNS (i.e., specific substances or disorders). By contrast, fatigue is caused by time on task and cognitive load and is influenced by emotional state and immune state. Thus, an individual may experience fatigue as a result of spending a considerable amount of time on a cognitively demanding task, but this experience of fatigue is a completely separate construct from that of sleepiness. Fatigue is more closely associated with a reduction in the efficiency of allocating mental resources while sleepiness is more closely associated with a reduction in the amount of resources that are available for allocation (Desmond & Matthews, 1997). Furthermore, fatigue can be physical, which can be experienced as muscular fatigue in manual laborers. Although both fatigue and sleepiness result in declines in task performance, the mechanisms through which their effects can be reversed differ: fatigue can be reversed by rest (e.g., time off task), while sleepiness can only be naturally (e.g., without the use of stimulants) reversed by sleep (Balkin & Wesensten, 2011). Thus, fatigue and sleepiness differ conceptually, differ in antecedents, and differ in the way that they are reduced and, in some cases (i.e., driving), interact with one another (Balkin & Wesensten, 2011).

Manifestations of Sleepiness Sleepiness is characterized by physiological changes that have a direct effect on information processing and on affect. The behavioral manifestations of sleepiness can occur through these information processing and affective pathways. Recall the first takeaway message: sleepiness has the potential to significantly influence workplace outcomes, largely through physiological


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changes that manifest through information processing and affective mediating mechanisms. In this section, we discuss the immediate physiological bases and effects of sleepiness and how such changes impact information processing and affect. Because the physiological bases and effects of sleepiness on information processing and affect have considerable empirical support, the conclusions from this research are presented as lemmas. Next we build upon the lemmas and present a discussion of the work-related behavioral manifestations of sleepiness (job performance, task performance, adaptive performance, contextual performance, accidents, and withdrawal and deviant work behaviors). Although some sleep research supports the relationships between sleepiness and workplace outcomes, this support is insufficient, primarily due to differences in operationalization of work-related constructs. Here, we aim to extend the literature and thus provide propositions denoting future research directions that incorporate operationalizations more consistent with those in the organizational sciences. Collectively, we draw from the sleep literature to inform future research directions that will fruitfully develop the understanding of the manifestations of sleepiness on workplace outcomes.

Physiological Bases of Sleepiness The physiological basis of sleepiness has been well documented in medical research on sleep. Through a brief review of the physiological consequences of sleep deprivation, sleep restriction, and resulting sleepiness, we demonstrate how physiological changes function as the mechanisms through which sleepiness results in work-related manifestations. Lab studies have shown that sleepiness has several physiological consequences that affect cognitive functioning. Thomas et al. (2000) and Mu et al. (2005) demonstrated that 24 hours of sleep loss results in 7% deactivation of the whole brain as evidenced by hypometabolism of glucose. The areas of greatest reduction in brain activity are in the prefrontal cortices, superior temporal– inferior parietal cortices, and the thalamus. The prefrontal cortices control higher order cognitive abilities, such as planning, foresight, and problem solving (Mesulam, 1985). The superior temporal– inferior parietal cortices are responsible for other higher order cognitive abilities such as semantic processing of auditory and visual information (Mesulam, 2000). The thalamus controls general arousal level (Mesulam, 2000). Thus, sleepiness results in hypometabolism in areas of the brain responsible for higher order cognitive abilities and in areas of the brain associated with arousal. As a result, the immediate physiological consequences of sleep loss are deficits in cognitive functioning and sleepiness. This decreased metabolic activity that occurs in frontal brain areas with inhibitory projections to the limbic system likely contributes to increased emotional activation of the amygdala following sleep deprivation (Gujar, Yoo, Hu, & Walker, 2011). Given the centrality of the amygdala in affective processing, this finding is key to understanding the impact of sleepiness on emotion. The biochemical changes that accompany regional brain changes associated with sleepiness (e.g., build-up of adenosine in the basal forebrain, changes in orexin/hypocretin including ascending and descending projections to brain stem arousal nuclei, and other neurotransmitters) are ongoing topics of research, as is a search for clear biochemical markers of sleepiness. A detailed discussion of neuroanatomical and biomechanical mechanisms of sleepiness is be-

yond the scope of this article (for in-depth reviews of this topic, please see Roehrs et al., 2011; and Saper, Cano, & Scammell, 2005). The immediate physiological changes that occur as a result of sleepiness impact several cognitive and affective processes. Two of these processes, information processing and affect, have been selected for inclusion in this article for four reasons: (a) they are directly tied to the physiology of sleepiness, (b) they are important antecedents of workplace outcomes, (c) they are potential mediating mechanisms between sleepiness and workplace outcomes, and (d) they minimize overlap with previous reviews (e.g., Barnes, 2012). These physiologically based mediating mechanisms are presented in the next section.

Physiologically Based Mediating Mechanisms The work-related physiologically based cognitive and affective transmitters of the effects of sleepiness include information processing and affect. In this section, we provide a brief review of the effect of sleepiness on each of these. Although the majority of the research presented in this section was conducted outside the workplace by biomedical and health researchers, we extrapolated the results of this research to the workplace. Recall that sleepiness and sleep loss are different. Here we recognize that in normal working individuals (i.e., individuals without sleep disorders), we are assuming that sleepiness is induced most commonly by sleep loss, sleep restriction, or poor sleep quality (and not other causes such as CNS-acting substances or CNS disorders). We also recognize that the negative physiological effects are in some cases contributed to by more than one cause of sleepiness; thus, making more specific statements would require further study. For example, some of the acute performance deficits of sleep loss may be eliminated by improving sleep, which provides evidence that these deficits are caused by sleepiness induced by sleep loss. Finally, we also recognize that often the manipulation in sleep studies involves sleep deprivation. Although there are some findings that are unique to the process of total sleep deprivation (e.g., those that concern memory consolidation), many of the findings can be extrapolated to the resulting sleepiness. In these cases, sleep deprivation studies are relevant in a discussion of sleepiness, and the presence of sleepiness is assumed by the design of the study, although not explicitly measured. Information processing. Decreases in activation of the brain regions responsible for higher order cognitive abilities result in substantial deficits in information processing, particularly in the areas of processing speed, attention, and learning and memory. While some of the research in this area focuses on sleepiness itself, other research focuses on one of its immediate antecedents: sleep deprivation, a short-term severe reduction in sleep quantity. Sleep deprivation results in deficits in information processing speed, which is evidenced by slower response times, increases in errors, and decreases in the ability to correct errors (Hsieh, Tsai, & Tsai, 2009). Sleep deprivation has a general negative effect on attention (Wimmer, Hoffmann, Bonato, & Moffitt, 1992) and on selective attention, with greater deficits experienced in early stages of cognitive processing (e.g., visual processing) than in the later stages of cognitive processing (e.g., response selection; Trujillo, Kornguth, & Schnyer, 2009). This can be manifested in different ways. For example, sleepiness decreases attentional capacity through hyper-


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reaction to novel stimuli (Gumenyuk et al., 2010) or through lapses in attention (Drake et al., 2001). Sleep deprivation has been found to decrease memory function through a reduction in hippocampal activity. Even a single night of sleep loss impairs working, procedural, and implicit memory (Forest & Godbout, 2000; Walker & Stickgold, 2006) and, subsequently, any hippocampal-dependent learning and memory (Alhaider, Aleisa, Tran, Alzoubi, & Alkadhi, 2010; Patti, Zanin, Sanday, & Kameda, 2010) including spatial working memory (Hagewoud, Havekes, Novati, et al., 2010) and sensory memory (Gumenyuk et al., 2010). Decreased attentional capabilities resulting from sleepiness and impaired processing speed and memory resulting from sleep deprivation have important implications for cognitive tasks and behaviors that rely on information processing. It is also important to note that many of the information processing, affect, and memory effects may be specifically mediated by reductions in certain sleep stages, such as rapid eye movement or slow wave sleep, and thus would not necessarily require a full night of sleep deprivation to manifest. While this is beyond the scope of the present article, the reader is referred to Walker (2010) for a comprehensive review. Taken together, the previously discussed arguments lead to the following: Lemma 1: Sleepiness leads to poorer information processing through its effects on attention, processing speed, and memory. Affect. Affect is a central construct in workplace psychology (e.g., Eid & Diener, 1999; Rafaeli & Sutton, 1987; Seo, Barrett, & Bartunek, 2004; Voronov & Vince, 2012). Research has shown that sleepiness impacts both the recognition and the experience of emotions. For example, sleep-deprived individuals have more difficulty recognizing low to moderate expression of happy and angry emotions than do non-sleep-deprived individuals (van der Helm, Gujar, & Walker, 2010). Sleep-deprived individuals are more easily distracted by negative emotional stimuli (Chuah et al., 2010) and are more likely to make choices associated with higher immediate emotional valence (Bayard et al., 2011). These effects have been attributed to sleep-deprivation-induced reduction in connectivity between the amygdala (the emotion center of the brain) and the prefrontal cortices, and the resulting reduction of inhibitory input to the amygdala (Chuah et al., 2010). Moreover, Watson et al. (1999) found that state positive affect (PA) has a circadian rhythm and relates to circadian phase such that one could predict the level of state PA from the time at which a person normally awakens In addition, several of the causes of sleepiness have been linked to changes in the experience of emotion. For example, poor sleep quality and sleep deprivation are related to a decrease in positive affect (e.g., cheerfulness or joviality; Bower, Bylsma, Morris, & Rottenberg, 2010; Scott & Judge, 2006) and an increase in negative affect (e.g., hostility; Scott & Judge, 2006; Selvi, Gulec, Agargun, & Besiroglu, 2007). This increased variability in emotions, combined with increased negative emotions and decreased positive emotions, has been proposed as the mediating mechanism between sleep quality and reductions in ratings of job satisfaction (Scott & Judge, 2006). Studies on the restorative nature of sleep show that good sleep is associated with positive affective outcomes. Additionally, good sleep quality is related to improved

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affect the following morning (Sonnentag et al., 2008), and individuals with good sleep habits (e.g., sleeping 6 hr or more a night on average) experience fewer depressive symptoms and experience a positive sense of purpose in life (Hamilton, Nelson, Stevens, & Kitzman, 2007). The previous arguments lead to the following: Lemma 2: Sleepiness results in increased negative affect, decreased positive affect, impaired emotion processing, and impaired emotion recognition through reductions in inhibitory input to the amygdala. These lemmas act as stepping stones for the propositions that follow.

Subsequent Behavioral Manifestations of Sleepiness Sleepiness also impacts outcomes that are more distal than those previously discussed. Overall job performance is one of the workrelated variables that is reduced by sleepiness. Sleepiness-related deficits in attention and learning impact academic grades (Beebe, Ris, Kramer, Long, & Amin, 2010), and sleepy individuals have significant impairments in work productivity (Dean et al., 2010; Swanson et al., 2011). The accumulation of sleep debt from sleep restriction results in cumulative impairment (Mollicone, Van Dongen, Rogers, Banks, & Dinges, 2010). The degree of impairment is greater for alertness, memory, and performance when the sleep debt is accumulated rapidly than when it is accumulated more slowly (Drake et al., 2001), perhaps because the brain adapts somewhat to slow accumulation of sleep debt, and this adaption stabilizes performance declines (e.g., Belenky et al., 2003; Drake et al., 2001; Hagewoud, Havekes, Tiba, et al., 2010). Although individuals can acclimate to the feeling of chronic sleepiness, performance does not improve with acclimatization (Durmer & Dinges, 2005). In the next section, we provide evidence that sleepiness is not benign by identifying linkages between sleepiness and more specific facets of job performance. Specifically, there is good reason to link sleepiness with decrements in each of the various dimensions of job performance (e.g., task, adaptive, and contextual), accidents, and withdrawal and deviant or counterproductive behaviors. Task performance. Task performance is part of every definition of job performance and refers to the specific role-prescribed behaviors that contribute to the technical core of an organization (Borman & Motowidlo, 1993). A considerable body of research links the deactivation in the brain associated with sleepiness to subsequent deficits in vigilance task performance (Akerstedt & Folkard, 1997; Akerstedt, Peters, Anund, & Kecklund, 2005; CoxFuenzalida, 2007; Dean et al., 2010; Durmer & Dinges, 2005; Maddox et al., 2009). The decreases in vigilance task performance are due to a combination of the low arousal caused by sleepiness and the aforementioned decrements in information processing (Cote et al., 2009; Glenville, Broughton, Wing, & Wilkinson, 1978). Numerous studies have focused on decreases in task performance and related phenomena such as performance monitoring, error recognition, and correction of errors that contribute to high performance. Sleep deprivation impairs aspects of task performance related to reaction times, response accuracy, errors of omission, and lapses (A. M. Tucker, Whitney, Belenky, Hinson, &


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Van Dongen, 2010). Both sleep restriction and sleep deprivation lead to a deficit in task-switching performance (Bratzke, Rolke, Steinborn, & Ulrich, 2009; Couyoumdjian et al., 2010) and multitasking performance (Haavisto et al., 2010). Performance that requires motor function is also reduced in partially sleep-deprived individuals (Durmer & Dinges, 2005). The effects of sleepiness on task performance are sometimes complex. For example, sleepiness impairs active inhibition of rule-based strategies (e.g., decision rule can be verbalized) but not information-integration strategies (e.g., decision rule cannot be verbalized and requires predecisional integration of information from multiple dimensions; Maddox et al., 2009). Sleepiness also increases the amount of attention required for response preparation but not the amount of attention required for maintenance of task performance (A. M. Tucker, Basner, Stern, & Rakitin, 2009). It is important to note, however, that this does not necessarily indicate that information integration and attention for maintaining task performance are unaffected by sleepiness as both are influenced by motivation. These findings imply that for jobs that require a great deal of monitoring, sleepiness is likely to have a stronger effect on performance than for jobs that require less monitoring. Furthermore, difficult, complex, or newly learned tasks are more affected by sleep deprivation than simple or well-learned tasks (Bonnet, 2011). Thus, we expect that workplace task performance, which is more complex than vigilance task performance, to be more greatly affected by sleepiness. Adaptive performance. The changing workforce now requires that employees have a degree of versatility and tolerance for ambiguity and novel work experiences (Cortina & Luchman, 2012; Murphy & Jackson, 1999; Pulakos, Arad, Donovan, & Plamondon, 2000). Adaptive performance as defined by White et al. (2005) refers to an effective change in performance in response to a dynamic environment. Sleepiness reduces several dimensions of adaptive performance through impairments in learning, attention, decision making, stress, and capacity for handling complex task environments. For example, adaptive performance requires the capability to learn work tasks, technologies, and procedures (Pulakos et al., 2000; 2002). Sleepiness resulting from a lack of sleep may be related to deficits in learning/memory consolidation (Curcio, Ferrara, & De Gennaro, 2006). Furthermore, sleep deprivation may impair the flexibility of previously learned information. Reversal training, training that aims to examine the ability to “unlearn” or replace old information with new information, is less effective under sleep deprivation conditions (Hagewoud, Havekes, Tiba, et al., 2010). Thus, sleep loss may lead to decrements in learning or memory consolidation and to decrements in the ability to unlearn information, an important form of learning that involves the active and adaptive “updating” of memories to reflect new relationships and realities. The implication is that this reduced flexibility may impair adaptive performance. Voluntary shifts in attention, attention selection, and attention-modulated information processing are impaired by sleep deprivation. These processes are required to monitor and respond to rapid changes in the environment (Trujillo et al., 2009), and their impairment could significantly reduce the capacity to handle emergencies or crisis situations and to deal with uncertain and unpredictable work situations (Pulakos et al., 2000, 2002). Adaptive performance is required in complex environments, which often involve the necessity for multitasking or task switch-

ing (Murphy & Jackson, 1999). As was mentioned earlier, the ability to multitask is substantially reduced for individuals experiencing sleepiness (Bratzke et al., 2009), and sleepy individuals have a lowered capacity to monitor complex technical systems, particularly because of reduced task engagement and increased risk taking (Sauer, Wastell, Robert, Hockey, & Earle, 2003). Finally, situations that demand adaptive performance, such as emergencies or crises, often require decision making under conditions that are changing and do not fit within traditional knowledge-based decision-making paradigms. A sleep-deprived decision maker is less innovative, has less flexibility in thinking, and displays poorer skills in risk assessment (Harrison & Horne, 2000), all of which lead to reduced adaptive performance. The impact of sleepiness on adaptive performance is likely to differ for distinct dimensions of adaptive performance. For example, interpersonal adaptability, which involves adjusting interpersonal style and requires recognizing and understanding emotions of others, may be more difficult for sleepy individuals than physically oriented adaptability, which involves adjusting to physical factors in the environment. Further research should be conducted to directly test the impact of objective sleepiness on each dimension of adaptive performance and utilize validated subjective measures of sleepiness where appropriate in field studies. Contextual performance. Contextual performance is defined as the contextual work behaviors that support the work environment rather than support the technical core (Cortina & Luchman, 2012; Motowidlo and Van Scotter, 1994). It includes behaviors such as demonstrating effort, personal discipline, organizational citizenship behaviors (OCBs), and other interpersonal behaviors such as facilitating team performance (Coleman & Borman, 2000). The components of contextual performance that are dependent on affect and interpersonal skills are most likely to be affected by sleepiness. Because sleep-deprived individuals are more likely to incorrectly recognize emotions such as anger or happiness and because social interactions rely on the accurate recognition of emotion (van der Helm et al., 2010), individuals who are sleepy due to sleep loss may be more likely to incorrectly interpret social situations. Furthermore, the propensity of sleepy individuals to have increased intraindividual variability in emotion (Scott & Judge, 2006) and to experience more negative affect and less positive affect leads to a reduction of positive relations with others (Hamilton et al., 2007) and inappropriate interpersonal behaviors (Pilcher & Huffcutt, 1996). Also, Anderson, and Dickinson (2010) found that sleep-deprived individuals were less likely to trust others and more likely to make decisions that were heavily influenced by emotion. This combination is likely to have implications for social exchange relationships. Barnes, Ghumman, and Scott (2013) found that sleep quantity (and likely concomitant sleepiness) predicted OCB directed toward individuals but inconsistently predicted OCB directed toward the organization. This complexity suggests that the relationship between sleep quantity and contextual performance is intricate. Changes in affect recognition are likely to increase relationship conflict in work teams (for a review of the effects of sleep deprivation on teams, see Barnes & Hollenbeck, 2009). Research indicates that at least the interpersonal components of contextual performance driven by affect processes are likely to decline with sleepiness. By contrast, Baranski et al. (2007) found that some sleepy individuals experience an increase in motivation when they know that others are counting on their


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contribution, which is notable because this was not expected of sleepy individuals. Furthermore, because there are knowledge and skill determinants of contextual performance (Dudley & Cortina, 2008), sleepiness is likely to lead to reduced contextual performance through its effects on knowledge acquisition and usage, behavioral flexibility, and emotion perception and management skills. For example, because acquiring and utilizing knowledge of organizational norms is important for helping, courtesy, and cooperating behaviors (Dudley & Cortina, 2008), a sleepy individual may be less helpful, courteous, and cooperative because of an inability to acquire and use information, perceive emotions, and so forth. The preceding arguments lead to the following:

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driving home after night work was related to an increase in accidents (Åkerstedt et al., 2005). The degree of impairment experienced by sleepy drivers is similar to that of someone operating an automobile under the influence of intoxicating levels of alcohol (Roehrs et al., 2004). Past research has provided a variety of technological and biobehavioral countermeasures to address sleepy driving and workplace conditions (e.g., please see Dinges, 1995). However, future studies should examine not only the degree to which the workforce is driving to and from work impaired by sleepiness but also potential workplace-specific ways to prevent this hazardous situation. The aforementioned arguments lead to the following:

Proposition 1: Sleepiness results in decreased job performance including task, adaptive, and contextual performance through its effects on information processing and affect.

Proposition 2: Sleepiness results in an increase in accidents through its effects on information processing and, at the extreme (i.e., microsleep), an absence of visual information processing.

Accidents. A workplace accident is a safety-related incident resulting in property damage, injury, or death (Smith & Carayon, 2011). Known predictors of workplace accidents include factors such as intelligence, perceptual-motor skills, machinery, technology, materials, task activities, the work environment, and organizational design and management (M. J. Smith & Carayon, 2011). Furthermore, work schedule factors including shift work and length of workday are related to an increase in accidents (C. Smith, Folkard, Tucker, & Evans, 2011) particularly because of the increased sleepiness associated with these work schedules (Drake et al., 2004). We return to the issue of work schedules in subsequent sections. In the current section, we focus on a considerable body of research that links sleepiness to an increase in the prevalence of accidents, predominately of automobile accidents. An individual does not need to fall asleep on the job in order for an accident to occur. Merely being sleepy is associated increases in risk-taking behavior (Roehrs, Greenwald, & Roth, 2004) and decreases in both detection of visual stimuli and reaction time, resulting in increases in the propensity for human error (Dinges, 1995). Objective measurement of sleepiness resulting from common causes in the general population, such as insufficient sleep, has been found to predict police-verified automotive accidents (Drake et al., 2010). Barnes and Wagner (2009) showed that the single hour of sleep lost when changing to daylight savings time was related to an increase in workplace accidents among miners. Additionally, self-reported disturbed sleep, which contributes to daytime sleepiness, has been found to predict both accidental death at work (Åkerstedt, Fredlund, Gillberg, & Jansson, 2002) and increased risk of work injury (Kling, McLeod, & Koehoorn, 2010; Salminen et al., 2010). Sleepiness measured by self-report (i.e., subjective sleepiness) is also related to an increase in automobile accidents (e.g., Ingre et al., 2006; Sagaspe et al., 2010). The increase in automobile accidents is relevant both for occupations involving commercial drivers and for all occupations in which employees commute by automobile to their job sites. There is evidence to support the idea that commercial drivers are particularly at risk for sleep-related accidents when they are experiencing a high degree of sleepiness (Vennelle, Engleman, & Douglas, 2010). Evidence from driving simulator studies suggests that subjective sleepiness and time of day predict automobile accidents (Åkerstedt et al., 2010) and that

Withdrawal and deviant behaviors. Withdrawal behaviors are behaviors in which individuals engage to avoid dissatisfying work situations (Hanisch & Hulin, 1990; Hanisch & Hulin, 1991). Deviant work behaviors are behaviors intended to harm the organization or organizational stakeholders (Spector et al., 2006). Of the withdrawal and deviant behaviors, absenteeism, lateness, turnover, and drug, alcohol, and tobacco use are most likely to be impacted by sleepiness. Absenteeism has the most clearly defined relationship with sleepiness. For example, individuals who report daytime sleepiness take more days off work for health reasons than do individuals who are not sleepy (Philip, Taillard, Niedhammer, Guilleminault, & Bioulac, 2001). Furthermore, disturbed sleep is related to both long-term (⬎90 days) and intermediate length (14 – 89 days) sickness leave (Åkerstedt, Kecklund, Alfredsson, & Selen, 2007). Employees who are sleepy are also more likely to arrive late to work (Swanson et al., 2011). Because turnover is partially determined by job attitudes and by other withdrawal actions (Hom, 2011) and because chronically sleepy individuals may have more negative attitudes regarding their jobs and schedules, greater emotional reactivity, increased absenteeism, and increased lateness, it is likely that chronically sleepy individuals are more inclined to leave their organizations. Future research should examine the role of sleepiness and turnover to determine the precise nature of the relationship. Sleepiness may also be related to an increase in deviant work behaviors, due to the increase in negative affect, decrease in decision-making ability, and reduction in self-regulation experienced by sleepy individuals. For example, Wagner et al. (2012) found that sleepiness leads to an increase in cyberloafing (using “work hours and company Internet access to check personal e-mails or visit websites not related to . . . work,” p. 1068), both in lab settings and in the workplace, following the change to daylight savings time. Additionally, there is evidence to support a bidirectional relationship between the number of hours one sleeps and one’s preference for heavy alcohol consumption (Roehrs & Roth, 2001). Although most sleep studies exclude those who use drugs from participation, longitudinal studies have reported that sleep problems (e.g., overtiredness and trouble sleeping) in childhood are related to an increase in alcohol, tobacco, and drug use later in life (Wong, Brower, Fitzgerald, & Zucker, 2004). Although the drug and alcohol use reported may not necessarily occur on the

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job, the effects of substance abuse (e.g., hangover) can impair performance on the job. Moreover, substance abuse is positively related to other counterproductive work behaviors such as theft; destruction of property; misuse of information, time, or resources; unsafe behaviors; poor attendance; and poor work quality (Gruys & Sackett, 2003). A sleepy individual who abuses drugs or alcohol may have more attendance problems, including lateness, than a substance abuser who is not sleepy. Clearly, further research on the role of sleepiness in withdrawal and deviant behaviors is warranted. Based on the previous arguments, we present the following proposition: Proposition 3: Sleepiness results in an increase in withdrawal and deviant behaviors through its effects on affect.

Antecedents of Sleepiness Now that we have discussed the behavioral manifestations of sleepiness, one can clearly see how sleepiness at work can negatively impact outcomes of interest to organizations. In this section, we discuss the job demands (e.g., work schedules, time pressure, workload, and perceived control) that can impact a worker’s experienced sleepiness. Through an understanding of the organizationally relevant antecedents of sleepiness, we as a field can begin to develop interventions that would reduce the sleepiness of individuals within an organization.

Job Demands The term job demands refers to physical, social, or organizational portions of a job that require sustained effort (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001; Karasek, 1979). Job demands can increase strain and the experience of stress, particularly when resources are low (Demerouti et al., 2001; Karasek, 1979). Certain job demands such as work load, time pressure, perceived control, and work schedules are also antecedents to sleepiness, most likely through the reduced sleep and circadian rhythm causes of sleepiness. Not only is this important given the behavioral manifestations of sleepiness, but it is also important because the restorative act of sleep itself can be viewed as a resource (e.g., Ota et al., 2009; Sonnentag et al., 2008). In this section, we discuss the role each of the aforementioned constructs plays in causing sleepiness. Time pressure, work load, and perceived control. Job demands that include a large amount of time pressure, a heavy workload, and low perceived control would be more likely to increase the amount of sleepiness an employee experiences through a reduction in the number of hours slept, overall sleep quality, or development of a sleep disorder. Gadinger et al. (2009) found that job demands and perceived control are related to subsequent impaired sleep quality. Åkerstedt, Knutsson, et al. (2002) found that high work demands and the inability to stop thinking about work while not at work predicted both disturbed sleep and feeling “not well rested” upon awakening. Furthermore, they found that high work demands predict difficulty awakening. De Lange et al. (2009) found that over time, cumulative exposure to high job demands and low perceived control was related to an increase in sleep-related complaints (e.g., trouble falling asleep,

waking up early in the morning) and that cumulative exposure to low job demands with high perceived control was related to the highest levels of sleep quality. When examining these relationships at the within-person level, they found that changing from a highdemand job to a low-demand job was associated with a substantial improvement in sleep quality. Collectively, this suggests that job design that emphasizes balance in job demands may have longterm effects on the sleepiness of employees, particularly through improvements in both the quantity and quality of sleep. The arguments presented lead to the following: Proposition 4: Job demands including high time pressure, high work load, and low perceived control will result in increased sleepiness through sleep restriction (reduced sleep quantity) and sleep disruption (reduced sleep quality). Work schedules. A great deal of research links work schedules, specifically working long hours and working on a night shift work schedule, to sleepiness. Although there are clear benefits to both employees and the organization in utilizing nontraditional or flexible schedules (e.g., Baltes, Briggs, Huff, Wright, & Neuman, 1999; Kossek & Michel, 2011), because of the way in which the timing of work is changed, these schedules often require individuals to work outside the traditional nine-to-five workday. For example, both flextime (i.e., which allows employees to alter their work hours, across fewer days for longer hours or over the weekend; Ronen, 1981) and compressed work weeks (i.e., which allows employees to work a full 40-hr work week in fewer than 5 days; Pierce, Newstrom, Dunham, & Barber, 1989) result in employees working extended hours each work day. Additionally, crisis situations often involve employees working additional hours on the weekend, in the evening, or at night, such as when a manager at a manufacturing plant must come to work in the middle of the night to handle an emergency or when a cardiologist is called in late at night to perform emergency surgery. When the length of the workday is increased or the number of hours in the workweek is increased, there tends to be a reduction in the amount of hours an individual sleeps per night (e.g., increase sleep debt; Virtanen et al., 2009). Working long hours is related to shorter sleep duration, reduced sleep quality, and severe sleepiness (Basner et al., 2007; Nakashima et al., 2011; Rosa, 1995; Son, Kong, Koh, Kim, & Härmä, 2008; Swanson et al., 2011; Virtanen et al., 2009). Shift work includes organizing the work hours into days, evenings, and nights (Kossek & Michel, 2011) and has been identified as a major cause of sleepiness (for a review, please see Drake & Wright, 2011). Shift work can either be composed of fixed shifts, in which an individual only works a single assigned shift of days, evenings, or nights, or rotating shifts, in which an individual rotates among day, evening, or night shifts. For example, in a rotating shift schedule, one might work days one week, evenings the next, and nights the following week. This is referred to as forward rotation of shifts. Alternately, in a backward rotating shift schedule, one works nights, then evenings, and then days. Backward rotating shifts have been shown to lead to the largest reductions in sleep, particularly between the end-of-day shifts and beginning of night shifts (Knauth, 1995; P. Tucker, Smith, Macdonald, & Folkard, 2000). Shift work often requires individuals to work during the hours when they would normally be sleeping, which results in misalignment or desynchronization between cir-


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cadian rhythms and wakeful working activities (Drake et al., 2010; Gumenyuk, Roth, & Drake, 2012; C. Smith et al., 1999). Approximately 10% of the night and rotating shift work population meets criteria for shift work sleep disorder (Drake et al., 2004). It is possible that there is self-selection out of shift work for older adults, given that there are proportionately fewer workers over the age of 55 who work on a shift work schedule (Molinié, 2003). Furthermore, shift work has been associated with feelings of not being rested, excessive sleepiness, and sleep deprivation (Åkerstedt, Knutsson, et al., 2002; Culpepper, 2010; Drake et al., 2004; Härmä, Sallinen, Ranta, Mutanen, & Muller, 2002; Sanquist, Raby, Forsythe, & Carvalhais, 1997). That is, shift work leads to sleepiness because of sleep restriction and circadian misalignment because shift workers are awake and working at their circadian nadir in alertness, either due to long shifts or to an inability to sleep/having fragmented sleep. There is evidence that many shift work schedules do not allow employees sufficient time to recover from the severe sleep restriction that occurs during work time (Paech et al., 2010). Additionally, there is an increase in falling asleep on the job when the length of the shift is increased (Pilcher, Lambert, & Huffcutt, 2000; Sallinen et al., 2003). Understanding how work schedules impact an individual’s sleepiness can allow organizations to construct schedules that optimize employee performance. The previous discussion leads to the following proposition. Proposition 5: Job demands such as a long or desynchronous work schedule will result in increased sleepiness through decreased sleep quality and circadian misalignment.

Moderators Although there is relatively little research on the variables that moderate sleepiness relationships, there are several factors that show promise. Moderators should explain under which boundary conditions the relationships between sleepiness and its antecedents or its work-related manifestations change in strength. These become particularly important when considering types of interventions to be implemented to reduce sleepiness or when understanding the degree to which certain tasks are impaired by sleepiness relative to others. Here we present some of the more promising moderators including demographic differences such as age, individual differences such as morningness versus eveningness, and the role of type of task (see Figure 2).

Age The average age of the workforce is increasing because individuals are delaying retirement and thus staying in the workforce

Age

longer (U.S. Bureau of Labor Statistics, 2008). Because there are well-researched changes in sleep that occur as individuals age, there is reason to believe that age is relevant when one is examining relationships between work-related variables and sleepiness. Specifically, age is expected to be an important moderator of the relationship between work schedules and sleepiness. Recall that desynchronous work schedules are likely to increase sleepiness. Work schedules, specifically those involving shift work, are likely to have a stronger effect on sleepiness in older workers. Older individuals experience a peak in alertness approximately 2 hr earlier than younger workers (Lieberman, Wurtman, & Teicher, 1989; Monk, 2005), and as individuals age, they drift toward a morning orientation (Monk, 2005). Individuals over age 50 have increased difficulty tolerating abrupt changes in their sleep–wake cycles (Härmä, 1995; Monk, 2005; Nachreiner, 1998). The effects of desynchronized circadian rhythms on sleepiness, which characteristically occur in shift work, are amplified in older adults (O’Donnell et al., 2009). In addition, there is some evidence that older workers may be less able to maintain their performance over the course of a night shift and cope with longer spans of successive night shifts (Folkard, 2008). Because older individuals have shifted peaks in alertness, are less able to tolerate changes in sleep–wake cycles, and experience the effects of desynchronized circadian rhythms to a greater degree than young individuals, we expected age to moderate the relationship between shift work schedule and sleepiness such that as age increases, the relationship between shift work schedule (i.e., synchronous vs. desynchronous) and sleepiness will be stronger. Proposition 6: Age moderates the relationship between work schedules that are desynchronized with circadian rhythms and sleepiness such that as worker age increases, the ability to tolerate desynchronous work schedules decreases. There is some evidence that age may have more complex relationships with sleepiness. In particular, age is likely to moderate the relationship between sleepiness and task performance, possibly though the information processing mechanism. Bliese, Wesensten, and Balkin (2006) found that under conditions of sleep restriction, adults experienced a performance decline on vigilance tasks. More important, the authors found that the slope of the performance decline was less steep for older adults than for young adults. The implication is that age provides some protection from the effects of sleep loss on performance. One reason for this may be that older adults have more experience with the effects of sleep restriction and have learned to channel available resources to limit the rate of performance decline. Because vigilance tasks require a certain degree of information processing, it is possible that this

Morningness/ Eveningness

Work Schedules

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Task Type

Sleepiness

Figure 2.

Moderators proposed in the model.

Performance

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experiential-learning-based conservation of resources provides older individuals with an edge in information processing, which translates into a reduction in performance decline. Although interesting, we did not feel that these relationships are sufficiently understood to warrant a formal proposition.


Morningness/Eveningness Morningness/eveningness was expected to moderate the relationship between work schedules and sleepiness such that the relationship is stronger when there is a mismatch between work schedule and circadian preference. Morningness and eveningness refer to differences in circadian preference (known as chronotype), and each type is associated with differences in when a person prefers to carry out various activities. For example, morningness is associated with going to sleep earlier at night and having an earlier circadian temperature peak, whereas eveningness is associated with being more alert later in the day and less alert early in the morning (Baehr, Revelle, & Eastman, 2000). Morningness is linked to greater daylight exposure in the early morning, and eveningness is linked to greater daylight exposure in the evening (Staples, Archer, Arber, & Skene, 2009). Morningness/eveningness preference affects one’s ability to tolerate certain work schedules, specifically those that are desynchronized with circadian preference (Härmä, 1995). Therefore, we would expect someone with an eveningness preference to have greater difficulty with a work schedule that requires morning responsibilities. Likewise, we would expect someone with a morningness preference to have greater difficulty with a work schedule that requires evening responsibilities. This misalignment in circadian preference and work schedule is likely to increase the amount of experienced sleepiness. Thus, we proposed the following: Proposition 7: Morningness/eveningness moderates the relationship between desynchronous work schedules and sleepiness such that the relationship is stronger when there is a mismatch between work schedule and circadian preference (morningness/eveningness).

Performance While the previous moderators target the work-related antecedent–sleepiness relationship, here we suggest that it is possible for some variables to moderate the sleepiness– behavioral manifestation relationship. Specifically, we expected that type of task would moderate the relationship between sleepiness and performance. Sleep deprivation studies suggest that some types of tasks are more impacted by complete sleep deprivation than other types of tasks. For example, tasks that are characterized by requiring a long period of time to perform and being high in monotony, externally paced and without feedback, newly learned, and reliant on memory performance are more likely to result in large performance decrements following sleep deprivation than tasks that do not have those characteristics, in part because of the increased opportunities for lapses in attention (Bonnet, 2011). High overall job performance requires successful performance on a variety of tasks that include the aforementioned task characteristics. When the type of task includes characteristics that are more affected by sleep deprivation, we would expect performance to be reduced

when an individual is sleep deprived. Because sleep deprivation results in sleep loss, one result of sleep deprivation is sleepiness. Here we are extrapolating the results of sleep deprivation to sleepiness such that it is possible that the some of the effects of sleep deprivation on performance are thus transmitted through sleepiness. For example, driving is a task that can be long and monotonous and is clearly impacted by sleepiness. Additionally, monitoring a security system also includes these types of characteristics. We would expect that a sleepy individual would perform more poorly on this type of task because of the increased opportunities for lapsed attention. Thus, we present the following: Proposition 8: Type of task moderates the relationship between sleepiness and performance such that performance on long, monotonous, externally paced (without feedback), and newly learned tasks will be more affected by sleepiness than performance on tasks without those characteristics.

Conclusion In this article, we have presented a framework for the workrelated antecedents and manifestations of sleepiness, as well as provided evidence for potential moderators of these relationships. Sleepiness results in a distinct pattern of physiological changes that contribute to reductions in information processing and changes in the experience of affect and emotion. Taken collectively, sleepiness reduces various types of performance, leads to increases in the rate of accidents, and is related to an increase in withdrawal and deviant behaviors. The work environment and the job itself can influence the amount of sleepiness that an individual experiences. Given the complex dynamic between an individual’s work and sleep, it is essential to include sleepiness within the framework of workplace psychology. Clearly, sleepiness, even below the threshold for clinical diagnosis, has major implications for organizations and their employees. The work-related manifestations and antecedents of sleepiness have implications for all areas of workplace psychology. For example, a better understanding of the role of sleepiness would allow for better design of jobs, better tailoring of flexible scheduling to employee needs, and better wellness program design. It would also help to reduce short-term performance decrements and increase overall job performance. It would allow for the development of a healthy workforce that can still meet the demands of a 24/7 global economy. Furthermore, it would allow organizational scientists to understand how to create workplace climates that promote not only traditional conceptualizations of safety but also healthy sleep as a component of workplace health and safety. The first key message presented in this article is that sleepiness has likely important implications for workplace outcomes such as performance and that these effects are likely transmitted through information processing and affect, both of which are altered on the physiological level in a sleepy individual. Although we do have some understanding of the nature of the effects of sleepiness on performance from the sleep literature, organizational scientists do not have a full understanding, largely due to differences in the conceptualization of workplace constructs. Future research in the organizational sciences should focus on exploring these relationships using the field’s conceptualizations of workplace variables in order to develop a


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valid understanding of how sleepiness affects different types of performance. For example, researchers could conduct a study to examine the effects of sleepiness on contextual performance. One possible study design for examining this relationship would be to utilize a day-level cross-sectional field study in which participants take a self-report measure of state sleepiness (for a review of measures of sleepiness, please see Johns, 2008) and self-reported measures of affect and information processing; then, supervisors or coworkers could rate the individual on a multidimensional measure of contextual performance for the day. Another possible design for assessing the relationship between sleepiness and contextual performance is to conduct a longitudinal or time series study in which the variables are measured daily. A third way to examine this relationship would be to design a lab study in which sleepiness can be measured objectively (i.e., using the MSLT; see Carskadon et al., 1986) followed by a carefully designed series of videotaped activities that would provide participants opportunities to engage in contextual performance behaviors and later be rated by trained coders. While the rigor of the study may depend on access to a sleep laboratory and equipment, even simple designs would allow organizational scientists to begin to understand these relationships. Regardless, there is a recognized need for the incorporation of physiology and physiologically based measurements into organizational research (e.g., Adis & Thompson, 2013; Volk & Köhler, 2012). Understanding sleepiness in the workplace provides a perfect opportunity for melding physiology into the organizational sciences. The second key message presented here is that research that contributes to understanding the work-related antecedents of sleepiness can help to inform future policy changes that promote healthy sleep for employees. In particular, future research aimed to address this goal should examine not only which antecedents have the most important effects on sleepiness but also the mechanisms through which sleepiness is affected. Once both the antecedents and mechanisms are identified, specific policy changes that are targeted to have the greatest impact, yet lowest cost for the organization, can be developed. One possible research direction that may lead to a solution for improving healthy sleep for employees includes assessing both organizational climate for sleep and opportunity for napping. For example, in organizations with a climate for responsiveness (i.e., expectation to check and respond to e-mail at all hours), employees may perceive pressure to fulfill work duties at the expense of sleep. Because there is considerable variation in the amount of sleep employees experience by management level and by industry (Luckhaupt et al., 2010), there appears to be preliminary evidence that workplace norms and climates differ with regard to their impact on employee sleep. Future research that more closely examines these differences at the organizational level can provide insight into possible effective policy implementation plans to influence healthy sleep. One possible intervention is that of providing the opportunity for napping. Although fewer than 5% of organizations currently have onsite nap rooms (Fegley, Esen, & Schramm, 2010), companies such as Google and Nike have embraced the practice with good reason. Meta-analytic evidence suggests that napping may be able to reduce the effects of sleep loss and may even reverse the effects of sleep deprivation under certain conditions (Driskell &

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Mullen, 2005), particularly when the nap is taken during a certain point of the circadian rhythm and is of limited duration (Milner & Cote, 2009). Conceptualizing napping as resource for individuals in an organization requires a drastic reframing away from the negative connotation of “sleeping on the job.” However, given the potential effectiveness of napping interventions, this reconceptualization is necessary. Such organizational context factors as climate and napping are one path for future research aimed at improving the healthy sleep of employees. Additionally, we presented demographic and individual difference moderators of the relationships proposed in the model. Chronotype (e.g., morningness/eveningness) is if offered as a moderator of the relationship between desynchronous schedules and sleepiness. For example, evening types may not perform at their peak in early morning job assignments, and job design may be used to structure the workday to minimize sleepiness and subsequently maximize performance around circadian preference. Task type may also influence the effects of sleepiness on performance. Understanding this influence can improve overall organizational effectiveness through delegation of important and highly impacted tasks to the least sleepy employees. Finally, we discussed how older age may both harm and help an individual. We proposed that older workers may be less likely to be able to tolerate desynchronous work schedules. However, it may also be that older workers have experience that allows them to decrease the rate of performance decline when sleepy. Together, these moderators represent only a small portion of those that may be relevant in the organizational sciences. Improving understanding of the boundary conditions of the proposed model will aid in both the research and practical implications of sleepiness in the workforce. Moreover, future research should focus on both intraindividual and interindividual effects of sleepiness. Sleepiness should be examined in both its acute and chronic forms, as the antecedents and consequences of each may differ greatly. An individual experiencing acute sleepiness, such as an emergency responder, may be impaired due to sleepiness that differs from the chronic sleepiness experienced by an individual who experiences sleep restriction resulting from working long hours over a long period of time, such as a corporate executive. On the one hand, although both the emergency responder and executive may experience similar problems with regard to judgment and decision making (because they are both human), since their jobs differ so greatly in content, tasks, and design, the organizational implications may be very different. On the other hand, the emergency responder who only experiences occasional acute sleepiness may be much less at risk for long-term health consequences than the chronically sleepy executive. Level of analysis is just as important in the measurement and analysis of sleepiness as it is in other organizational constructs. Finally, and at the very least, sleepiness ought to be included in future studies for which variables such as attention, affect, and motivation might be relevant. The amount and strength of the known relationships between sleepiness and work-related constructs provide compelling evidence that studies that ignore sleepiness, or even time of day or time on task, may have results that are confounded by a mis-specified model. Until future organizational research includes the construct of sleepiness in


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its measurement, design, and analysis, we do not have a full understanding of the true impact of sleepiness on work.


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Received July 18, 2013 Revision received July 23, 2014 Accepted July 28, 2014 䡲

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