Effects of slow-release caffeine and a nap on driving simulator performance after partial sleep deprivation

Comparative Bioavailability and Benefits on Mental Functions of Novel Extended-Release Caffeine Capsules against Immediate-Release Caffeine Capsules: An Open-Label, Randomized, Cross-over, Single-Dose Two-Way Crossover Study

Present study aimed compared pharmacokinetic profile of sustained-release CaffXtend® capsules (SR-Caffeine) with immediate-release caffeine capsules (IR-Caffeine), and the effect of SR-caffeine on memory, motivation, concentration, and attention. This open-label, randomized, single-dose, two-treatment, two-sequence, two-period, two-way crossover oral bioavailability study block randomized (1:1) healthy subjects (N = 15) to receive SR-Caffeine (200 mg) and IR-Caffeine (200 mg). Blood samples were collected at 0.25, 0.50, 0.75, 1, 1.5, 2, 3, 4, 5, 6, 8, 10, 12, 24, 36 and 48 h in each period. Primary study outcome included comparing relative bioavailability of SR-Caffeine 200 mg and IR-Caffeine 200 mg under fasting conditions, and changes in caffeine research visual analogue scale (Caff-VAS) scores ('relaxed', 'alert', 'jittery', 'tired', 'tense', 'headache', 'overall mood' and 'mentally fatigued') were also evaluated. Fifteen subjects completed the study. Mean tmax was 4.08 ± 2.13h for SR-Caffeine compared to 0.83 ± 0.39h for IR-Caffeine, (p < 0.0001). Similarly, mean t½ was 7.07 ± 3.48h for SR-Caffeine compared to 5.78 ± 2.11h for IR-Caffeine (p = 0.04189). However, total exposure was similar for SR-Caffeine and IR-Caffeine (90% CI: 89.89-120.50% to 94.49-123.82% for geometric least square mean of ln-transformed AUC0-t and AUC0-∞). In the Caff-VAS evaluation, the SR-Caffeine group showed significantly better scores for 'jitteriness', 'tiredness', 'alertness' and 'overall mood' for 8-12 h than the IR-Caffeine group. No adverse events were reported. Results demonstrated sustained release of caffeine over 24 h from SR-Caffeine as compared to IR-Caffeine, which showed significant improvements in the scores for 'relaxed', 'alertness' and 'overall mood' and significantly lower scores for the parameters-'jittery' and 'tired' for extended period.Clinical trial registration: CTRI/2021/06/034185.

Adenosine, caffeine, and sleep-wake regulation: state of the science and perspectives

For hundreds of years, mankind has been influencing its sleep and waking state through the adenosinergic system. For ~100 years now, systematic research has been performed, first started by testing the effects of different dosages of caffeine on sleep and waking behaviour. About 70 years ago, adenosine itself entered the picture as a possible ligand of the receptors where caffeine hooks on as an antagonist to reduce sleepiness. Since the scientific demonstration that this is indeed the case, progress has been fast. Today, adenosine is widely accepted as an endogenous sleep‐regulatory substance. In this review, we discuss the current state of the science in model organisms and humans on the working mechanisms of adenosine and caffeine on sleep. We critically investigate the evidence for a direct involvement in sleep homeostatic mechanisms and whether the effects of caffeine on sleep differ between acute intake and chronic consumption. In addition, we review the more recent evidence that adenosine levels may also influence the functioning of the circadian clock and address the question of whether sleep homeostasis and the circadian clock may interact through adenosinergic signalling. In the final section, we discuss the perspectives of possible clinical applications of the accumulated knowledge over the last century that may improve sleep‐related disorders. We conclude our review by highlighting some open questions that need to be answered, to better understand how adenosine and caffeine exactly regulate and influence sleep.

The Effect of Experimental Recuperative and Appetitive Post-lunch Nap Opportunities, With or Without Caffeine, on Mood and Reaction Time in Highly Trained Athletes

Purpose: To investigate the effects of placebo (PLA), 20 min nap opportunity (N20), 5mg·kg-1 of caffeine (CAF), and their combination (CAF+N20) on sleepiness, mood and reaction-time after partial sleep deprivation (PSD; 04h30 of time in bed; study 1 ) or after normal sleep night (NSN; 08h30 of time in bed; study 2 ). Methods: Twenty-three highly trained athletes ( study 1 ; 9 and study 2 ; 14) performed four test sessions (PLA, CAF, N20 and CAF+N20) in double-blind, counterbalanced and randomized order. Simple (SRT) and two-choice (2CRT) reaction time, subjective sleepiness (ESS) and mood state (POMS) were assessed twice, pre- and post-intervention. Results: SRT was lower (i.e., better performance) during CAF condition after PSD (pre: 336 ± 15 ms vs. post: 312 ± 9 ms; p < 0.001; d = 2.07; Δ% = 7.26) and NSN (pre: 350 ± 39 ms vs. post: 323 ± 32 ms; p < 0.001; d = 0.72; Δ% = 7.71) compared to pre-intervention. N20 decreased 2CRT after PSD (pre: 411 ± 13 ms vs. post: 366 ± 20 ms; p < 0.001; d = 2.89; Δ% = 10.81) and NSN (pre: 418 ± 29 ms vs. post: 375 ± 40 ms; p < 0.001; d = 1.23; Δ% = 10.23). Similarly, 2CRT was shorter during CAF+N20 sessions after PSD (pre: 406 ± 26 ms vs. post: 357 ± 17 ms; p < 0.001; d = 2.17; Δ% = 12.02) and after NSN (pre: 386 ± 33 ms vs. post: 352 ± 30 ms; p < 0.001; d = 1.09; Δ% = 8.68). After PSD, POMS score decreased after CAF (p < 0.001; d = 2.38; Δ% = 66.97) and CAF+N20 (p < 0.001; d = 1.68; Δ% = 46.68). However, after NSN, only N20 reduced POMS (p < 0.001; d = 1.05; Δ% = 78.65) and ESS (p < 0.01; d = 0.71; Δ% = 19.11). Conclusion: After PSD, all interventions reduced sleepiness and only CAF enhanced mood with or without napping. However, only N20 enhanced mood and reduced sleepiness after NSN. Caffeine ingestion enhanced SRT performance regardless of sleep deprivation. N20, with or without caffeine ingestion, enhanced 2CRT independently of sleep deprivation. This suggests a different mode of action of napping and caffeine on sleepiness, mood and reaction time.

The impact of sleep deprivation and alcohol on driving: a comparative study

Background

There is concern about the detrimental effects of shift-workers’ increasing working hours particularly when driving sleep deprived. The approach to measuring the magnitude of driving impairment caused by sleep deprivation was by comparing it to alcohol. The study compared driving performance after 24-h of wakefulness to performance with a BrAC of just over 22 μg/100mls of breath which is equal to 50 mg of alcohol per 100mls of blood (Scottish drink-drive limit). The effectiveness of coffee as a countermeasure for driver fatigue and the association between subjective impairment and actual performance was also investigated.

Methods

A study of 30 participants (11 male and 19 female; mean age 21) was conducted. Subjects were tested under three conditions: fully rested, sleep deprived, and alcohol intoxicated – BrAC mean [SD] 25.95 μg [2.78]. Under each condition, subjects were tested before and after coffee ingestion. This involved driving simulation (Lane Change Task and Reaction Test) and subjective Likert scales (Karolinska Sleepiness Scale and driver impairment scale). Outcome measures included lane tracking adaptive mean deviation, reaction time, and subjective sleepiness and impairment ratings.

Results

Compared to alcohol, sleep deprived mean reaction times were slower (2.86 s vs. 2.34 s) and lateral control of the vehicle was reduced (lane tracking adaptive mean deviation: 0.5 vs. 0.3). Coffee did not produce an improvement when sleep deprived, and instead, performance deteriorated. Females were less impaired following sleep deprivation than males. Following prolonged wakefulness, the correlation between subjective impairment and actual performance was significant.

Conclusions

It was concluded that sleep deprivation has a greater impact on driving performance than a BrAC of 22 μg/100mls of breath, as measured by driving simulation. Coffee is not an effective countermeasure for sleep deprived driving and drivers’ ability to judge this impairment is suggested to be limited.

Detection and prediction of driver drowsiness using artificial neural network models

Not just detecting but also predicting impairment of a car driver's operational state is a challenge. This study aims to determine whether the standard sources of information used to detect drowsiness can also be used to predict when a given drowsiness level will be reached. Moreover, we explore whether adding data such as driving time and participant information improves the accuracy of detection and prediction of drowsiness. Twenty-one participants drove a car simulator for 110min under conditions optimized to induce drowsiness. We measured physiological and behavioral indicators such as heart rate and variability, respiration rate, head and eyelid movements (blink duration, frequency and PERCLOS) and recorded driving behavior such as time-to-lane-crossing, speed, steering wheel angle, position on the lane. Different combinations of this information were tested against the real state of the driver, namely the ground truth, as defined from video recordings via the Trained Observer Rating. Two models using artificial neural networks were developed, one to detect the degree of drowsiness every minute, and the other to predict every minute the time required to reach a particular drowsiness level (moderately drowsy). The best performance in both detection and prediction is obtained with behavioral indicators and additional information. The model can detect the drowsiness level with a mean square error of 0.22 and can predict when a given drowsiness level will be reached with a mean square error of 4.18min. This study shows that, on a controlled and very monotonous environment conducive to drowsiness in a driving simulator, the dynamics of driver impairment can be predicted.

How much is left in your "sleep tank"? Proof of concept for a simple model for sleep history feedback

Technology-supported methods for sleep recording are becoming increasingly affordable. Sleep history feedback may help with fatigue-related decision making - Should I drive? Am I fit for work? This study examines a "sleep tank" model (SleepTank^™), which is analogous to the fuel tank in a car, refilled by sleep, and depleted during wake. Required inputs are sleep period time and sleep efficiency (provided by many consumer-grade actigraphs). Outputs include suggested hours remaining to "get sleep" and percentage remaining in tank (Tank%). Initial proof of concept analyses were conducted using data from a laboratory-based simulated nightshift study. Ten, healthy males (18-35y) undertook an 8h baseline sleep opportunity and daytime performance testing (BL), followed by four simulated nightshifts (2000 h-0600 h), with daytime sleep opportunities (1000 h-1600 h), then an 8 h night-time sleep opportunity to return to daytime schedule (RTDS), followed by daytime performance testing. Psychomotor Vigilance Task (PVT) and Karolinska Sleepiness Scale were performed at 1200 h on BL and RTDS, and at 1830 h, 2130 h 0000 h and 0400 h each nightshift. A 40-minute York Driving Simulation was performed at 1730 h, 2030 h and 0300 h on each nightshift. Model outputs were calculated using sleep period timing and sleep efficiency (from polysomnography) for each participant. Tank% was a significant predictor of PVT lapses (p < 0.001), and KSS (p < 0.001), such that every 5% reduction resulted in an increase of two lapses, or one point on the KSS. Tank% was also a significant predictor of %time in the Safe Zone from the driving simulator (p = 0.001), such that every 1% increase in the tank resulted in a 0.75% increase in time spent in the Safe Zone. Initial examination of the correspondence between model predictions and performance and sleepiness measures indicated relatively good predictive value. Results provide tentative evidence that this "sleep tank" model may be an informative tool to aid in individual decision-making based on sleep history.

Adapting artificial neural networks to a specific driver enhances detection and prediction of drowsiness

Monitoring car drivers for drowsiness is crucial but challenging. The high inter-individual variability observed in measurements raises questions about the accuracy of the drowsiness detection process. In this study, we sought to enhance the performance of machine learning models (Artificial Neural Networks: ANNs) by training a model with a group of drivers and then adapting it to a new individual. Twenty-one participants drove a car simulator for 110 min in a monotonous environment. We measured physiological and behavioral indicators and recorded driving behavior. These measurements, in addition to driving time and personal information, served as the ANN inputs. Two ANN-based models were used, one to detect the level of drowsiness every minute, and the other to predict, every minute, how long it would take the driver to reach a specific drowsiness level (moderately drowsy). The ANNs were trained with 20 participants and subsequently adapted using the earliest part of the data recorded from a 21st participant. Then the adapted ANNs were tested with the remaining data from this 21st participant. The same procedure was run for all 21 participants. Varying amounts of data were used to adapt the ANNs, from 1 to 30 min, Model performance was enhanced for each participant. The overall drowsiness monitoring performance of the models was enhanced by roughly 40% for prediction and 80% for detection.

Sleep inertia associated with a 10-min nap before the commute home following a night shift: A laboratory simulation study

Night shift workers are at risk of road accidents due to sleepiness on the commute home. A brief nap at the end of the night shift, before the commute, may serve as a sleepiness countermeasure. However, there is potential for sleep inertia, i.e. transient impairment immediately after awakening from the nap. We investigated whether sleep inertia diminishes the effectiveness of napping as a sleepiness countermeasure before a simulated commute after a simulated night shift. N=21 healthy subjects (aged 21-35 y; 12 females) participated in a 3-day laboratory study. After a baseline night, subjects were kept awake for 27h for a simulated night shift. They were randomised to either receive a 10-min nap ending at 04:00 plus a 10-min pre-drive nap ending at 07:10 (10-NAP) or total sleep deprivation (NO-NAP). A 40-min York highway driving task was performed at 07:15 to simulate the commute. A 3-min psychomotor vigilance test (PVT-B) and the Samn-Perelli Fatigue Scale (SP-Fatigue) were administered at 06:30 (pre-nap), 07:12 (post-nap), and 07:55 (post-drive). In the 10-NAP condition, total pre-drive nap sleep time was 9.1±1.2min (mean±SD), with 1.3±1.9min spent in slow wave sleep, as determined polysomnographically. There was no difference between conditions in PVT-B performance at 06:30 (before the nap). In the 10-NAP condition, PVT-B performance was worse after the nap (07:12) compared to before the nap (06:30); no change across time was found in the NO-NAP condition. There was no significant difference between conditions in PVT-B performance after the drive. SP-Fatigue and driving performance did not differ significantly between conditions. In conclusion, the pre-drive nap showed objective, but not subjective, evidence of sleep inertia immediately after awakening. The 10-min nap did not affect driving performance during the simulated commute home, and was not effective as a sleepiness countermeasure.

Do night naps impact driving performance and daytime recovery sleep?

Short, nighttime naps are used as a fatigue countermeasure in night shift work, and may offer protective benefits on the morning commute. However, there is a concern that nighttime napping may impact upon the quality of daytime sleep. The aim of the current project was to investigate the influence of short nighttime naps (<30min) on simulated driving performance and subsequent daytime recovery sleep. Thirty-one healthy subjects (aged 21-35 y; 18 females) participated in a 3-day laboratory study. After a 9-h baseline sleep opportunity (22:00h-07:00h), subjects were kept awake the following night with random assignment to: a 10-min nap ending at 04:00h plus a 10-min nap at 07:00h; a 30-min nap ending at 04:00h; or a no-nap control. A 40-min driving simulator task was administered at 07:00h and 18:30h post-recovery sleep. All conditions had a 6-h daytime recovery sleep opportunity (10:00h-16:00h) the next day. All sleep periods were recorded polysomnographically. Compared to control, the napping conditions did not significantly impact upon simulated driving lane variability, percentage of time in a safe zone, or time to first crash on morning or evening drives (p>0.05). Short nighttime naps did not significantly affect daytime recovery total sleep time (p>0.05). Slow wave sleep (SWS) obtained during the 30-min nighttime nap resulted in a significant reduction in SWS during subsequent daytime recovery sleep (p<0.05), such that the total amount of SWS in 24-h was preserved. Therefore, short naps did not protect against performance decrements during a simulated morning commute, but they also did not adversely affect daytime recovery sleep following a night shift. Further investigation is needed to examine the optimal timing, length or combination of naps for reducing performance decrements on the morning commute, whilst still preserving daytime sleep quality.

The Case for Addressing Operator Fatigue

Sleep deficiency, which can be caused by acute sleep deprivation, chronic insufficient sleep, untreated sleep disorders, disruption of circadian timing, and other factors, is endemic in the U.S., including among professional and non-professional drivers and operators. Vigilance and attention are critical for safe transportation operations, but fatigue and sleepiness compromise vigilance and attention by slowing reaction times and impairing judgment and decision-making abilities. Research studies, polls, and accident investigations indicate that many Americans drive a motor vehicle or operate an aircraft, train or marine vessel while drowsy, putting themselves and others at risk for error and accident. In this chapter, we will outline some of the factors that contribute to sleepiness, present evidence from laboratory and field studies demonstrating how sleepiness impacts transportation safety, review how sleepiness is measured in laboratory and field settings, describe what is known about interventions for sleepiness in transportation settings, and summarize what we believe are important gaps in our knowledge of sleepiness and transportation safety.

Effects of 28-days ingestion of a slow-release energy supplement versus placebo on hematological and cardiovascular measures of health

Background

Recently, slow release tablets have been developed to prolong energy release throughout the day. The efficacy of the delivery of slow-release caffeine alone is fairly well documented; however, an assessment of safety and tolerability of prolonged use of slow-release energy supplements is lacking. Therefore the objective of this study was to investigate the effect of daily ingestion of a slow-release energy supplement for 28 days on blood chemistry and resting cardiovascular measures in healthy men and women.

Methods

Forty healthy individuals (20 males, 20 females; age: 22.73 ± 3.06 years; height: 171.68 ± 10.45 cm; mass: 74.49 ± 15.51 kg; BMI: 25.08 ± 3.66 (kg • m²) ^-1) participated in this randomized, double-blind, placebo controlled study. Following a 12-hour fast, participants reported for pre-testing. Testing consisted of resting heart rate (RHR) and blood pressure (BP) measures, followed by assessment of metabolic blood chemistry, blood lipids and complete cell counts. Participants then supplemented with either Energize™ (SUPP) or placebo (PL) for 28 days. Post-testing occurred 24-hours after ingestion of the final dose and consisted of the same protocol at the same time of day as pre-testing.

Results

No significant changes in outcome measures were observed. A significant difference between groups was observed for plasma glucose concentrations; however, follow-up testing revealed that pre- to post-supplementation changes were not significant for either SUPP or PL. All variables remained within normal adult reference ranges. No adverse events were reported.

Conclusions

These findings indicate that 28 consecutive days ingestion of a slow release energy supplement containing caffeine in caffeine users is both safe and tolerable.

Effects of d-amphetamine on simulated driving performance before and after sleep deprivation

RATIONALE

Stimulant drugs are commonly abused and also used to promote wakefulness, yet their effects on driving performance during sleep deprivation have not been thoroughly researched in experimental studies.

OBJECTIVES

The aims were to assess the effects on fundamental driving parameters during simulated driving of two doses of d-amphetamine and further to assess the interaction between d-amphetamine and sleep deprivation.

METHODS

A double-blind, placebo-controlled experiment including 18 healthy male volunteers was conducted.

RESULTS

The participants felt more alert when taking a dose of d-amphetamine than when taking placebo, and the effect was stronger for the higher dose. However, the data did not show any evidence that taking d-amphetamine prevented the subjects from becoming successively sleepier during the night. A significant main effect of the dose was found for three out of the five primary indicators where the lower dose led to improved driving. These indicators were crossing-car reaction time, and coherence and delay from a car-following event. Regarding sleep deprivation, a main effect was found for four of the primary indicators and three of the secondary indicators. The results showed overall impaired driving with respect to standard deviation of lateral position and delay in reaction time when the sleep-deprived conditions were compared to the alert condition. We found no interactions between dose and sleep deprivation for any of the performance indicators.

CONCLUSIONS

Our results suggest that administration of d-amphetamine does not compensate for impairment of driving due to fatigue. The positive effects of 10 mg were not further improved or even sustained when increasing the dose to 40 mg.

Effect of caffeine and taurine on simulated laparoscopy performed following sleep deprivation

Background

Sleep deprivation affects surgical performance and has the potential to endanger patient safety. Pharmacological stimulants may counter this consequence of long working hours. This study aimed to investigate whether commonly available stimulants can counter the effects of fatigue on technical and neurocognitive skill.

Methods

This was a single-blind crossover study of surgical novices trained to proficiency on the Minimally Invasive Surgical Trainer—Virtual Reality laparoscopic simulator. Participants were acutely sleep-deprived three times each, followed by administration of either placebo, 150 mg caffeine, or 150 mg caffeine combined with 2 g taurine before simulated laparoscopy. Outcome measures were: laparoscopic psychomotor skill, cognitive performance and the Stanford Sleepiness Scale (range 1–7). Rested baselines were gathered following completion of test sessions.

Results

Baseline performance was recorded for 18 participants in the rested state. Sleep-deprived participants receiving the placebo took longer (median 41 versus 35 s; P = 0·016), were less economical with movement (3·25 versus 2·95 m; P = 0·016) and made more errors (66 versus 59; P = 0·021) on the laparoscopic task compared with the rested state. Caffeine restored psychomotor skills to baseline for time taken (37 versus 35 s; P = 0·101), although the number of errors remained significantly greater than in the rested state (63 versus 59; P = 0·046). Sleep-deprived subjects receiving placebo had slower reaction times (377 versus 299 ms; P = 0·008) and a higher score on the Stanford Sleepiness Scale (6 versus 2 points; P = 0·001) than rested surgeons. Negative effects of sleep deprivation on reaction time were reversed when caffeine (307 ms versus 299 ms in rested state; P = 0·214) or caffeine plus taurine (326 versus 299 ms; P = 0·110) was administered. Subjective sleepiness was also improved, but not to baseline levels.

Conclusion

Sleep deprivation affects laparoscopic psychomotor skills, reaction time and subjective measures of sleepiness in novice surgical subjects. Caffeine and taurine restore simulated laparoscopic performance to rested levels, but do not reduce errors.

Expert opinion on pharmacotherapy of narcolepsy

IMPORTANCE TO THE FIELD

Narcolepsy is a neurodegenerative disorder resulting in the instability of the sleep-wake cycle and marked by low levels of hypocretin in cerebrospinal fluid. Sleep instability is marked by brisk, sleep-onset REM periods and sleep fragmentation, while the waking state is interrupted by the intrusion of REM sleep and sometimes accompanied by cataplectic attacks.

AREAS COVERED IN THIS REVIEW

Current pharmacologic interventions that aim to address three primary features of this disorder; excessive daytime sleepiness (EDS), cataplexy and automatic behaviors, and sleep fragmentation. We review and compare the use of traditional and new stimulants in the treatment of EDS. For the treatment of cataplexy and automatic behaviors, serotonergic and noradrenergic agents are considered. The role of gamma-hydroxybutyrate (GHB) is also explored in its ability to reduce daytime sleepiness and catapletic attacks and to consolidate sleep. Findings are based on a PubMed literature search of clinical and basic science research papers spanning 1977-2009.

WHAT THE READER WILL GAIN

A comprehensive understanding of the various existing and promising future treatments for narcolepsy. For each of these treatments, we evaluate risks versus benefits of treatment, and proposed pharmacologic mechanisms of action. We conclude with a review of new treatment approaches, including thyrotropin-releasing hormone (TRH), histamine agonists, immunotherapy and hypocretin replacement therapies.

TAKE HOME MESSAGE

Narcolepsy is an autoimmune, neurodegenerative disorder that results in significant sleep-wake instability with or without cataplectic attacks. Current treatments aim symptomatically to reconsolidate the sleep and waking states and to reduce daytime attacks of cataplexy. Future treatments aim primarily towards correcting the causal deficiency of hypocretin or preventing the autoimmune response that results in the loss of hypocretin cells.

Effects of modafinil on simulator driving and self-assessment of driving following sleep deprivation

OBJECTIVES

While it has been suggested that the novel wake promoting drug modafinil may have some utility with respect to drowsy driving in healthy adults, this has not been investigated until now. The present study was designed to assess the effects of modafinil on objective and self-assessed driving simulator performance during an overnight period of sleep loss.

METHODS

Sixteen healthy participants (eight males and eight females) remained awake overnight on two separate occasions during which they ingested either a single 300 mg dose of modafinil or a placebo capsule at either 0230 or 0330 h. Two hours post-treatment, participants were evaluated using measures of driving simulator performance, self-assessed driving performance and subjective alertness.

RESULTS

Modafinil treatment reduced lane deviation but had less effect on speed deviation, off-road incidents and reaction time to a concurrent task. Modafinil also improved subjective appraisals of driving performance, although its use may have resulted in overconfidence in driving ability during short trips.

CONCLUSIONS

Modafinil offers some benefits with respect to objective driving performance under conditions of sleep loss. However it may induce overconfidence, suggesting that its use as a countermeasure to drowsiness when driving requires further examination.

Circadian rhythm sleep disorders: part I, basic principles, shift work and jet lag disorders. An American Academy of Sleep Medicine review

OBJECTIVE

This the first of two articles reviewing the scientific literature on the evaluation and treatment of circadian rhythm sleep disorders (CRSDs), employing the methodology of evidence-based medicine. In this first part of this paper, the general principles of circadian biology that underlie clinical evaluation and treatment are reviewed. We then report on the accumulated evidence regarding the evaluation and treatment of shift work disorder (SWD) and jet lag disorder (JLD).

METHODS

A set of specific questions relevant to clinical practice were formulated, a systematic literature search was performed, and relevant articles were abstracted and graded.

RESULTS

A substantial body of literature has accumulated that provides a rational basis the evaluation and treatment of SWD and JLD. Physiological assessment has involved determination of circadian phase using core body temperature and the timing of melatonin secretion. Behavioral assessment has involved sleep logs, actigraphy and the Morningness-Eveningness Questionnaire (MEQ). Treatment interventions fall into three broad categories: 1) prescribed sleep scheduling, 2) circadian phase shifting ("resetting the clock"), and 3) symptomatic treatment using hypnotic and stimulant medications.

CONCLUSION

Circadian rhythm science has also pointed the way to rational interventions for the SWD and JLD, and these treatments have been introduced into the practice of sleep medicine with varying degrees of success. More translational research is needed using subjects who meet current diagnostic criteria.

Perception of simulated driving performance after sleep restriction and caffeine

OBJECTIVE

As feelings of alertness are reported to be highly correlated with performance perception, the objective of this study was to determine whether caffeine, a common countermeasure to driver sleepiness, affected a sleepy driver's ability to monitor his or her simulated driving performance.

METHODS

Twelve healthy young adults (six males, six females) participated in three counterbalanced, blinded, daytime conditions: control [9 h time in bed (TIB)], 100 mg caffeine (4 h TIB), and placebo (4 h TIB). Driving performance was measured through lane drift on a series of 30-min simulated driving sessions. Subjective sleepiness and perception of driving performance were measured at 5-min intervals during driving sessions via the Karolinska Sleepiness Scale and a corresponding perception scale.

RESULTS

Sleep restriction had a significant detrimental effect on driving performance and subjective measures. Caffeine resulted in significant improvements across all measures. Subjective measures were found to be significantly correlated after sleep restriction and prior to caffeine. Correlations between actual and perceived performance were nonsignificant across all conditions.

CONCLUSIONS

The strong correlation between subjective measures supports the postulation that sleepiness is used as a cue for performance prediction when sleep restricted. The relationship between perceived and actual performance after fatigue countermeasures remains inconclusive. Further research, addressing limitations, is needed.

Sleep disorders, sleepiness and traffic safety: a public health menace

Sleep disorders are not uncommon and have been widely reported throughout the world. They have a profound impact on industrialized 24-h societies. Consequences of these problems include impaired social and recreational activities, increased human errors, loss of productivity, and elevated risk of accidents. Conditions such as acute and chronic insomnia, sleep loss, excessive sleepiness, shift-work, jet lag, narcolepsy, and sleep apnea warrant public health attention, since residual sleepiness during the day may affect performance of daily activities such as driving a car. Benzodiazepine hypnotics and zopiclone promote sleep, both having residual effects the following day including sleepiness and reduced alertness. In contrast, the non-benzodiazepine hypnotics zolpidem and zaleplon have no significant next-day residual effects when taken as recommended. Research on the effects of wakefulness-promoting drugs on driving ability is limited. Countermeasures for excessive daytime sleepiness have a limited effect. There is a need for a social awareness program to educate the public about the potential consequences of various sleep disorders such as narcolepsy, sleep apnea, shift-work-related sleep loss, and excessive daytime sleepiness in order to reduce the number of sleep-related traffic accidents.

Caffeine: implications for alertness in athletes

Caffeine is one of the most widely consumed drugs in the world, taken socially and for its alertness- and performance-promoting actions. Extensive reports assert that caffeine increases alertness and cognitive performance levels and, when taken before exercise, demonstrates ergogenic properties. Caffeine ingestion has been associated with increased performance during endurance submaximal, and acute, high-intensity exercise. The exact mechanism of action for the performance effects of caffeine is unknown, although several physiologically and psychologically based theories exist as to how caffeine achieves increased performance capabilities. This paper outlines the known sites of caffeine activity in the body,and discusses these with respect to the effects of caffeine observed during performance assessments.

The efficacy of naps as a fatigue countermeasure: a meta-analytic integration

Modern requirements for extended operations in aviation, transportation, the military, and industry have led to extensive research on countermeasures to mitigate the adverse effects of fatigue. The goals of this research were to (a) summarize and integrate existing research on naps as a fatigue countermeasure using meta-analysis, (b) identify the strength and significance of the effects of naps on performance and feelings of fatigue, and (c) identify factors that may moderate the effects of napping as a fatigue countermeasure. The results of these analyses can be used to predict nap efficacy as a function of length of the nap and the postnap interval. The results of these analyses also suggest an approach to work design that takes into account the optimal effects of naps as a fatigue countermeasure. Actual or potential applications of this research include the development of optimal work schedules to minimize fatigue and increase safety.

Effect of cognitive arousal on sleep latency, somatic and cortical arousal following partial sleep deprivation

Emerging research has shown that sleepiness, defined as the tendency to fall asleep, is not only determined by sleep pressure and time of day, but also by physiological and cognitive arousal. In this study we evaluated (i) the impact of experimentally induced cognitive arousal on electroencephalogram (EEG) defined sleep latency, and subjective, somatic and cortical arousal, and (ii) whether experimentally induced cognitive arousal enhances performance on a driving simulator test. Twelve healthy sleepers each spent three nights and the following day in the sleep laboratory: an adaptation, a cognitive arousal and a neutral testing day. In the cognitive arousal condition, a visit of a television camera crew took place and subjects were asked to be interviewed. On each testing day, a 5-min heart rate recording, subjective sleepiness and arousal scales, Multiple Sleep Latency Test and a 25-min driving simulator task were scheduled three times at 2-h intervals. Experimentally induced cognitive arousal resulted in significant increases in objective sleep latency. Significantly elevated levels of subjective and somatic arousal--as indexed by a subjective arousal scale and heart rate--were also evidenced following cognitive arousal induction. A marginally significant trend for increased cortical arousal, measured by EEG beta activity, was also found. No effects were found on driving simulator performance. These findings support the concept of cognitive arousal as a significant component in determining sleep latency. In addition, it was illustrated that cognitively induced arousal can provoke increases in somatic and possibly even cortical arousal in normal sleepers. However, this was not accompanied by an enhanced ability to perform adequately on a driving simulator test.