DOT/FAA/AM-00/10

U.S. Department

of Transpor tation

Federal Aviation

Administration

Pamela S. Della Rocco

Carlos Comperatore

Lynn Caldwell

Crystal Cruz

Civil Aeromedical Institute

Federal Aviation Administration

Oklahoma City, Oklahoma 73125

February 2000

Final Report

This document is available to the public

through the National Technical Information

Service, Springfield, Virginia 22161.

Office of Aviation Medicine

Washington, D.C. 20591

The Effects of Napping on

Night Shift Performance
NOTICE

This document is disseminated under the sponsorship of

the U.S. Department of Transportation in the interest of

information exchange. The United States Government

assumes no liability for the contents thereof.
i

Technical Report Documentation Page

1. Report No. 2. Government Accession No. 3. Recipient's Catalog No.

DOT/FAA/AM-00/10

4. Title and Subtitle 5. Report Date

The Effects of Napping on Night Shift Performance February 2000

6. Performing Organization Code

7. Author(s) 8. Performing Organization Report No.

Della Rocco, P.S., Comperatore, C., Caldwell, L., and Cruz, C.

9. Performing Organization Name and Address 10. Work Unit No. (TRAIS)

11. Contract or Grant No.

FAA Civil Aeromedical Institute

P.O. Box 25082

Oklahoma City, OK 73125

12. Sponsoring Agency name and Address 13. Type of Report and Period Covered

Office of Aviation Medicine

Federal Aviation Administration 14. Sponsoring Agency Code

800 Independence Ave., S.W.

Washington, DC 20591

15. Supplemental Notes

16. Abstract

This study represents a collaborative effort between the Federal Aviation Administration’s Civil Aeromedical Institute

and the US Army Aeromedical Research Laboratory to investigate the effects of napping on the midnight shift as a

potential countermeasure to sleepiness during the shift. The purpose of the present paper was to examine the patterns of

performance degradation along with the subjective measures of mood, sleep quality, and sleepiness as a function of

napping condition and time on task during the midnight shift. Sixty Air Traffic Control Specialists (ATCSs) were

randomly assigned to one of the three midnight shift napping conditions: a long nap (LN) of 2 hours, a short nap (SN)

of 45 minutes, and a no nap condition (NN). ATCSs completed a four-day protocol during which they worked three

early morning shifts (0700-1500) followed by a rapid rotation to the midnight shift (2300-0700). Subjects completed

three 1.5 hour test sessions (one session before the nap and 2 sessions after the nap) during the midnight shift involving

two computer-based tasks: 1) the Air Traffic Scenarios Test (ATST), a task developed for selection of ATCSs, and 2)

the Bakan, a test of vigilance. Data were analyzed using repeated measures analysis of variance and post-hoc multiple

comparisons. Both cognitive performance and subjective measures of sleepiness supported the use of naps during the

midnight shift. In fact, both the long nap of 2 hours and the short nap of 45 minutes resulted in better performance

than no nap on the Bakan test at the end of the midnight shift. A dose-response relationship existed such that the long

nap also resulted in better performance than the short nap. The ATST, on the other hand, was much less sensitive to

differences in napping condition and even to the natural circadian trough, which would have been expected to affect all

groups. Sleepiness ratings on the Stanford Sleepiness Scale suggested that, while sleepiness increased across the midnight

shift for all groups, ratings were generally lower for the LN condition and were lower for males in the SN condition,

when compared with the NN condition. The present study suggests that naps taken during the midnight shift could be

useful as a countermeasure to performance decrement and sleepiness on the midnight shift.

17. Key Words 18. Distribution Statement

Air Traffic Control Specialists, Naps, Shiftwork, Night

Shift, Performance, Vigilance, Sleepiness, Sleep Quality,

Mood

Document is available to the public through the

National Technical Information Service,

Springfield, Virginia 22161

19. Security Classif. (of this report) 20. Security Classif. (of this page) 21. No. of Pages 22. Price

Unclassified Unclassified 36

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized

1

THE EFFECTS OF NAPPING ON NIGHT SHIFT PERFORMANCE

Sleepiness on the first midnight shift of a work

schedule is common among shiftworkers when their

circadian rhythms are day-oriented. Effective countermeasures for sleepiness are important for employees in a safety critical job such as the Federal Aviation

Administration’s (FAA) Air Traffic Control Specialist (ATCS). The Human Factors Research Laboratory (HFRL) at the Civil Aeromedical Institute

(CAMI) was asked by the Miami Air Route Traffic

Control Center to investigate sleepiness on the midnight shift. They specifically requested information

about the possibility of using a scheduled nap as a

method to reduce sleepiness and maintain alertness

during this shift.

The shift schedules worked by ATCSs often minimize the employee’s exposure to the midnight shift

(Cruz & Della Rocco, 1995). ATCSs generally work

only one or two midnight shifts in a row. Thus, a

circadian adaptation strategy of shifting the biological

clock to a night orientation is not practical in this

population because of the time courses required to shift

the clock to a night orientation and return back to a day

orientation. An acutely administered coping strategy,

such as scheduled napping, therefore, was a more reasonable candidate for a sleepiness countermeasure.

The purpose of this study was to determine the

effect of naps taken during a night shift on sleepiness

and performance after awakening and throughout

the duty hours following the nap. Issues related to

sleep duration and sleep inertia were investigated.

The study specifically compared two napping conditions, a Long Nap (2 hours) and a Short Nap (45

minutes), to a No Nap condition. Performance was

examined on two tasks, an air traffic scenarios task

(high workload) and a vigilance task (low workload).

BACKGROUND

The problems associated with night and shift work

have been investigated by many researchers over the

past several years (Folkard, 1989; Wilkinson, 1992).

These problems include physiological, psychological, and social difficulties experienced by people who

must change their sleep/wake schedule from day

activity and night sleep to day sleep and night activity

(Anch, Browman, Mitler, & Walsh, 1988).

Research indicates that a major problem among

shift workers is disturbed sleep. Daytime sleep is

shorter than nighttime sleep and tends to be fragmented (Torsvall, Akerstedt, Gillander, & Knutsson,

1989; Tilley, Wilkinson, Warren, Watson, & Drud,

1982). In addition, the order of slow wave sleep (SWS)

and rapid eye movement (REM) sleep is disturbed, with

more REM sleep occurring at the beginning of the sleep

period and more SWS occurring at the end, the opposite

of the natural SWS/REM pattern (Tilley et al., 1982).

Due to the disturbance in sleep, research shows that shift

workers nap more frequently than daytime workers to

compensate for the sleep loss (cf Rosa, 1993; Akerstedt

& Torvsall, 1985).

Research also shows that night workers have increased sleepiness during work, with most sleepiness

occurring during the last half of the work shift

(Akerstedt, Torsvall, & Gillberg, 1982). This increase in sleepiness during work leads to a decrease in

performance (Mitler, Carskadon, Czeisler, Dement,

Dinges & Graeber, 1988), an increase in accidents

(Ribak, Ashkenazi, Klepfish, Avgar, Tall, Kallner &

Noyman, 1983), and an increase in spontaneous naps

on the job (Torsvall & Akerstedt, 1987; Torsvall et

al., 1989). According to a report by the Association of

Professional Sleep Societies’ Committee on Catastrophes, Sleep and Public Policy, heart attacks, vehicular accidents, performance errors, and major

disasters are more likely to occur during the early

morning hours of shift work (Mitler et al., 1988).

Other researchers have reported increased accidents

due to sleepiness in night workers (Hamelin, 1987;

Ribak et al., 1983; Torsvall & Akerstedt, 1987).

Abuse of substances such as nicotine, caffeine, and

other stimulants to help maintain alertness, and sleeping pills to help obtain sleep also have been reported

(cf Penn & Bootzin, 1990).

According to Czeisler and his colleagues (Czeisler,

Kronauer, Allan, Duffy, Jewett, Brown & Ronda,

1989; Czeisler, Johnson, Duffy, Brown, Ronda &
2

Kronauer, 1990), the problems associated with night

work — sleep problems, fatigue and sleepiness, and

decreased performance — result from a desynchronization of the circadian cycle. Other problems in

shift workers stem from the social and family disruptions associated with shift work (Penn & Bootzin,

1990). Workers desiring to spend time with family

and friends may not sleep when the opportunity

comes, leading to more fatigue and lack of sleep due

to social and family activities.

Because of the problems inherent with night work,

many interventions have been attempted to alleviate

the ill effects. Some of the methods undertaken

during the night shift to increase arousal and performance include rest breaks, social activity during

breaks, increasing task demands, feedback about work

performance, exercise, bright lights, and naps (Penn

& Bootzin, 1990; Bonnet, 1990). Napping seems to

be an effective, inexpensive way to help alleviate the

sleepiness experienced during night work, particularly for those night workers whose schedules require

minimal exposure to night work and circadian adaptation to a night shift is not desirable.

Naitoh, Englund, and Ryman (1982) indicate that

several variables must be considered when scheduling

naps during a prolonged work period. These variables

are as follows: 1) the extent of sleep loss prior to the

work period (i.e., sleep deprivation), 2) the length of

the nap, 3) the placement of the nap within the

circadian phase, and 4) the length of time between

the end of the nap and the work period.

Sleep deprivation. The length of the total sleep

deprivation period is an important factor when determining whether a nap will be beneficial. Most data

suggest that the best time to nap is before significant

sleep loss has occurred; however, naps do not completely reverse the effects of sleep loss (Bonnet, 1991;

Dinges, Orne, Whitehouse, & Orne, 1987). In a

study conducted by Bonnet (1991), subjects were

kept awake for 52 hours. A nap taken before the

continuous wake period was beneficial in keeping

performance and alertness from decreasing for up to

24 hours of sleep loss, as compared to a No Nap

condition. By the second night of sleep loss, the

benefit of the naps could not be reliably measured.

Other studies have found similar results using only

24 hours of sleep deprivation (Dinges et al., 1987;

Gillberg, 1984; Nicholson, Pascoe, Roehrs, Roth,

Spencer, Stone & Zorick, 1985; Bonnet, 1990). The

findings from each of these studies indicate that a nap

taken before an extended sleep loss period, called

“prophylactic naps”, will considerably attenuate the

decrease in performance during a night shift.

Length of nap. It is very difficult to compare many

of the nap studies due to variations in methodology,

however, most studies indicate that naps from 1 hour

to 8 hours will improve performance and alertness

during continuous operations (Bonnet, 1991). In a

study by Naitoh and colleagues (1982), subjects were

given a 3-hour nap after being awake for approximately 24 hours. After the nap, they were required to

stay awake an additional 20 hours. Results indicated

that this 3-hour nap reduced the decline in performance over the additional work period.

Another study (Lumley, Roehrs, Zorick, Lamphere,

& Roth, 1986) deprived subjects of sleep for 24

hours, after which a nap of either 15, 30, 60, or 120

minutes was given. The results indicated that alertness increased with the increase in nap length, with

the highest level of alertness occurring after the 60-

minute nap. There was no difference between the 60-

minute nap and the 120-minute nap, possibly due to

fragmentation of the sleep in the longer nap. The

authors concluded that the alerting effects of naps are

related to the length of the nap.

The same relationship between nap length and performance was found in a study by Bonnet (1991) which

allowed subjects either a 2, 4, or 8-hour nap before 52

hours of continuous operations. The results indicated a

dose-response relationship between the length of the

nap and performance during the first 24 hours of sleep

deprivation. Based on this type of nap, Bonnet concluded that the nap one takes before an all-night shift

should be as long as possible to have a maximum benefit

on performance. He also states that a nap should ideally

be prophylactic, and not used to replace lost sleep from

the regular sleep period. Prophylactic naps may be more

beneficial during a sleep deprivation period than a nap

during the continuous wakefulness period (Mullaney,

Kripke, Fleck, & Johnson, 1983; Gillberg, 1984;

Nicholson et al., 1985; Carskadon & Dement, 1982;

Haslam, 1985).

In a study by NASA (Graeber, Rosekind, Connell,

& Dinges, 1990), one group of pilots was given a 40-

minute rest period followed by a 20-minute recovery

period during a long-haul flight. Performance was

maintained at consistent levels, and physiological

alertness was higher during the last 90 minutes of

flight. These naps were implemented with no evidence of compromised safety. In a group which was
3

not allowed a rest period, the occurrence of reduced

physiological alertness (micro-events) was five times

higher than in the group who took a nap. Although

current regulations prohibit sleep in the cockpit, the

results of this study indicated that a planned rest

period during the cruise portion of long-haul flights

may increase safety by reducing uncontrolled and

involuntary napping and increase safety associated

with higher alertness at the end of the flight.

Generally, studies conclude that a nap of 1 to 4

hours in length prior to a night work period improved morning performance and alertness above

that seen without a nap. As summarized by Bonnet

(1990), results from many studies indicate that naps

do not totally eliminate the circadian dip seen in the

early morning (around 0500), but the degradation in

both cognitive performance and alertness is attenuated.

Circadian placement of nap. Much research has

been conducted to determine the circadian pattern of

sleep and alertness. Sleep tendency is highest when

core body temperature is in its trough, around 0300,

and is lowest when core body temperature is at its

peak, around 1500 (Dinges, 1986). The effects of

naps taken during the circadian trough are different

from the effects of naps taken during the circadian

peak. Research in which a 2-hour nap was given at

five different times within a 24-hour period indicated that a nap taken during the early morning

reinforced the circadian rhythm of temperature,

strengthening the normal fall and rise of core temperature (Matsumoto, 1981). A study by Naitoh,

Englund, and Ryman (1982) indicated that a 3-hour

nap taken between 0400 and 0700 after 20 hours of

continuous wakefulness reduced the amount of performance degradation seen upon awakening when

compared to a no nap group. Gillberg (1984) examined the effects of a 1-hour nap on subjects after only

24 hours of sleep deprivation. Two nap times were

tested — 2100 and 0430. Both naps improved performance the following morning when compared to

a no nap group, especially the nap taken at 0430.

Other studies indicated that early morning naps are

beneficial in restoring alertness and performance

(Matsumoto, 1981; Naitoh, Englund, & Ryman,

1982; Gillberg, 1984). Dinges and colleagues (Dinges,

Whitehouse, Orne & Orne, 1988) found that a nap

taken anywhere in the circadian cycle before a sleep

loss period will be beneficial in maintaining performance across the sleep loss period.

Another use of naps is as an adjunct to the regular

sleep period. There is substantial evidence that a nap

taken during the day before an all-night work shift,

but no sleep loss prior to the shift, will result in less

performance decrement over the night than without

the nap. Schweitzer, Muehlback & Walsh (1992)

measured performance and alertness in subjects who

received a 2- to 3-hour nap before the night shift.

Although the usual circadian trough was seen in the

early morning, the nap attenuated the decline in

performance when compared to a night when no nap

was taken prior to the shift.

A study by Matsumoto and Harada (1994) indicated that a nap taken during the night work period

can help alleviate the fatigue caused by night work, a

practice commonly used in Japan. A study by Rogers,

Spencer, Stone, & Nicholson (1989) found that a 1-

hour nap taken at 0200 during a work period had

limited beneficial effects on performance compared

to a no nap condition.

Time between the nap and the work period.

When scheduling a nap, one should consider whether

performance is required immediately upon awakening. Performance is generally low immediately upon

awakening, but recovers usually after 15 to 30 minutes (Dinges, Orne, & Orne, 1985). This decrease in

performance shortly after awakening is called “sleep

inertia.” Several factors will lead to extensive sleep

inertia: awakening from non-rapid eye movement

(NREM) sleep, especially slow wave sleep (SWS);

awakening within the first few hours of sleep; and

sleep following a long period of sleep deprivation

(Dinges, Orne, & Orne, 1985). Studies show that

post-nap sleepiness is higher and performance is

lower when one is awakened from a nap during the

circadian trough as compared to a nap taken during

the circadian peak (Dinges, Orne, & Orne, 1985).

Lavie and Weler (1989) found that, after 32 hours of

sleep deprivation, a 2-hour nap taken at 1500 produced less sleep inertia than a 2-hour nap taken at

1900. However, the later nap was more successful in

reducing sleepiness levels during the early morning

(2300 to 0400) than the early nap. In a study by

Dinges and associates (1985), subjects deprived of

sleep for 54 hours were given 2-hour naps at various

times in the circadian cycle, corresponding to peaks

and troughs in the cycle. The results indicated that

naps taken during the circadian troughs led to greater

performance decrements than did naps taken during
4

the circadian peaks. The authors concluded that

during continuous performance operations, naps in

the circadian trough should be avoided, and naps

should be taken before a person’s sleep loss extends

beyond 36 hours.

In summary, some research indicates that a nap

during the night shift would be beneficial in reducing

the circadian trough in performance usually seen in

the early morning hours. When a person must return

to work immediately upon awakening, sleep inertia

should be considered. This decrease in performance

due to sleep inertia is worse when one is awakened

from slow wave sleep, during the circadian trough, or

after a long period of sleep deprivation.

Miami ARTCC ATCSs requested a study examining the utility of naps taken on the night shift as a way

to alleviate sleepiness and maintain alertness. Since

ATCSs are generally scheduled for only one or two

night shifts per work week, it is undesirable to shift

their circadian rhythms to a night shift. Allowing a

nap during the work shift may serve to: 1) improve

alertness and maintain performance, 2) strengthen

the normal rise and fall of the temperature curve, 3)

provide an anchor sleep that could maintain stability

in the sleep/wake cycle, and 4) decrease the amount

of unscheduled napping by workers who have a

difficult time staying awake, thus enhancing safety

during the shift.

The present study examined the effects of two

different nap lengths scheduled prior to and into the

approximate circadian trough on the ability of both

male and female ATCSs to maintain alertness and

performance levels during a night shift. The questions addressed were as follows: 1) Does a nap taken

during a night shift decrease subsequent sleepiness

and maintain performance during the remainder of

the shift when compared with alertness and performance without a nap? 2) Do the effects of a 45-

minute nap differ from the effects of a 120-minute

nap on alertness and performance? 3) Are there gender differences in response to a nap taken during the

night shift? The two types of performance tasks, the

low fidelity air traffic control (ATC) simulation and

the vigilance task, were used to assess performance

relevant to ATC.

METHODS

The study compared naps of two different durations to a No Nap (NN) condition. The long-nap

(LN) was 120 minutes. The short-nap (SN) was 45

minutes. The protocol involved 9 days of subject

participation. During the first five days, subjects

were asked to wear wrist activity monitors and to

maintain a sleep/wake cycle ensuring day-orientation

of the circadian rhythms. On the fifth day (Sunday

evening), subjects reported to the sleep laboratory at

the U.S. Army Aeromedical Research Laboratory in

Ft. Rucker, Alabama where they maintained residence for the remainder of the study. The laboratory

protocol involved three days of synthetic work (computerized test battery) on an early morning schedule

(0700-1500) followed by a quick-turn-around (8

hours off duty) to a night shift (2300-0700). Subjects

were trained on the computerized test battery during

the three day shifts. The effects of napping were

assessed on the night shift.

Subjects

Subject recruitment and reimbursement. Army

participants were recruited through the Commander’s

office of the 1-11th Aviation Regiment. The study

was coordinated with the FAA Office of Air Traffic

Program Management (ATZ-1). FAA participants

were recruited through active assistance of the National Air Traffic Controllers Association (NATCA)

and coordination with FAA Regional Air Traffic

Offices. Information regarding the study was distributed to FAA Air Traffic Regional Vice Presidents. A

contact in each region was established to coordinate

participation in the study with CAMI staff. Individuals interested in participating provided their name to

the regional contact person. CAMI staff contacted

volunteers to conduct screening and to obtain informed consent to participate in the study. In addition to their normal salary for a 40-hour work week

for the 5-day period of travel and participation, FAA

ATCSs received 5 hours of overtime pay, 2 hours of

Sunday premium pay, and 8 hours of midnight shift

differential. All travel expenses and per diem were

paid by the FAA.

Subject selection. FAA ATCSs were required to

hold FAA medical certification. Army air traffic

controllers underwent a brief medical examination
5

by the USAARL medical monitor to ensure that they

met Class II standards. Volunteers were excluded for

1) hypertension, 2) taking medication which could

not be discontinued during study participation, 3)

use of tobacco products, 4) high caffeine consumption (more than 3 cups of coffee or 6 colas containing

caffeine, or 6 cups or glasses of tea per day), or 5) any

medical disorder which sleep deprivation may exaggerate. All subjects were selected between the ages of

20 and 40. One female ATCS was included even

though she turned 41 prior to being scheduled to

participate.

A total of 65 air traffic controllers completed the

study protocol. Four of the controllers were members

of the Army 1-11th Aviation Regiment and worked

in a tower. The remaining 61 controllers were employed by the FAA. Two additional FAA ATCSs

began participation but withdrew from the study

before completing the protocol. One of these participants experienced insomnia during the first two

nights of the protocol. The other participant who

withdrew from the study did not like wearing the

EEG electrodes. The FAA ATCSs were from both

terminal and enroute facilities, representing all geographic regions of the United States. Subjects were

randomly assigned to Nap Condition by Gender

resulting in the following groups: 1) Short Nap male

(SNM), 2) Short Nap female (SNF), 3) Long Nap

male (LNM), 4) Long Nap female (LNF), 5) No Nap

male (NNM), and 6) No Nap female (NNF).

Data from 59 participants are reported here. Data

from six of the 65 were not included in these analyses.

Of those six, four subjects’ computer files for the

midnight shift performance on the Air Traffic Scenarios Test were unrecoverable, and two subjects

assigned to the No Nap Condition were determined

by EEG scoring to have taken naps of at least 30

minutes in length on the midnight shift. The resulting groups were as follows: 1) SNM, (n=10), 2) SNF,

(n=10), 3) LNM, (n=10), 4) LNF, (n=10), 5) NNM,

(n=8), and 6) NNF, (n=11).

Subject demographics. The average age of the 59

volunteers was 33.4 years (sd=3.9 years). The female

participants were slightly younger on average (M=32.2

years, sd=4.0 years) than the male participants

(M=34.8 years, sd=3.3 years). The majority of participants (n=54, 91.5%) were Caucasian; two (3.4%)

were Hispanic; two (3.4%) were Black; and one

(1.7%) was American Indian. More than half of the

participants were married (n=33; 55.9%); 15 were

single (25.4%); 6 were divorced or separated (10.2%);

3 did not respond to the question (5.1%); and 2 were

cohabitating (3.4%). Two participants were high

school graduates (3.4%); 23 completed some undergraduate college (39.0%); 2 held Associate’s degrees

(3.4%); 21 held Bachelor’s degrees (35.6%); 7 completed some post-graduate work (11.9%); 1 held a

Master’s degree (1.7%). Three subjects did not complete the question on educational background (5.1%).

Table 1 presents demographic data.

The Army participants were tower controllers and

reported an average of 4.5 years as Full Performance

Level (FPL). Of the 56 FAA ATCSs, 42 (75.0%)

reported being FPL controllers; four (7.1%) were

developmental controllers; four (7.1%) were staff

specialists; two (3.6%) were area supervisors; three

(5.4%) did not respond to the question; and one

(1.8%) worked in the Traffic Management Unit.

Table 1. Selected Demographics of Study

Participants.

Gender

Males 28

Females 31

Average Age 33.4 years

Education

High School 3.4%

Some College 39.0%

College Degree 39.0%

Some Post-graduate Work 11.9%

Graduate Degree 1.7%

Unknown 5.1%

Facility Type

Enroute 37%

Terminal 63%

Average Years Full Performance

Level

6.4 years
6

Twenty-two were from the enroute option and thirtyseven were from the terminal option. The participants in the study reported having an average of 9.2

years experience as air traffic controllers and 6.4 years

of experience as FPL controllers. Table 2 provides a

breakdown by Gender and geographic region for the

participants included in the data analysis.

In previous studies the Digit Span from the

Wechsler Adult Intelligence Scale (WAIS) (Wechsler,

1955) and the Shipley Institute of Living Scale

(Zachary, 1986) have been administered for purposes

of matching non-ATCS volunteers with ATCSs.

These tests were administered to support selection of

noncontroller subjects in case an insufficient number

of Army or FAA ATCSs volunteered for the study.

Although enough ATCSs volunteered, the data from

these measures are presented in Table 3.

Measures

Cognitive performance measures. Evaluations of

performance were measured by two tests, the Air

Traffic Scenarios Test (ATST) (Broach & BrechtClark, 1994), and a modified version of the Bakan

vigilance test (Dollins, Lynch, Wurtman, Deng,

Kischka, Gleason, & Lieberman, 1993). The ATST

was a low fidelity simulation of radar-based air traffic

control used by the FAA for a couple of years in the

Pre-Training Screen (PTS) test battery to screen air

traffic controllers before they were hired. The modified

version of the Bakan previously has been shown to be

sensitive to alertness degradation (Dollins et al., 1993).

The ATST software used in this study was from

the DOS-based, International Air Traffic Control

Specialist (termed Eurotest) version of the PTS battery

(Broach, Enos & Moore, 1994). The ATST served as

Table 2. Breakdown of Study Participants by Region and Gender.

Region Males Females TOTAL

Army (Ft. Rucker, AL) 3 0 3

Southern Region 2 4 6

Eastern Region 2 4 6

New England Region 3 2 5

Alaska Region 3 1 4

Great Lakes Region 2 11 13

Southwest Region 6 5 11

Central Region 2 3 5

Western Pacific Region 2 0 2

Northwest Mountain 3 1 4

Total 28 31 59

Table 3. Descriptive Statistics from Digit Span and Shipley Institute of Living Scale Tests.

Males Females Total

(N=28) (N=31) (N=59)

Mean SD Mean SD Mean SD

Digit Span

Forward 10.5 2.3 10.4 2.3 10.5 2.3

Backward 7.8 2.1 8.1 2.5 8.0 2.3

Shipley Institute of Living Scale

Verbal 34.2 2.4 33.3 3.2 33.7 2.9

Abstract 34.2 3.5 34.3 3.1 34.3 3.3

Combined 68.3 5.0 67.7 4.6 68.0 4.8

WAIS-R Equivalent 109.9 4.6 109.6 4.5 109.7 4.5
7

a computer-administered, low fidelity work sample

that required the subject to control a predetermined

number of aircraft within a simplified synthetic airspace, directing them to their destinations according

to a small set of rules. A computer-based instruction

module provided standardized training. Twenty-two

practice scenarios and seven test scenarios were administered. The scenarios escalated in complexity by

increasing the number of aircraft and changing the

duration of the scenarios. The practice problems

ranged from 11 aircraft in 16 minutes to 45 aircraft

in 28 minutes. The test scenarios all involved 45

aircraft in 27-28 minutes. The sequence of the practice and test problems was modified from the Eurotest

version (Broach, Enos, & Moore, 1994). During the

practice sessions, two additional practice scenarios

were added by duplicating scenario 10 and 12 to

provide an 8-hour synthetic work day for 3 days. The

seven test scenarios were administered in the following order: EX1, EX4, EX2, EX5, EX3 EX6, and EX1.

Measures included from the ATST were in two

categories: errors and delays. Errors included incorrect landing speed and level, incorrect gate speed and

level, destination errors, separation errors, and crashes.

All of these added together were analyzed as Total

Errors. The errors were divided into Procedural and

Safety Errors. Safety errors included crashes and

separation errors. Procedural errors included incorrect landing speed and level, incorrect gate speed and

level, and destination errors. Delays were a measure

of time (in minutes) required to handle the aircraft.

Handoff Delays were computed from the time an

aircraft, requiring acceptance of the handoff, was

presented on the screen to the time the controller

accepted the handoff. For Enroute Delays, the system

computed the difference between the actual time to

reach destination for each aircraft and the time required if the aircraft had flown the optimum flight

path. Total Delays were the sum of Handoff and

Enroute Delays.

The modified Bakan test had two components: a

stimuli comparison and an estimation task. A sequence of three-digit numbers was presented on a

CRT screen every 1.5 seconds for 30 minutes. When

a three-digit number was repeated in sequence, depressing the space bar on the keyboard indicated a

correct response. In addition to the three-digit stimuli,

a single digit or letter was presented simultaneously

to the right of the three-digit stimuli. At the end of

each 5-minute block of trials, subjects were required

to indicate the proportion of numbers to letters

presented during that block. Six blocks of 200 trials

were presented in each session, which lasted approximately 30 minutes.

Sleep EEG measures. Polysomnography was recorded using Oxford Instruments ambulatory

Medilog electroencephalograph (EEG). Ag-AgCl

Grass electrodes were fixed to the scalp with collodion, and plugged into the Medilog unit. Polysomnography records were recorded from scalp sites

C3 and C4 with the low-pass filter at 35 and the highpass filter at 0.3. For the electrooculograms (EOGs),

the low-pass filter was set at 5 and the high-pass filter

was 0.003. Electromyograms (EMG) were measured

with the low-pass filter set at 120 and the high-pass

filter set at 1.

Subjective measures. The Stanford Sleepiness Scale

(SSS) (Hoddes, Zarcone, Smythe, Phillips, & Dement, 1973) and the Positive and Negative Affect

Schedule (PANAS) (Watson, Clark, & Tellegen,

1988) were used to assess sleepiness and mood at

various times throughout the protocol. The SSS was

composed of seven statements ranging from “Feeling

active and vital; wide awake” to “Almost in reverie;

sleep onset soon; losing struggle to remain awake.”

The PANAS was composed of 20 adjectives (10

representing positive affect [PA] and 10 representing

negative affect [NA]) and a five point scale ranging

from “Very slightly or not at all” to “Extremely.” A 4-

item sleep quality questionnaire was used to assess

sleep quality in terms of difficulty falling asleep,

depth of sleep, difficulty arising from sleep, and level

of restedness (Cruz & Della Rocco, 1995).

The subjective measures were collected in daily

logbooks. In addition, the logbooks were used to

collect self reports of sleep times, awakenings, physical symptoms, meals, beverages, activities, and comments. The daily logbook was modified from those

developed by the National Aeronautics and Space

Administration (Gander, Myhre, Graeber, Andersen,

& Lauber, 1989).

Activity measures. Activity monitors (AMA 32C,

version 8.6) from Precision Control Design were

used to study the rest/activity cycles of participants.

Rest/activity data were analyzed to document each

participant’s sleep schedule for the 5 days before

coming to the laboratory. The data collected at the

laboratory was used as a secondary measure to the

EEG data for sleep duration and immobility.
8

The activity monitor was an 8-bit (expandable to

16-bit), lithium battery-powered microprocessor with

32 kB of nonvolatile RAM. The battery power was

sufficient for 10-14 days of continuous operation.

The monitor was approximately 44 mm x 33 mm x 13

mm, made of water-resistant metal, and was worn on

the nondominant arm. It contained a piezoelectric

motion sensor and a real-time clock. Depending on

the parameters chosen, the monitor has a recommended operating range of accelerations from 0.3 to

2.0 Gs, however it can handle as much as 10 Gs. The

monitor compares each signal against a threshold of

detection. The activity monitor was used in the

threshold crossing mode. In this mode, a count was

registered for each occurrence of a signal greater than

the threshold of detection. Counts were accumulated

for the duration of the user selected epoch (60 seconds) and were then stored in memory. This mode

provided a measure of frequency of movement. It was

programmed to operate for the duration of the study.

Upon the participants’ arrival and departure from the

laboratory, data were transferred to permanent storage in a personal computer and analyzed off-line.

Procedures

The protocol was reviewed and approved by the

USAARL Human Use and Scientific Review Committees. Subjects were briefed about the study by

CAMI or USAARL staff over the phone, and the

informed consent form was discussed in detail at least

5 days prior to the study. Subjects signed the consent

forms and returned them to CAMI. At least five days

prior to arriving at the USAARL laboratory, participants received and were briefed on how to wear the

Wrist Activity Monitor. Monitors were worn 24-

hours per day for the duration of the study, with the

exception of during showers.

Participants arrived at the laboratory on Sunday

evening and departed on Thursday afternoon. They

completed three day shifts (0700-1500) and one

midnight shift (2300-0700). Up to five subjects

could participate at the same time. A total of nineteen

groups were required to complete data collection.

Upon arrival Sunday evening, subjects checked in

and were oriented to the laboratory. They completed

biographical questionnaires, the Shipley Institute of

Living Scale, and the Digit Span tests. All subjects

were assigned to a semi-private bedroom and shower

area. Subjects were required to retire to their bedrooms at 2230, and lights out was no later than 2300.

Subjects were awakened each morning at 0530. They

were allowed time to shower, dress, and eat breakfast

before the first training session of the day. Naps

during the day were not allowed.

On Monday morning, subjects began training on

the cognitive tasks. Training sessions were administered for the 3 day shifts, with the test sessions

beginning the night of day 3 and ending the morning

of day 4. Table 4 presents the schedule for the

training days.

Following the final training session at 1500 on

Day 3, subjects were allowed to break but not allowed

to nap before the midnight shift. Electrode placement for the midnight shift was initiated at approximately 2100. The night shift began at 2300. Table 5

presents the protocol schedule for the midnight shift.

All groups received a 30-minute break following

the first test session (0030-0100) after which a 30

minute ATST problem was administered to all groups.

Subjects were informed about their napping condition assignments at 0130. At 0145, the 120-minute

nap was initiated. Short Nap subjects were placed on

break at 0130 and in bed by 0300 and awakened by

0345. The No Nap group was placed on break at

Table 4. Study Protocol.

Training Sessions for All Napping Conditions

Training Day 1 Training Day 2 Training Day 3

0700-0830 Orientation 0700-0830 Training 1 0700-0830 Training 1

0830-0900 Break 0830-0900 Break 0830-0900 Break

0900-1030 Training 1 0900-1030 Training 2 0900-1030 Training 2

1030-1100 Break 1030-1100 Break 1030-1100 Break

1100-1230 Training 2 1100-1230 Training 3 1100-1230 Training 3

1230-1330 Lunch 1230-1330 Lunch 1230-1330 Lunch

1330-1500 Training 3 1330-1500 Training 4 1330-1500 Training 4
9

0130 and returned for testing at 0345. During the

break for the Short Nap and No Nap groups, subjects

relaxed in the break area. The subjects were not

allowed to sleep during their break, but were permitted to read, watch television, or interact with other

subjects during the break time. Test Session 2 was

administered within 5 minutes after awakening from

the nap, but no later than 0345. Subjects in all the

conditions received a 15-minute break after Test

Session 2 (0515-0530). At 0530, the final test session

began. Upon completing Session 3, subjects were

allowed to eat a light meal and return to their bedrooms to sleep/rest for five hours. After a lunch break,

subjects completed a final ATST scenario from 1330

to 1400. Finally, subjects were debriefed and allowed

to return to their homes.

The investigators controlled timing and content

of meals. Breakfast, lunch, and dinner were scheduled at 0600, 1230, and 1800, respectively, during

the day shifts. A snack before the first test session on

the midnight shift was allowed at 2200. The subjects

were allowed to consume light snacks during scheduled breaks. No foods or beverages were allowed

during the testing period. Only light snacks and noncaffeinated beverages were allowed at any time during

the night shift. One caffeinated beverage was allowed

with breakfast if the subject normally consumed

caffeine. No alcohol consumption was allowed

throughout the laboratory protocol. All food and

drink intake was recorded in the daily log book.

Cognitive performance. During orientation, subjects completed the computer-based instruction on

the ATST and four practice sessions. They were also

instructed on the Bakan. Subjects were provided

feedback about performance after each training test.

Each session on the computerized test battery lasted

approximately 90 minutes and consisted of two 27 or

28-minute ATST scenarios, separated by 30 minutes

of the Bakan. The participants were given a total of 11

practice sessions on the three day shifts and three full

test sessions on the night shift. A single ATST problem was administered just prior to notifying participants about their napping conditions. A final session

was administered after a rest period following the

night shift to diminish the potential end-of-study

effect on performance.

Sleep EEG. The electrodes were attached the

evening before the second night of sleep. Subjects

slept with sensors attached to their scalp beginning

the second night in the laboratory (Monday night).

To attach the EEG electrodes, the scalp was measured

according to the International 10-20 system for proper

location of sites C3 and C4. Each placement site was

rubbed with acetone to clean the scalp. Electrodes

were placed on the site and secured with collodion.

After each electrode was secured, it was filled with

electrode paste. All impedances were maintained below 7-10 Kohms. EEG electrodes were referenced to

the contralateral mastoid. The EOG and EMG sites

were cleaned with acetone and the electrodes were

filled with electrode cream, placed on the cleaned

sites, and secured with tape. EOG was recorded from

electrodes placed approximately 2 cm below the outer

canthus of the left eye and 2 cm above the outer

canthus of the right eye. Both eye electrodes were

referenced to the left mastoid. Muscle tone was

measured by submental electrodes. Only the EOG

and EMG electrodes were removed each morning.

Table 5. Midnight Shift Schedule for Each Nap Condition.

TIME No Nap Group Short Nap Group Long Nap Group

2300-0030 ATST-Bakan-ATST ATST-Bakan-ATST ATST-Bakan-ATST

0030-0100 Break Break Break

0100-0130 ATST ATST ATST

0130-0145 Break Break Break

0145-0300 Break Break Nap

0300-0345 Break Nap Nap

0345-0520 ATST-Bakan-ATST ATST-Bakan-ATST ATST-Bakan-ATST

0520-0530 Break Break Break

0530-0700 ATST-Bakan-ATST ATST-Bakan-ATST ATST-Bakan-ATST

0700-1200 Sleep Sleep Sleep

1300-1330 ATST ATST ATST
10

These were reattached before bedtimes each night,

before testing on day 3, and before the midnight

shift. The stages of sleep were determined by guidelines set forth by Rechtschaffen and Kales (1968).

Subjective measures. Subjects rated sleep quality

upon arising each day and upon arising from the nap.

The PANAS was administered upon arising, at the

beginning of the workday, at the end of the workday,

and at bedtime. The SSS was administered during

each workday including the night shift before and

after each test battery session.

Data Analysis

Sleep EEG and Wrist Activity Monitor measures.

Data were used to: 1) assess sleep quality before the

night shift, 2) determine the quality of the nap and

ensure that the No Nap subjects did not sleep, 3)

determine sleep stage at the termination of the nap

and 4) to examine alertness during performance on

the last day shift and the night shift. The EEG data

will be reported elsewhere; however, nap data were

examined to ensure that each of the participants

actually met napping condition criteria. Data from

the wrist activity monitors were used to determine

the subject’s activity before coming to the laboratory

and were analyzed to determine sleep during the nap

when EEG data were unavailable.

Records of participants in the Short Nap condition

were scored for sleep from approximately 0245-0345,

while records from subjects in the Long and No Nap

conditions were scored from 0145-0345. EEG records

were visually examined to identify and determine the

time of day for analysis. The actual beginning of the

time period varied from subject to subject because it was

set to the time in which EEG and EMG channels

exhibited a clear reduction in muscle activity as the

subject sat on the bed and lay down to sleep. Sleep stages

were identified using Rechtshaffen and Kales (1968) as

implemented in the Oxford polysomnography analysis

software. Five records could not be scored automatically

because of faults in the electromagnetic storage medium. In these cases an experienced polysomnography

scorer visually scored the records using Rechtshaffen

and Kales’ guidelines. Records of subjects in the No Nap

condition were screened for evidence of sleep of 30 or

more minutes in duration. Two subjects’ records were

found to meet this criteria, but no other records were

found to have evidence of sleep. Data from subjects

which exhibited sleep episodes lasting 30 or more minutes were excluded from the analysis of performance.

Study design and analyses. The experimental design was a 3 (Nap Condition) x 2 (Gender) x 3

(Session) mixed factorial design with repeated measures. Data from the three Test Sessions on the

midnight shift were analyzed using SPSS version 7.5

for Windows General Linear Model for repeated

measures. Pillai’s Trace multivariate analysis of variance results were used to test the within-subjects

effects. Significant interaction and main effects were

analyzed with post hoc multiple comparisons for

between groups and within subjects per Toothaker

(1991). Comparisons of the repeated factor(s), either

within groups or collapsed over groups, were conducted using two correlated-sample t-tests and Dunn

critical values (CV). Between-group comparisons,

either within Session or collapsed over Session, were

conducted based on the t-statistics, tG and tG@T,

where G equals group and T equals time, using Tukey

CVs as described by Toothaker.

Cognitive performance measures. Analyses and

handling of missing data were conducted for the

ATST and Bakan as follows:

ATST — A total of 7 ATST scenarios were administered on the midnight shift. Only those scenarios

that were included in a complete Session of ATSTBakan-ATST were analyzed here. The third scenario

was administered as a single problem prior to the

napping conditions being announced and was not

included in these analyses. A 3 (Nap Condition) X 2

(Gender) X 3 (Session) X 2 (Pre-Post Bakan) factorial

design with repeated measures on Session and Prepost was analyzed for Enroute Delay (ERD), Handoff

Delay (HOD), Total Delay (TD), Procedural Errors

(PE), Safety Errors (SE) and Total Errors (TE) for

each of six ATST scenarios on the midnight shift.

The ATST scenarios before and after each Bakan task

were considered Pre- and Post-Bakan in the model.

Examination of the ATST data revealed 4 subjects

with data consistently identified as outliers on a

number of ATST measures. These subjects were

excluded from the ATST analyses. The number of

subjects in each group for analyses of the Error

measures were as follows: 1) SNM, n=9; 2) SNF,

n=10; 3) LNM, n=9; 4) LNF, n=9; 5) NNM, n=7;

and 6) NNF, n=11. Data were lost for the Delay times

(Enroute, Handoff and Total) for an additional 4

subjects. Because this occurred for all of the scenarios

on the night shift, they were dropped from the

analyses and no attempt was made to estimate values.

The remaining number of subjects in each group for
11

analyses of the Delay times were as follows: 1) SNM,

n=8; 2) SNF, n=10; 3) LNM, n=8; 4) LNF, n=9; 5)

NNM, n=7; and 6) NNF, n=9.

Bakan — A 3 (Nap Condition) X 2 (Gender) X 3

(Session) factorial design with repeated measures on

Session was analyzed for 1) Correct Responses, 2)

False Responses, and 3) Number/Letter Ratio Estimation. A total of three 30-minute Bakan Sessions

were administered and analyzed for the midnight

shift. To investigate the effects of time on task, each

Bakan Session was broken down into six 5-minute

blocks, resulting in a full model with two betweensubjects factors (Nap Condition and Session) and

two within-subjects factors (Session and Block).

Planned multiple comparisons examined changes

within and between groups for each Session.

Files for two subjects’ performance data on the

Bakan were corrupted, and therefore lost for the

analyses. This included the second midnight shift

session for one subject in the NNM group and the

first three of the five-minute blocks during the first

midnight shift session for one subject in the NNF

group. Both cases were handled by substituting the

missing values with the NNM and NNF group averages for those particular data points, respectively.

Subjective ratings. Analyses were conducted for

three subjective measures, Sleep Quality Ratings

(SQR), the PANAS, and the Stanford Sleepiness

Scale (SSS). Subjective ratings of the four sleep quality dimensions and for the Overall Sleep Quality

score were analyzed for the nap on the midnight shift

in a 3 (Nap Condition) x 2 (Gender) factorial model.

For the scores on the PANAS, subjective ratings of

NA and PA for the beginning of the midnight shift

and the end of the midnight shift were analyzed in a

3 (Nap Condition) x 2 (Gender) x 2 (Time) model

with repeated measures on Time. One subject in the

LNM group failed to respond to one adjective on the

PANAS at the beginning of the midnight shift. The

missing rating was replaced with the mean of all of the

subject’s own ratings for that adjective. SSS subjective

ratings of sleepiness over the course of the midnight

shift were analyzed in a 3 (Nap Condition) x 2

(Gender) x 3 (Session) x 2 (Pre-Post) model with

repeated measures on Session and Pre-Post. A total of

seven subjects failed to respond to the SSS questionnaire following the last work session of the midnight

shift (1 NNF, 1 SNF, 1 SNM, 2 LNM, and 2 LNF).

Scores were replaced for these individuals by group

mean substitution.

RESULTS

EEG Analyses

Two NNM subjects were excluded from these analyses because they exhibited one sleep episode for a period

of 30 minutes or greater during their break on the

midnight shift. The remaining No Nap subjects did not

exhibit sleep episodes during the break. Data from

subjects in both Nap Conditions revealed sleep episodes

consistent with the assigned Nap Condition.

Air Traffic Scenarios Test (ATST) Results

Results from this low fidelity air traffic control

simulation were reported for six measures from the

ATST: Enroute Delay (ERD), Handoff Delay

(HOD), Total Delay (TD), Safety Errors (SE), Procedural Errors (PE), and Total Errors (TE).

Delay time. Analyses revealed significant Session

by Nap Condition interactions for both HOD,

F(4,90)=3.03, p=.022, and ERD, F(4,90)=2.51,

p=.047. There were no significant findings for Total

Delay or for Gender on any of the Delay measures.

Tables 6 and 7 and Figures 1 and 2 present descriptive

information for HOD and ERD by Nap Condition

and Session, respectively, collapsed across Gender.

Multiple comparisons to investigate differences

between Nap Conditions at each level of Session

revealed no significant differences in HOD. The No

Nap group (M=45.7) was found to have a significantly higher ERD on the last scenario at the end of

the midnight shift than the Short Nap group

(M=35.3), t=2.03, p<.05.

ATST errors. Results of the analyses of the three

error measures — SE, PE, and TE — revealed no

effects of Nap Condition. However, a significant

interaction of Session by Gender was present for SE,

F(2,48)=4.19, p=.021. Table 8 and Figure 3 present

descriptive statistics for SE by Gender and Session.

Bakan Results

The Bakan provided a measure of vigilance. Three

measures on the Bakan <Bullet>— Correct Responses,

False Responses, and Number/Letter Ratio Estimation

— were analyzed. Results from the three sessions on the

night shift were as follows:

Correct responses. Results of the analysis revealed a

significant interaction for Nap Condition by Session,

F(4.106)=5.097, p=.001. Table 9 and Figure 4 present

descriptive information for Correct Responses by Nap

Condition and Session.
12

Table 6. Handoff Delay on the ATST Scenarios by Session and Nap Condition.

Session

12 3

Pre Post Pre Post Pre Post

No Nap Group (n=16)

mean 10.0 9.3 9.2 8.9 10.7 10.5

sd 4.1 3.1 3.3 2.4 4.8 4.4

Short Nap Group (n=18)

mean 8.4 8.6 9.3 9.3 8.9 9.6

sd 1.5 1.8 2.3 4.2 2.4 6.0

Long Nap Group (n=17)

mean 9.6 8.8 10.1 8.3 9.6 9.1

sd 2.1 1.5 2.7 1.2 1.9 2.5

Table 7. Enroute Delay on the ATST Scenarios by Nap Condition and Session.

Session

123

Pre Post Pre Post Pre Post

No Nap Group (n=16)

mean 44.4 37.6 40.6 45.3 45.0 45.7

sd 16.1 12.5 14.0 22.3 18.5 15.9

Short Nap Group (n=18)

mean 40.5 33.5 37.5 38.3 39.8 35.3

sd 16.4 11.3 14.1 17.9 23.5 11.7

Long Nap Group (n=17)

mean 48.3 36.8 42.2 38.7 41.6 39.9

sd 16.5 7.6 12.2 8.3 13.9 10.1
13

Figure 1. Handoff Delay Times by Nap Condition and Session.

ATST Hand-off Delay

Session by Nap Condition

6

7

8

9

10

11

12

pre post pre post pre post

No Nap Short Nap Long Nap

Session 1 Session 2 Session 3

Figure 2. Enroute Delay Times by Nap Condition and Session.

ATST En Route Delay Time

Session by Nap Condition

30

35

40

45

50

pre post pre post pre post

No Nap Short Nap Long Nap

Session 1 Session 2 Session 3
14

Figure 3. ATST Safety Errors by Gender and Session.

Multiple comparisons to investigate the differences between Gender at each level of Session

revealed that the males (M=0.4) had 1.2 fewer errors on average than the females (M =1.6) in

the last scenario of the midnight shift, t=3.09, p<.05.

ATST Safety Errors

Session by Gender

0

0.5

1

1.5

2

pre post pre post pre post

Session 2

Males Females

Session 1 Session 3

Table 8. Safety Errors on the ATST Scenarios by Gender and Session.

Session

1 23

Pre Post Pre Post Pre Post

Males (n=25)

mean 0.8 1.2 1.9 1.0 1.4 0.4

sd 1.9 1.2 2.1 1.6 1.7 1.0

Females (n=30)

mean 1.3 0.9 1.5 0.8 1.4 1.6

sd 2.0 1.2 1.8 1.0 1.6 2.1

Table 9. Correct Responses on the Bakan by Nap Condition and Session.

Session 1 Session 2 Session 3

No Nap (n=19)

mean 125.8 109.1 96.5

sd 4.5 17.1 28.3

Short Nap (n=20)

mean 118.7 118.1 109.7

sd 14.7 11.8 19.0

Long Nap (n=20)

mean 125.1 123.4 115.7

sd 7.1 7.9 16.9
15

Multiple comparisons to investigate cell mean

differences within each level of Session and Nap

Condition revealed a pattern of decline in performance in all of the nap groups. The No Nap group

demonstrated a consistent, significant pattern of decline at each Session from M=125.8 in Session 1 to

M=96.5 in Session 3. Within both of the Nap Conditions, only the performance on the third Session

was found to be significantly lower than Sessions 1

and 2. Thus, both Nap Conditions protected performance on Correct Responses in the Session following

the nap, but some decrement was observed in the

final Session of the midnight shift. Results of the

multiple comparisons were as follows:

No Nap Group (CV(18,3)=2.64):

•Session 1 was significantly higher than Session 2,

t(18)=4.46, p<.05

•Session 1 was significantly higher than Session 3,

t(18)=4.67, p<.05

•Session 2 was significantly higher than Session 3,

t(18)=3.16, p<.05

Short Nap Group (CV(19,3)=2.62):

•Session 1 was significantly higher than Session 3,

t(19)=4.30, p<.05

•Session 2 was significantly higher than Session 3,

t(19)=3.93, p<.05

Long Nap Group (CV(19,3)=2.62):

•Session 1 was significantly higher than Session 3,

t(19)=3.05, p<.05

•Session 2 was significantly higher than Session 3,

t(19)=3.15, p<.05

Multiple comparisons between groups at each level

of Session revealed a pattern in which the Long Nap

condition protected performance compared to the

Short Nap and No Nap groups. Results revealed the

following significant differences.

•LN Session 2 was significantly higher than NN

Session 2, t=2.78, p<.05

•LN Session 3 was significantly higher than NN

Session 3, t=2.14, p<.05

•LN Session 3 was significantly higher than SN

Session 3, t=2.57, p<.05

Figure 4. Bakan Correct Responses by Nap Condition and Session.

Bakan Session Total Correct Responses

Nap Condition by Session

90

100

110

120

130

123

Session

No Nap Short Nap Long Nap
16

Figure 5. Bakan False Responses Nap Condition by Session.

Bakan Session Total False Responses

Session by Nap Condition

0

2

4

6

8

10

123

Session

No Nap Short Nap Long Nap

Table 10. False Responses on the Bakan by Nap Condition and Session.

Session 1 Session 2 Session 3

No Nap (n=19)

mean 1.5 4.7 9.0

sd 1.2 4.2 5.9

Short Nap (n=20)

mean 3.0 3.8 5.6

sd 2.8 3.7 5.0

Long Nap (n=20)

mean 2.2 2.0 3.4

sd 1.9 1.9 3.7
17

False responses. Results of the analysis of false

responses revealed a significant Session by Nap Condition interaction, F(4,106)=4.085, p=.004 and a

significant Session by Gender interaction,

F(2,52)=3.425, p=.04. Table 10 and Figure 5 present

descriptive statistics for false responses by Session

and Nap Condition.

Multiple comparison procedures to investigate

cell mean comparisons within each level of Session

and Nap Condition revealed the anticipated pattern

of significant decrement in performance from session

to session across the midnight shift for the No Nap

condition. As with the data for the Short Nap group

on correct responses, performance was protected

during the session following the nap (Session 2), but

some increases in false responses were observed by the

final session of the shift (Session 3). For the SN

group, mean false responses for the first two Sessions

were 3.0 and 3.8, respectively. SN false responses

increased to 5.6 by Session 3. There were no significant increases in false responses in the Long Nap

group revealing protection of performance on false

responses for the entire shift. The results of the

multiple comparisons were as follows:

No Nap Group (CV(18,3)=2.64:

•Session 1 was significantly lower than Session 2,

t(18)=3.68, p<.05

•Session 1 was significantly lower than Session 3,

t(18)=5.85, p<.05

•Session 2 was significantly lower than Session 3,

t(18)=4.49, p<.05

Short Nap Group (CV(19,3)=2.62:

•Session 1 was significantly lower than Session 3,

t(19)=2.80, p<.05

•Session 2 was significantly lower than Session 3,

t(19)=2.67, p<.05

Long Nap Group (CV(19,3)=2.62:

•No significant differences between Sessions.

Multiple comparisons between groups at each level

of Session revealed significant protection of performance for both the Long Nap and Short Nap groups

compared to the No Nap group. Multiple comparisons resulted in the following significant differences.

•LN Session 2 was significantly lower than NN

Session 2, t=2.25, p<.05

•SN Session 3 was significantly lower than NN

Session 3, t=2.81, p<.05

•LN Session 3 was significantly lower than NN

Session 3, t=4.66, p<.05

Table 11 and Figure 6 present descriptive statistics

for false responses related to the significant Session

by Gender interaction.

Multiple comparison procedures to investigate

cell mean comparisons within each level of Gender

and Session revealed a pattern of declining performance across the midnight shift for both males and

females. The females, however, did not show a significant decline until the final Session of the midnight shift.

Males (CV(27,3)=2.56:

•Session 1 was significantly lower than Session 2,

t(27)=2.68, p<.05

•Session 1 was significantly lower than Session 3,

t(27)=4.01, p<.05

•Session 2 was significantly lower than Session 3,

t(27)=3.00, p<.05

Females (CV(30,3)=2.54:

•Session 1 was significantly lower than Session 3,

t(30)=3.91, p<.05

•Session 2 was significantly lower than Session 3,

t(30)=4.70, p<.05

Multiple comparisons between Gender at each

level of Session revealed no significant differences.

Number/Letter Ratio Estimation. Analyses conducted on the Bakan number/letter ratio estimation

task revealed no significant differences.
18

Time on Task. To better understand the protective effects of naps revealed by the previous analyses,

the Bakan data were examined for the changes in

performance with time-on-task within each Bakan

Session. Each 30-minute Bakan session was analyzed

by the six 5-minute blocks for each of the three Bakan

measures (Correct Responses, False Responses, and

Number/Letter Ratio Estimation). The model included two between-subjects factors (Nap Condition

and Session) and two within-subjects factors (Session

Table 11. False Responses on the Bakan by Gender and Session.

Session 1 Session 2 Session 3

Males (n=28)

mean 2.25 3.99 5.43

sd 2.24 3.67 4.09

Females (n=31)

Mean 2.19 3.03 6.48

sd 2.10 3.34 6.29

Figure 6. Bakan False Responses by Gender and Session.

Bakan Session Total False Responses

Session by Gender

0

1

2

3

4

5

6

7

123

Session

Males Females

and Block). Planned comparisons involved examining the changes within Session. Results of the analyses for False Responses and Number/Letter Ratio

Estimation revealed no significant findings for Block.

Correct Responses

Results of this analysis revealed a significant threeway Nap Condition by Session by Block interaction,

F(20,90)=2.59, p=.001. The following section presents results for each Session.
19

Session 1 correct responses. Descriptive statistics

for Session 1 correct responses on the Bakan test by

Nap Condition and Block are presented in Table 12

and Figure 7.

Multiple comparisons within each group, based

on Dunn (n-1, C) and a paired t-test, revealed no

significant differences. Multiple comparisons between

Nap Condition groups revealed that even though the

Short Nap group did not show a significant decline

on the within subject comparisons, they averaged

Figure 7. Bakan Correct Responses for Nap Condition by Block for Session 1.

Bakan Correct Responses (Session 1)

Nap Condition by 5-minute Block

18

19

20

21

22

123456

5-minute Block

No Nap Short Nap Long Nap

Table 12. Bakan Correct Responses for Session 1 by Nap Condition and 5-minute Block.

Block 1 Block 2 Block 3 Block 4 Block 5 Block 6

No Nap

mean 21.2 21.0 21.1 21.2 20.8 20.5

sd 1.0 1.1 1.1 1.5 1.4 1.7

Short Nap

mean 20.8 20.9 19.6 19.7 19.1 18.8

sd 1.2 1.4 2.9 3.7 3.9 4.7

Long Nap

mean 21.6 21.3 20.7 20.4 20.8 20.3

0.6 1.1 3.1 2.1 1.5 1.9

significantly lower Correct Responses than both the

Long Nap and No Nap groups on Block 5 and lower

than the NN on Block 6. The following values were

computed for the multiple comparisons:

•SN Block 5 was significantly lower than NN

Block 5, t=2.08, p,.05

•SN Block 5 was significantly lower than LN Block

5, t=2.15, p<.05

•SN Block 6 was significantly lower than NN

Block 6, t=2.06, p<.05
20

Table 13. Bakan Test Correct Responses for Session 2 by Nap Condition and 5-minute Block.

Block 1 Block 2 Block 3 Block 4 Block 5 Block 6

No Nap

Mean 20.2 19.3 17.5 17.7 17.4 17.0

sd 2.3 3.8 4.2 3.4 2.9 4.9

Short Nap

Mean 21.1 20.8 20.35 19.3 18.3 18.5

sd 1.3 1.5 1.9 2.6 3.4 3.4

Long Nap

Mean 21.2 20.5 20.6 20.6 20.4 20.2

sd 1.1 2.0 1.2 2.1 2.0 2.1

Figure 8. Bakan Correct Responses for Nap Condition by Block for Session 2.

Bakan Correct Responses (Session 2)

Nap Condition by 5-minute Block

16

17

18

19

20

21

22

123456

5-minute Block

No Nap Short Nap Long Nap
21

Session 2 correct responses. Descriptive statistics

for Session 2 correct responses on the Bakan test are

presented in Table 13 and Figure 8.

Multiple comparison procedures to investigate

within Nap Condition cell mean comparisons for

each level of Block in Session 2 revealed the beginning of performance decrements by Block 5 across

the session for the No Nap and Short Nap groups. No

significant differences were found in the Long Nap

group. The following significant differences were

observed:

No Nap Group (CV(18,30)=3.69:

•Block 1 was significantly higher than Block 5,

t(18)=4.35, p<.05

Short Nap Group (CV(19,30)=3.66:

•Block 1 was significantly higher than Block 5,

t(19)=4.15, p,.05

•Block 1 was significantly higher than Block 6,

t(19)=3.92, p<.05

•Block 2 was significantly higher than Block 5,

t(19)=3.89, p<.05

•Block 2 was significantly higher than Block 6,

t(19)=3.79, p<.05

•Block 3 was significantly higher than Block 5,

t(19)=4.23, p<.05

•Block 3 was significantly higher than Block 6,

t(19)=3.75, p<.05

Long Nap Group (CV(19,30)=3.66:

•No significant differences between Blocks.

Multiple comparisons between Nap Conditions

revealed that although the Short Nap group’s performance demonstrated a significant decline across the

Session, they performed better than the NN group at

Block 3. The Long Nap protected performance compared to both the Short Nap and No Nap groups in

the last three blocks of the Session. The following

significant differences were observed:

•SN Block 3 was significantly higher than NN

Block 3, t=3.46, p<.05

•LN Block 3 was significantly higher than NN

Block 3, t=3.70, p<.05

•LN Block 4 was significantly higher than SN

Block 4, t=2.21, p<.05

•LN Block 4 was significantly higher than NN

Block 4, t=3.45, p<.05

•LN Block 5 was significantly higher than SN

Block 5, t=2.65, p<.05

•LN Block 5 was significantly higher than NN

Block 5, t=3.49, p<.05

•LN Block 6 was significantly higher than SN

Block 6, t=2.15, p<.05

•LN Block 6 was significantly higher than NN

Block 6, t=3.83, p<.05
22

Table 14. Bakan Correct Responses for Session 3 by Nap Condition and 5-minute Block.

Block 1 Block 2 Block 3 Block 4 Block 5 Block 6

No Nap

Mean 18.6 17.6 15.5 14.1 15.2 15.4

sd 4.0 4.5 5.9 6.5 4.7 5.4

Short Nap

Mean 19.2 19.1 18.3 18.2 17.8 17.2

sd 3.6 2.9 3.8 3.9 3.7 4.5

Long Nap

Mean 20.7 19.3 19.9 18.8 18.6 18.6

1.8 3.5 3.2 3.6 4.0 3.7

Figure 9. Bakan Correct Responses for Nap Condition by Block for Session 3.

Bakan Correct Responses (Session 3)

Nap Condition by 5-minute Block

12

14

16

18

20

22

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5-minute Block

No Nap Short Nap Long Nap

Session 3 correct responses. Descriptive statistics

for Session 3 correct responses on the Bakan test are

presented in Table 14 and Figure 9.

Multiple comparisons for within Nap Condition

for each level of Block, revealed a pattern suggesting

that both the Long Nap and the Short Nap protected

performance across the entire final session of the

midnight shift. The following significant differences

were found for the within group comparisons:

No Nap Group (CV(18,30)=3.69:

•Block 1 was significantly higher than Block 3,

t(18)=3.76, p<.05

•Block 1 was significantly higher than Block 4,

t(18)=4.62, p<.05

•Block 1 was significantly higher than Block 5,

t(18)=4.32, p<.05

•Block 2 was significantly higher than Block 4,

t(18)=4.51, p<.05

•Block 2 was significantly higher than Block 5,

t(18)=3.83, p<.05

Short Nap Group (CV(19,30)=3.66):

No significant differences between Blocks.
23

Long Nap Group (CV(19,30)=3.66):

No significant differences between Blocks.

Results of the multiple comparisons between Nap

Conditions revealed the following significant differences:

•LN Block 1 was significantly higher than NN

Block 1, t=2.48, p,.05

•LN Block 3 was significantly higher than NN

Block 3, t=5.17, p<.05

•SN Block 3 was significantly higher than NN

Block 3, t=3.32, p<.05

•LN Block 4 was significantly higher than NN

Block 4, t=4.84, p<.05

•SN Block 4 was significantly higher than NN

Block 4, t=5.56, p<.05

•LN Block 5 was significantly higher than NN

Block 5, t=4.06, p<.05

•SN Block 5 was significantly higher than NN

Block 5, t=3.04, p<.05

•LN Block 6 was significantly higher than NN

Block 6, t=3.81, p<.05

•SN Block 6 was significantly higher than NN

Block 6, t=2.07, p,.05

False responses and number/letter ratio estimation. Results of the analyses revealed no interactions

or main effects of the Block factor.

Subjective Measures

The subjective measures included sleep quality,

PANAS mood scale, and Stanford Sleepiness Scale ratings.

Sleep Quality Ratings

To assess the quality of the naps taken on the

midnight shift, sleep quality ratings (SQR) were

compared by Nap Condition and by Gender. Means

and standard deviations for each SQR component

and the overall SQR are presented in Table 15.

The two factor analysis of variance for Nap Condition and Gender revealed no significant effects for

the overall SQR. The analysis resulted in significant

Nap Condition by Gender interactions for two of the

SQR components: 1) Difficulty Arising from Sleep

F(1,36)=4.787, p=.035 and 2) Level of Restedness

F(1,36)=4.954, p=.032.

Table 15. Means and standard deviations for sleep quality ratings by Nap Condition and Gender.

Short Nap (45 min.) Long Nap (120 min.)

male female male female

Difficulty Falling Asleep

mean

sd

4.1

1.5

3.9

1.1

4.1

1.0

4.0

0.8

Depth of Sleep

mean

sd

4.2

1.3

3.8

0.8

4.4

1.0

4.4

0.7

Difficulty Arising From Sleep

mean

sd

3.1

0.9

2.5

1.3

2.6

0.8

3.5

1.3

Level of Restedness

mean

sd

2.7

1.2

1.8

0.8

2.9

0.7

3.3

0.9

Overall Sleep Quality Rating

mean

sd

14.1

3.4

12.0

2.4

14.0

2.4

15.2

2.4
24

Figure 10 illustrates the Nap Condition by Gender

interaction for the sleep quality item, Difficulty Arising from Sleep. The interaction indicates that females in the LN group reported greater difficulty

arising than those in the SN group and that this

pattern was reversed for males. Tests of simple effects,

however, indicated that the differences between Nap

Condition within Gender were not significant.

Figure 11 illustrates the Nap Condition by Gender

interaction for the sleep quality item, Level of

Restedness. Tests of simple effects indicated that the

LN females reported feeling significantly more rested

(M=3.3) than the SN females (M=1.8),

F(1,18)=14.78, p<.001. No differences in restedness

were found between Nap Conditions for the males.

Positive Affect and Negative Affect Scale

(PANAS)

To assess the effect of Nap Condition and Gender

on the positive (PA) and negative affect (NA) ratings

on the PANAS, mood ratings were compared for the

beginning and end of the midnight shift. Means and

standard deviations for PA and NA are presented in

Tables 16 and 17, respectively.

Figure 10. Sleep Quality Rating for Difficulty Arising by Nap Condition and Gender.

Difficulty Arising From Sleep

0

1

2

3

4

5

6

Males Females

Gender

Short Nap Long Nap
25

Figure 11. Sleep Quality Rating for Level of Restedness by Nap Condition and Gender.

Level of Restedness

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Males Females

Gender

Short Nap Long Nap

Table 16. Means and standard deviations for Positive Affect (PA) ratings Before and After the

Midnight Shift by Nap Condition and Gender.

Before Midnight Shift After Midnight Shift

Nap Condition Males Females Males Females

No Nap

mean 24.6 17.0 15.5 11.5

sd 8.8 5.8 8.8 3.1

Short Nap

mean 22.6 16.2 14.6 12.0

sd 9.7 6.5 6.6 3.6

Long Nap

mean 22.9 17.8 19.1 14.3

sd 9.9 6.1 8.4 4.4

Table 17. Means and standard deviations for Negative Affect (NA) ratings Before and After the

Midnight Shift by Nap Condition and Gender.

Before Midnight Shift After Midnight Shift

Nap Condition Males Females Males Females

No Nap

mean 11.8 11.0 12.4 12.5

sd 1.8 2.1 1.9 2.4

Short Nap

mean 10.3 10.8 12.3 13.6

sd 0.7 0.9 2.8 3.6

Long Nap

mean 11.9 10.9 13.0 11.9

sd 3.0 1.6 3.7 2.5
26

A three-factor analysis of variance, with two between-subjects factors (Nap Condition and Gender)

and one within-subjects factor (Time) revealed a

significant main effect for Time on NA, F(1,53)=24.3,

p<.001. Ratings of NA were higher at the end of the

midnight shift (M=12.6) than at the beginning of the

midnight shift (M=11.1). The analysis revealed a

significant Gender by Time interaction for PA,

F(1,53)=4.1, p=.048. Figure 12 illustrates the Gender by Time interaction for PA.

The interaction was further investigated for simple

effects. Results revealed that males rated PA higher than

females both before the midnight shift, t(45.4)=3.07,

p=.004 and after the midnight shift, t(37.8)=2.37,

p=.018. In addition, both males and females rated PA

higher at the beginning of the midnight shift than at the

end of the midnight shift, t(27)=6.153, p<.001 and

t(30)=5.982, p<.001, respectively.

Stanford Sleepiness Scale

A four-factor analysis of variance, with two between-subjects factors (Nap Condition and Gender)

and two within-subjects factors (Session and Prepost Session) revealed a significant three-way interaction for Nap Condition by Session by Pre-post Session, F(4,106)=4.077, p=.004 and a significant Nap

Condition by Gender interaction, F(2,53)=6.801,

p=.002. Table 18 and Figure 13 present descriptive

statistics for SSS.

Multiple comparisons to investigate differences

between ratings within Nap and Gender groups were

conducted in three ways: between all Pre-session

ratings, between all Post-session ratings, and between

Pre and Post ratings for each session. This resulted in

a total of 9 comparisons within each group. Results of

the comparisons were as follows:

No Nap Males (CV(7, 9)=3.95):

•Session 2 Pre was significantly higher than Session 1 Pre, t(7)=5.02, p<.05

•Session 3 Pre was significantly higher than Session 1 Pre, t(7)=8.10, p<.05

•Session 3 Pre was significantly higher than Session 2 Pre, t(7)=5.29, p<.05

•Session 2 Post was significantly higher than Session 1 Post, t(7)=5.29, p<.05

Figure 12. PANAS Positive Affect before and after the midnight shift.

Positive Affect Ratings Before & After the Midnight Shift

0

5

10

15

20

25

30

35

Before Shift After Shift

Males Females
27

Figure 13. Stanford Sleepiness Scale by Nap Condition, Session and Pre-Post.

Stanford Sleepiness Scale Ratings for the Midnight Shift

0

1

2

3

4

5

6

7

Pre Post Pre Post Pre Post

Session 2

NNM NNF SNM SNF LNM LNF

Session 1 Session 3

Table 18. Means and Standard Deviations for Stanford Sleepiness Scale Scores on the Midnight

Shift by Nap Condition and Gender.

Session 1 Session 2 Session 3

Pre Post Pre Post Pre Post

NNM

mean 2.75 3.62 4.38 5.62 5.38 6.38

sd 1.04 0.74 1.19 1.06 0.92 0.92

NNF

mean 2.64 3.36 4.00 5.18 5.09 6.00

sd 0.67 0.92 1.18 1.47 1.14 1.10

SNM

mean 2.50 2.80 3.80 3.30 3.50 4.11

sd 1.35 1.03 1.48 1.34 1.27 1.79

SNF

mean 3.90 4.60 4.90 5.10 4.90 5.89

sd 0.99 0.97 1.10 0.99 1.20 0.99

LNM

mean 2.90 3.30 4.10 3.80 3.40 4.63

sd 1.29 1.49 1.29 1.32 1.35 1.15

LNF

mean 2.80 3.40 3.20 3.80 3.40 5.00

sd 0.63 0.70 0.79 1.14 0.84 1.05
28

•Session 3 Post was significantly higher than Session 1 Post, t(7)=6.67, p<.05

•Session 3 Post was significantly higher than Session 2 Post, t(7)=4.58, p<.05

•Pre and Post comparisons were not significantly

different for any Session.

No Nap Females (CV(10, 9)=3.52):

•Session 2 Pre was significantly higher than Session 1 Pre, t(10)=4.89, p<.05

•Session 3 Pre was significantly higher than Session 1 Pre, t(10)=7.86, p<.05

•Session 3 Pre was significantly higher than Session 2 Pre, t(10)=5.16, p<.05

•Session 2 Post was significantly higher than Session 1 Post, t(10)=4.54, p<.05

•Session 3 Post was significantly higher than Session 1 Post, t(10)=7.25, p<.05

•Session 1 Post was significantly higher than Session 1 Pre, t(10)=3.73, p<.05

•Session 2 Post was significantly higher than Session 2 Pre, t(10)=3.99, p<.05

•Session 3 Post was significantly higher than Session 3 Pre, t(10)=3.63, p<.05

Short Nap Males (CV(9, 9)=3.63:

•No significant differences.

Short Nap Females (CV(9, 9)=3.63:

•Pre-session ratings were not significantly different.

•Session 3 Post was significantly higher than Session 1 Post, t(9)=4.84, p<.05

•Session 3 Post was significantly higher than Session 2 Post, t(9)=3.85, p<.05

•Session 1 Post was significantly higher than Session 1 Pre, t(9)=4.58, p<.05

Long Nap Males (CV(9, 9)=3.63:

•Session 2 Pre was significantly higher than Session 1 Pre, t(9)=3.67, p<.05

•Post-session ratings were not significantly different.

•Pre and Post comparisons were not significantly

different for any Session.

Long Nap Females (CV(9, 9)=3.63:

•Pre-session ratings were not significantly different.

•Session 3 Post was significantly higher than Session 1 Post, t(9)=4.31, p<.05

•Session 3 Post was significantly higher than Session 2 Post, t(9)=6.00, p<.05

•Session 3 Post was significantly higher than Session 3 Pre, t(9)=4.71, p<.05

Multiple comparisons to investigate differences

between Nap and Gender groups within ratings were

conducted on three rating times (Session 1 Pre,

Session 2 Pre, and Session 3 Post) to determine if

differences existed between groups at the beginning

of the shift, immediately following the nap/break,

and at the end of the shift. Results of the comparisons

were as follows:

Session 1 Pre (Beginning of Shift):

•SNF were significantly higher than NNM, t=2.20,

p<.05

•SNF were significantly higher than NNF, t=3.06,

p<.05

•SNF were significantly higher than SNM, t=3.40,

p<.05

•SNF were significantly higher than LNM, t=2.43,

p<.05

•SNF were significantly higher than LNF, t=2.67,

p<.05

Session 2 Pre (Immediately after nap/break):

•SNF were significantly higher than NNF, t=2.18,

p<.05

•SNF were significantly higher than SNM, t=2.67,

p<.05

•SNF were significantly higher than LNF, t=4.12,

p<.05

•LNM were significantly higher than LNF, t=2.18,

p<.05

•NNM were significantly higher than LNF, t=2.26,

p<.05

Session 3 Post (End of Shift):

•NNM were significantly higher than SNM, t=4.34,

p<.05

•NNM were significantly higher than LNM,

t=3.35, p<.05

•NNM were significantly higher than LNF, t=2.64,

p<.05

•NNF were significantly higher than SNM, t=4.58,

p<.05

•NNF were significantly higher than LNM, t=3.32,

p<.05
29

•NNF were significantly higher than LNF, t=2.43,

p<.05

•SNF were significantly higher than SNM, t=4.32,

p<.05

•SNF were significantly higher than LNM, t=3.06,

p<.05

•SNF were significantly higher than LNF, t=2.16,

p<.05

•LNF were significantly higher than SNM, t=2.16,

p<.05

DISCUSSION

The findings from this study revealed that both a

long nap of 2 hours duration and a shorter nap of 45

minutes duration can significantly protect performance during a midnight shift. The long nap, however, resulted in more consistent findings. The results

in this study were most evident in the Bakan vigilance

task and subjective ratings. The findings were important in demonstrating the effectiveness of napping as

a countermeasure to performance decrement and

sleepiness on the midnight shift on tasks requiring

skills and abilities similar to those required in safety

critical jobs such as Air Traffic Control Specialist.

The ATST and Bakan were selected because they

assessed different abilities. The ATST simulated ATC

tasks. The workload was high to simulate a scenario

in which a napping ATCS would be asked to resume

air traffic control duties during high workload condition. The Bakan was selected because it imposed a

boring, low workload, vigilance condition. The Bakan

had been demonstrated to be sensitive to variations in

alertness and sleepiness (Dollins et al., 1993).

The findings from the Bakan revealed the anticipated performance decrement across the midnight

shift in the No Nap group in both Correct Responses

and False Responses. The decrements in the No Nap

group between the first and last Session represented

a decrease of 23% in Correct Responses and an

increase in false responding of 600% from an average

of 1.5 in Session 1 to 9.0 in Session 3. Therefore, the

test was demonstrated in this study to be sensitive to

sustained wakefulness and possibly the circadian

trough in the performance rhythm.

The Long Nap provided the best protection on the

Bakan in this study. Performance on both Correct

Responses and False Responses was better for the

Long Nap group than the No Nap group for both

sessions after the nap. The Long Nap group performed

better than the Short Nap group for Correct Responses in the final Session of the midnight shift.

Examination of the 5-minute Blocks within each 30

minute Session revealed no significant decrements

within any of the sessions for the Long Nap group.

Results from the Short Nap group were less robust in

the protection provided. No consistent significant

differences on Correct Responses were found between the Short Nap group and the No Nap group on

the Session level until the end of the midnight shift.

This difference was revealed by the analysis of Blocks

where the final 3 Blocks were significantly better for

the Short Nap group. A significant decrement in

performance in the final session of the midnight shift

was observed for both the Long Nap and Short Nap

on Correct Responses and for the Short Nap on False

Responses. However, these decrements represented

an 8% decline in Correct Responses for both groups

and less than double the number of False Responses

from an average of 3.0 to an average of 5.6 for the

Short Nap group when Session 1 is compared to

Session 3. This represented substantial protection

compared to the No Nap group.

Results from the ATST revealed that the test was

less sensitive than the Bakan to the sustained wakefulness induced by the protocol in the No Nap group,

the circadian trough expected to affect all groups, or

the napping conditions. The only nap conditionrelated finding was a shorter average Enroute Delay

time for the Short Nap compared to the No Nap

group on the last scenario. There are a number of

factors which may have contributed to the ATST’s

lack of sensitivity to the factors which frequently

induce decrements in performance. First, the ATST

was selected as a quasi-work sample. All of the subjects were active Air Traffic Controllers. Even though

the ATST was a low fidelity simulation, the skills

required to perform the task may have been well

practiced in this sample and were very robust. In

addition, many of the participants were or had been

required to work midnight shifts during their careers

and many may have brought coping strategies to this

study. Second, the ATST scenarios were designed to

present a fairly high workload. The high workload

may have had an alerting effect for all groups and

maintained performance. Third, participants were selected from all types of facilities, from Level 1 FAA

Towers to Level 3 Enroute Centers. Because of differences

in job duties and traffic workload at their facilities,

participants came to the study with a wide variation
30

of skill levels within the air traffic control occupation. Participants from the Level 1 Towers, for example, did not use radar separation on their job; and

they were probably not trained in radar procedures.

In contrast, Enroute controllers use radar separation

procedures daily in their jobs. This difference in skills

may have introduced extraneous variability into these

analyses. Four, the within group comparisons were

confounded with the scenarios. Different problems

were administered for each test scenario. Even though

the scenarios had a similar number of aircraft and

duration, it was not possible to equate the complexity

of scenarios. The best method would be to obtain

normative data for the problems from a large number

of FPL controllers. Such data was unavailable. Therefore, the degree to which scenario complexity and

experimental factors were confounded was not adequately assessed. Finally, even though some ATST

measures, such as Handoff Delays, might appear to

be a measure which would be affected by fatigue

analogous to a reaction time measure, the nature of

controlling air traffic may not be as directly sensitive

to fatigue effects. Individual controllers may have

compensated for the effects of fatigue in a number of

ways in which they controlled the scenario traffic

which were not reflected in the ATST measures in

this study.

It was encouraging that performance on the ATST

failed to demonstrate sensitivity to such factors as

circadian trough, sustained wakefulness, and naps. This

is especially true in light of the decrements on the Bakan.

The ATST with high workload scenarios was selected

for the study to simulate a situation where an ATST who

was napping would be required to arise and immediately

return to the radar to work traffic.

As with the cognitive findings, results of the subjective measures supported the use of naps during the

midnight shift. Specifically, the analysis of sleepiness

ratings across the midnight shift indicated that naps

could result in reduced sleepiness at the end of the

shift. With the exception of the females in the short

nap group (M=3.9), sleepiness was rated similarly by

each of the other groups at the beginning of the shift

(M=2.5 to 2.9). Over the course of the midnight

shift, however, both the males and females in the no

nap conditions rated their sleepiness increasingly

higher so that by the end of the midnight shift, the no

nap groups were significantly more sleepy than males

or females in the long nap group or males in the short

nap group. Females in the short nap group continued

to rate their sleepiness higher than the other napping

condition groups throughout the entire shift.

In addition to lower ratings of sleepiness as a result

of napping, ratings of mood on the PANAS mood

scale were not adversely or differentially affected by

napping condition. Analysis of sleep quality ratings

revealed that participants felt that naps were fairly

easy to obtain. They also indicated that sleep during

the naps was deep. All participants in the napping

conditions found it moderately difficult to arise from

sleep and reported low to moderate feelings of

restedness, with short nap females reporting feeling

the least rested and long nap females feeling the most

rested.

The placement of the naps in this study was

designed to occur just prior to or during the circadian

trough in temperature and performance rhythms

such that performance would be measured during the

“red zone.” Because circadian rhythms were not measured, they could only be implied to result from the

sleep/wake cycle and subsequent exposure to daylight

imposed by the experimental schedule. The Bakan

data for the no nap group would suggest that the

experimental design which included early morning

shifts, combined with a prohibition of napping at any

time induced a significant level of fatigue.

The present study would tend to support the work

of Matsumoto and Harada (1994), which indicated

that a nap taken during a night work period can

alleviate fatigue. Rogers, Spencer, Stone, & Nicholson

(1989), however, found that a 1-hour nap taken at

0200 during a work period had limited beneficial

effects on performance compared to a no nap condition. Dinges and associates (1985) indicated that

naps taken during the circadian troughs led to greater

performance decrements than did naps taken during

the circadian peaks. This study showed post-nap

sleepiness was higher and performance was lower

when subjects were awakened from a nap during the

circadian trough as compared to a nap taken during

the circadian peak. Dinges advocates prophylactic

napping and taking naps before a person’s sleep loss

extends beyond 36 hours. This advice is also applicable for ATCSs or other personnel in safety critical

or aviation-related jobs. These work forces should be

advised to nap prior to arriving at work for a midnight shift.
31

The protection of performance on the Bakan suggests that naps during the midnight shift would be

useful as a countermeasure to performance decrement and sleepiness on the midnight shift during low

workload conditions. From these data, the 2-hour

nap appeared to be more protective. Future studies

should examine a comparison between a prophylactic

nap and a nap during the midnight shift.

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