analyses of the combined scores. Therefore, the
effects of the 2-2-1 schedule on performance on
each individual task measure of speed and accuracy
were presented.

Examination of performance on each measure of
individual tasks revealed a similar pattern of perfor-
mance decrements with the turn-around to the
Night shift. Significant differences were found,
however, in the Active tasks, exclusively. While
Arithmetic performance revealed no significant dif-
ferences due to the shift, both Code Lock and
Target Identification did. Code Lock consisted of
two separate parts: the procedural task of systemati-
cally decoding the series of five letters, and subse-
quent recall 30 seconds later utilizing short-term
memory. Accuracy of decoding the letter sequence
in the procedural part remained intact throughout
the 2-2-1 schedule, although response times were
slowed on the Night shift, particularly during the
third session. Code Lock Recall was the only task to
reveal a hint that age, as well as the first quick-turn-
around in the 2-2-1, might result in performance
decr&ments. The Older group demonstrated decre-
ments in accuracy of Recall on both quick-turn-
around days. The Younger group demonstrated a
decrement in Recall on the Night shift. Response
time was slowed for both the Older and Younger
groups on the Night shift. Finally, Target Identifi-
cation demonstrated decrements in both speed and
accuracy on the Night shift. No significant decre-
ments were observed in any individual measure on
the passive tasks.

The hypothesis that the two quick-turn-arounds
would result in performance deficits was only par-
tially substantiated. There was some evidence, how-
ever, in Code Lock Recall that the quick-turn-arounds
may have differentially affected the Older group.
Performance on the first two days of the final Day
shift week following the 2-2-1 indicated that per-
formance did not require a petiod of recovery. It
should be noted that subjects did complain about
feeling shift-lagged on the first day of the final week,
but the feelings were not reflected in performance.

Performance decrements during the Night shife
for each workload level were investigated through
assessment of the effect on secondary (passive) tasks

under changes in workload by addition of Active
tasks. Results revealed a significant three-way inter-
action of Age x Interval x Session in which the Older
group’s scores were generally lower than the Younger
group’s scores during most intervals in Session 3,
and declined over Session 2 to their lowest levels
during a high workload condition (Interval 6) that
combined the passive tasks with both Code Lock
and Target Identification. Interval scores generally
declined with increased workload. Significant per-
formance decrements occurred, however, during
two moderate workloads. Specifically, performance
on the Passive tasks during Session 3 Interval 2
(when Arithmetic was also Present) was signifi-
cantly lower by approximately 12% than Session 1
Interval 2. In addition, performance decrements of
approximately 8% were found for the Passive tasks
in Interval 5, when Code Lock was also present,
between Session 1 and 2. Examination of perfor-
mance on the Active Tasks by 15-minute intervals
revealed no significant decrements, suggesting that
subjects protected performance on the Active Tasks.

Because of the observed impact on the sleep/wake
cycle over the course of the schedule (Della Rocco
& Cruz, 1995), ic was not surprising to find that the
largest decrement in performance was observed on
the last shift, a night shift. It was notable, however,
that performance during the first 2-hour MTPB
session of the shift was not significantly worse than
performance on the previous day shift. Performance
declined over the course of the Night shift. Such a
pattern would have been predicted by the
chronobiology if subjects were successful at main-
taining a day-orientation with their circadian
thythms. It also suggests that interventions to
improve employee alertness may not be needed
during the first few hours of the night shift, but
become critical during the final two-thirds of the shift.

There was a substantial learning curve for MIPB
performance. Based upon several traditional assess-
ments of asymptotic performance, including the
assessment of differential stability (recommended
by Damos [1989]), we had reported that subjects
attained asymptotic performance by the end of the
first week after 28 hours of practice (Cruz, Della
Rocco, & MacLin, 1993). Assessment of stabiliza-


Table 35

Means and Standard Deviations for Green Warning Lights Percent Correct
Study Day cp | At A2 [D1 b2] oN cp2 | cos] cpa | cps
Session 1

Younger_Mean | 98.2 | 99.8 | 99.3 [ 99.0 | 99.3 | 100.0 | 100.0 99.6 | 100.0 | 99.2
SD} 46 0.8 23 16 2.3 0.0 0.0 1.3 0.0 2.6
Older Mean | 96.6 | 96.4 | 97.9 | 99.0 | 98.0 99.7 | 99.1 | 99.5 99.1 | 100.0
SD] 28 48 27 2.2 3.8 1.0 21 1.5 2.0 0.0

Session 1 Mean | 97.4 | 98.1 [98.6 | 99.0 | 986 | 99.8 99.5 | 99.6 | 99.6 99.6

SD} 3.8 3.8 2.5 1.9 3.1 7 15 1.4 1,5 1.9

Session 2
Younger_Mean | 98.1 | 100.0 | 985 | 99.4 | 985 | 100.0 99.6 | 98.4 | 96.8 | 99.4
SD| 3.1 0.0 3.1 2.0 47 0.0 1.3 49 9.0 2.0

Older Mean | 99.2 98.2 | 95.7 | 98.3 | 99.4 | 98.4 | 993 | 986 | 99.4 | 995
sD 1.8 3.2 6.6 2.7 2.0 2.6 1.5 3.7 2.0 1.5

Session 2 Mean | 98.6 | 99.1 [97.1 | 98.9 | 98.9 | 992 99.5 | 98.5 | 98.1 99.4
SD] 2.5 2.4 5.3 2.4 3.6 1.9 1.4 4.3 6.5 17

Session 3
Younger Mean} 99.3 | 99.7 | 99.6 | 100.0 | 98.1 99.1 100.0 | 98.4 99.8 99.6

sD 2.3 1.0 1.3 0.0 6.0 2.8 0.0 49 0.8 13

Older Mean |_ 96.5 97.4 | 98.3 97.7 | 99.8 | 95.7 99.1 | 98.5 99.8 99.6
sD 41 3.7 3.8 3.3 0.8 63 2.8 4.0 0.6 1.3

Session 3 Mean | 97.9 | 98.6 | 989 | 98.9 | 98.9 | 974 | 996 98.5 | 99.8 | 99.6
SD] 3.5 2.9 2.8 2.5 43 5.0 2.0 4.4 0.7 1.3

Table 36
MANOVA Summary Table for Green Warning Lights Percent Correct
Degrees of Sums of Squares | Mean Squares
Source of Variation Freedom F
[Age 1 87.33 87.33 NS.
Between Subjects 18 881.30 48.96
Day of Shift 9 136.38 15.15 N.S.
| Age by Day 9 154.89 17.21 N.S.
Within Subjects 162 1510.42 9.32
Session 2 6.25 3.13 N.S.
Age by Session 2 19.15 9.58 NS.
Within Subjects 36 $86.33 16.29
Day by Session 18 173.96 9.66 N.S.
Age by Day by Session 18 129.38 7.19 N.S.
Within Subjects 324 2108.13 6.51
*p<.05
**p<.001



ue

i

Table 27
Means and Standard Deviations for Probability Meters Percent Correct
Study Day cpt Al A2 D1 b2 N Cb2 | CbD3 | CD4 CD5
Session 1
Younger _Mean| 94.1 | 95.1! 97.0] 95.1] 965] 96.0| 96.2] 95.3 96.0 95.8
SD 9.2 7.6 49 8.8 75 4.0 5.3 9.0 8.3 8.8
Older Mean] 945] 909| 916] 95.9] 943] 939| 943} 928] 95.1 93.4
SD|_ 52|{ 97/118] 55] 98] 11.0] 105{[ 10.4 9.0 12.9
Session1 Mean | 94.3 | 93.0 | 94.3] 95.5] 95.4] 94.9| 95.3] 94.1 95.6 94.6
sp] 7.3] 88{ 92] 71] 86] 81[ 82] 96 84] 10.8
Session 2
Younger_Mean| 96.5| 97.3] 97.7] 97.2| 94.7{ 9491 953] 95.3[ 91.3] 948
sD 67 4.2 42 5.3 9.5 8.1 6.2 83 14.5 8.2
Older Mean |_93.1 | 948] 92.5} 944] 93.31 91.0] 94.0| 926 95.5 93.5
SD|_55| 671 941 99/ 81] 169] 122} 118[ 10.6 114
Session 2 Mean| 948]| 96.0] 95.1] 95.8| 94.0] 93.0| 946] 93.9 93.4 94.2
sp|_ 62| 56| 76] 79| 87| 131[ 94] 100[ 126 9.5
Session 3
Younger Mean | _ 95.9 | 97.3] 98.3] 95.9] 95.5 | 923] 96.4| 94.1 95.4 93.7
so| 44] 29] 34] 74] 85] 107[ 66]/ 136 92] 10.8
Older__—Mean| 93.6] 93.6] 93.1 | 94.0] 929| 88.1[ 938[ 945] 95.2] 93.7
sD. 7.2 6.9] 122] 119] 12.0] 183] 100] 12.3 10.6 15.2
Session3 Mean| 94.8| 95.5| 95.7| 949| 942] 90.2[ 95.1[ 943][ 95.3[ 93.7
so{ 60] 55] 91} 97[ 102] 147/] 84] 126 97[ 128
Table 28
MANOVA Summary Table. for Probability Meters Percent Correct
Degrees of Sums of Squares | Mean Squares
Source of Variation Freedom F
[ Age 1 663.58 663.58 | ONS.
Between Subjects 18 38923.65 2162.42
Day of Study 9 306.88. 34.10 N.S.
[ Age by Day 9 381.09 42.34 NS.
Within Subjects 162 5835.53 36.02
Session 2 10.38 5.19 N.S.
|_ Age by Session 2 1.26 63 N.S.
Within Subjects. 36 612.58 17.02
Day by Session 18 444.29 24.68 41.90"
| Age by Day by Session 18 224.36 12.46 N.S.
Within Subjects 324 4213.61 13.00
*p<.05
**p<.001

A-14



Table 44

MANOVA Summary Table for Critical Tracking

Degrees of Sums of Squares | Mean Squares
Source of Variation Freedom F
Age 1 40 40 N.S.
Between Subjects 18 129.54 7.20
Day of Study J 24.71 2.75 17.7**
| Age by Day 9 95 VW NS.
Within Subjects. 162 25.13 16
Session 1 02 02 N.S.
| Age by Session 1 .23 .23 N.S.
Within Subjects 18 3.40 19
Day by Session 9 2.36 26 2.91"
| Age by Day by Session 9 2.49 28 3.08"
Within Subjects 162 14.56 09
*p<.05
**p<.001

A-23



Workload data were examined for each of the six
15-minute intervals among Sessions of the Night
shift utilizing a 2 (Age) x 3 (Session) x 6 (Interval)
tepeated measures model for the Passive and Active
Composite Scores. Planned comparisons for Session
x Interval interactions resulted in a total of 16 with
18 degrees of freedom. The uninterpolated Dunn’s
critical value was 3.62 (p<.05).

Critical tracking data analyzed for this paper
investigated the changes in performance between
the first session of the day and the last. This resulted
in a 2 (Age Group) x 10 (Day) x 2 (Session) mixed
model where age represented the between-subjects
factor, and Day and Pre-Post work session assess-
ments represented the repeated measures factors.
Planned comparisons included: 1) Daily Pre-Post
assessments from CD1, through the 2-2-1, to CD2;
2) CD1, day shift, Pre-workday assessments to each
day of the 2-2-1 as well as to CD2 Pre-workday
assessments; and 3) CD1 Post-workday assessments
to each day of the 2-2-1 as well as to CD2 Post-
workday assessments. This resulted in a total of 19
plannéd comparisons with 18 df. An uninterpolated
Dunn's critical value of 3.62 for 20 comparisons
and 15 df was used.

RESULTS

MTPB performance data were analyzed on three
levels to investigate changes due to the shift work
schedules in this study: 1) M7PB composite scores,
standardized for each task for each two-hour session
and combined into three composites for Total (all
tasks), Passive (green warning lights, red warning
lights, probability meters) and Active tasks (arith-
metic, target identification, code lock), 2) Indi-
vidual MTPB task raw scores, and 3) 15-minute
intervals for secondary (passive) tasks as a method
for examining the effects of workload. All results
tables and figures can be found in Appendices A and
B, respectively.

MTPB Composite Scores
This section presents the results of analyses of the
MTPB composite scores. Three composite scores

13

were computed from the standardized task scores.
The Total Composite Score included all six tasks.
The Active Composite Score included the active
tasks (Arithmetic, Target ID, and Code Lock). The
Passive Composite Score included the passive tasks
(Red Warning Lights, Green Warning Lights, and
Probability Meters). Higher composite scores indi-
cate better performance.

Total Composite Scores. Figure 1 and Table 5
present descriptive statistics for the Total Compos-
ite Scores. Table 6 presents the MANOVA sum-
mary table for Total Composite Scores.

The results of the 2 x 10 x 3 MANOVA revealed
significant interactions for 1) Age by Day, E(9, 162)
= 4.15, p<.01, and 2) Day by Session, F(18, 324)
=2.76, p<.01, as well as a significant main effect for
Day of the study, E(9, 162) = 4.60, p<.01. There
was no significant main effect of Age Group. Mul-
tiple comparisons, computed per the planned com-
parisons for Total Composite Scores, revealed no
significant differences between Days, Sessions or
Age that resulted from the 2-2-1 shift schedule.

Post hoc comparisons on Day revealed evidence
that learning occurred well into the 2-2-1 shift
work week. The performance mean of 486 for CD1
was significantly lower than the mean of 502 for day
A2, (19) = 4.15, p<.05, and the mean of 507 for
day A3, (19) = -3.95, p<.05. The mean for day Al
(M = 494) was significantly lower than the mean for
day D1 (M = 507), £(19) = 3.93, p<.05. These
findings demonstrated that performance improved
significantly into the middle of the 2-2-1 schedule,
through approximately 46 hours of practice. These
comparisons were computed for the Total Compos-
ite scores to demonstrate the degree to which learn-
ing continued into the 2-2-1 week. Further post hoc
analyses for learning effects on the other MTPB mea-
sures were not computed here, because they were
beyond the scope of this report.

Of final note, although not within the planned
comparisons of the effects of the 2-2-1, a decline in
the Total Composite Scores of the Younger group
can be observed in Figure 1 (and Table 5) for
Session 2 of CD4. This was due to one Younger
subject falling asleep for 10 minutes during Interval 6.


Green Warning Lights

Younger ¢ YoungSD -*-Older 4 Older SD J

108

100 | -

Percent Correct

64
Session 123123123123123123123123123123
Day CDi | Al A2 D1 D2 N \" CcD3 CD4 CDS

Days1 2-2-1 Days2

Figure 16. Means and standard deviations for Green Warning Lights
Percent Correct by Age group by Session from day CD1 (week 2) to day
CD5 (week 4).

Green Warning Lights

‘*Younger * YoungSD -+Older 4 Older SD J

Response Time (Seconds)

0
Session1 23123123123123123123123123123

Day cor AL A2 Di D2 N | CD2 CD3 CD4 CDs
Days! 224 Days2

Figure 17. Means and standard deviations for Green Warning Lights Response
Times by Age group by Session from day CD1 (week 2) to day CD5 (week 4).

B-l1



Probability Meters

Younger ¢ YoungSD Older 4 Older SD j

108
104
100
96
92
88
84
80
76
72
68
64
Session 123123123123123123123123123123
Day D1 Al A2 D1 D2 N ||CD2 CD3 CD4 CD5
Daysi | 2-2-1 | Day .
Figure 12. Means and standard deviations for Probability Meters Percent
Correct by Age group by Session from day CD1 (week 2) to day CD5 (week 4).

Percent Correct

Probability Meters

Younger * Young SD --Older 4 Older SD I

Response Time (Seconds)

Session 123123123123123123123123123123

Day CDi]| At A2 D1 D2 N {]}CD2 CD38 CD4 CDS
Days1 | | 2-2-1 | | Days2

Figure 13. Means and standard deviations for Probability Meters Response

Time by Age group by Session from day CD1 (week 2) to day CD5 (week 4).

B-9



Code Lock Recall

Younger ¢ Young SD -* Older 4 Older SD j

108
104
100

96
92
88
84

80
76
72
Ce

Percent Correct

64
Session 123123123123123123123123123123
Day D1 | Ai A2 Di D2 N \°~ CD3 CD4 cD5
2-2-

Days1 1 Days2

Figure 8. Means and standard deviations for Code Lock Recall Percent
Correct by Age group by Session from day CD1 (week 2) to day CD5 (week 4).

Code Lock Recall

® Younger * YoungSD -*-Older 4 Older SD J

Response Time (Seconds)

0

Session 123123123123123123123123123123

Day D1 | Al A212 SN || CD3 CD4 CD5
Days1 2-2-1 Days2

Figure 9. Means and standard deviations for Code Lock Recall Response
Time by Age group by Session from day CD1 (week 2) to day CD5 (week 4).

B-7



Knowles, W. (1963). Operator loading tasks. Human
Factors, 5: 155-161.

Melton, C. (1982). Physiological stress in air traffic
controllers: A review (DOT/FAA/AM-82-17).
Washington, DC: Federal Aviation Administra-
tion, Office of Aviation Medicine.

Mertens, H., McKenzie, J., & Higgins, E. (1983).
Some effects of smoking withdrawal on complex
performance and physiological responses (DOT!
FAA/AM-83-4). Washington, DC: Federal Avia-
tion Administration, Office of Aviation Medi-
cine.

Monk, T. (1990). Shiftworker performance. In A.
Scott (Ed.) Occupational Medicine: State of the Art
Reviews, 5 (2): 183-198. Philadelphia, PA:
Hanley & Belfus.

Monk, T., Moline, M., & Graeber, R. (1988). Induc-
ing jet lag in the laboratory: Patterns of adjust-
ment to an acute shift in routine. Aviation, Space,
and Environmental Medicine, 59 (Aug.) : 703-
710.

Price, W. & Holley, D. (1990). Shiftwork and safety

“« in aviation. In A. Scott (Ed.), Occupational Medi-

cine: State of the Art Reviews, 5 (2): 343-377.
Philadelphia, PA: Hanley & Belfus.

23

Rutenfranz, J., Aschoff, J., 8& Mann, H. (1972). The
effects of cumulative sleep deficit, duration of
preceding sleep period and body-temperature
on multiple choice reaction time task. In W.
Colquhoun (Ed.), Aspects of human officiency,
(pp. 217-229). London: English Universities
Press.

Schroeder, D., Rosa, R., 8 Witt, L. (1995). Some
Effects of 8- vs, 10-hour work schedules on the test
performancelalertness of air traffic control specialists
(DOT/FAA/AM-95/32). Washington, DC: Fed-
eral Aviation Administration, Office of Aviation
Medicine.

Smith, J. & Jex, H. (1986). Operation manual critical
task tester MK 10 (Working paper No. 431—
IR). Hawthorne, CA: Systems Technology, Inc.

Taub, J. & Berger, R. (1973). Performance and mood
following variations in the length and timing of
sleep. Psychophysiology, 10: 559-570.

Toothaker, L. (1991). Multiple comparisons for re-
searchers. Newbury Park: Sage Publications.

Wegmann, H. & Klein, K. (1985). Jet-lag and aircrew
scheduling. In S. Folkard & T. Monk (Eds.),
Hours of work: Temporal factors in work schedul-
ing, (pp. 263-276). New York: John Wiley &
Sons Ltd.


Table 37

Means and Standard Deviations for Green Warning Lights Response Time

Study Day cbi| At A2 D1 D2 N cb2/ CD3| CD4 CDS
Session 1
Younger_Mean |__ 2.7 21 2.3 22 2.2 19 2.0 2.1 2.0 2.1
SD] 14 0.3 0.7 0.7 0.7 0.5 0.4 12 0.8 08
Older Mean | _ 3.0 3.7 3.0 27 2.4 27 2.8 2.3 24 2.1
SD| 09 1.9 1.0 07 0.6 0.9 11 0.6 0.7 0.6
Session 1 Mean | 2.8 2.9 2.6 25 2.3 2.3 24 2.2 2.2 21
SD {1.0 16 09 0.8 0.6 0.8 0.9 0.9 0.7 0.7
Session 2
Younger_Mean | 2.4 2.4 2.4 2.2 24 24 21 2.3 25 2.2
SD] 04 1.3 0.9 0.6 1.4 1.0 0.7 1.7 1.7 0.8
Older Mean |_ 3.0 3.3 37 29 2.2 3.0 27 2.5 2.3 2.2
SD] 12 15 17 1.2 0.7 1A 0.7 0.7 08 0.5
Session 2 Mean | 2.7 2.8 3.1 2.6 2.3 2.7 2.4 2.4 2.4 2.2
SD] 09 1.4 15 1.0 11 11 0.7 1.2 1.3 0.7
Session 3
Younger Mean |_ 2.6 24 24 2.0 2.2 2.5 2.2 2.4 2.4 2.0
SD] 0.6 0.5 04 0.5 12 1.0 07 15 0.6 0.6
Older Mean {3.1 3.4 34 3.0 2.6 3.6 2.6 2.4 21 24
SD} 07 1.4 1.3 0.9 0.9 2.0 08 0.8 0.4 0.7
Session 3 Mean |_ 2.8 28 | 26 | 25 | 24 | 34 24 2.4 24 21
SD] 07 1.2 11 0.9 11 1.6 0.8 12 0.5 0.6
Table 38
MANOVA Summary Table for Green Warning Lights Response Time
Degrees of Sums of Squares | Mean Squares
Source of Variation Freedom F
[ Age 1 39.13 39.13 NS.
Between Subjects 18 244.53 13.58
Day of Study 9 34.38 3.82 4.48**
‘Age by Day 9 26.32 2.92 3.43"
Within Subjects 162 138.16 85
Session 2 1.73 86 N.S.
| Age by Session 2 A6 .23 N.S.
Within Subjects 36 23.63 66
Day by Session 18 9.73 54 N.S.
| Age by Day by Session 18 5.41 30 NS.
Within Subjects 324 117.24 36
*p<.05
**p<.001

A-19



target flight duration for the ANP Program was set
at five days. Although the resulting life support
requirements had been addressed in ground and sea
operations, such problems had not been addressed
in the cockpit. The resulting additional weight in
an airborne system was a critical factor. Thus, the
human factors (such as minimum number of crew
members, maximum duration of missions, and work/
rest schedules) of such an increase in flight time
needed to be investigated. Because no specific ad-
vanced aircraft system was to be simulated directly,
the line of research led to an approach to studying
multiple-task performance of synthetic work in
controlled laboratory situations. In 1968, Chiles et
al. presented a summary of their eight-year research
Program on the performance effects of various work/
rest schedules during confinement in a simulated
aerospace vehicle crew compartment. The MTPB,
the task battery utilized in the program to provide
the synthetic work environment, was found to be a
reliable, face-valid, sensitive technique for assessing
complex operator performance.

The goal of the measurement Process in the
Wright-Patterson research was to permit detection
of operationally important changes in operator per-
formance as a function of the requirements of an
extended mission. Thus, decrements should be
meaningfully relatable to critical operational tasks
in the cockpit that affect operator reliability, safety,
and success of the mission. To meet these goals, the
measurements had to be related to functions that
are required in the performance of operational tasks.
The determination of the measurements to be used
had to be based upon an analysis of the tasks
performed in the operational environment. Chiles,
et al. (1968) categorized the functions required in
an aviation related environment into the following
five categories: 1) monitoring a system's status; 2)
making discriminations among various stimuli pre-
sented by display indicators; 3) operating on or
storing information received from displays; 4) oper-
ating various controls to correct deviations from
desired conditions, to change existing conditions,
and to remove errors; and 5) communicating by
transmitting and receiving information from other

individuals in the system. In addition, time-shar-
ing, or the ability to distribute attention and action
over multiple displays and activities, was also iden-
tified as necessary.

Selection of the specific tasks for the battery was
initiated in a review of the existing human perfor-
mance literature. Chiles and associates concluded
that research at that time contributed only to
general guidelines, and that the selection would
need to be derived from task analysis for functions
of interest. Criteria were set for the tasks that dealt
with psychometric Properties, as follows: 1) the
tasks should be defensible as measures of functions
performed by an operator in advanced aviation-
related systems; 2) the tasks must appear to the
subject to measure important, valid functions; 3)
the tasks had to have good test-retest reliability; 4)
the tasks should be orthogonal, to the extent that
the operator functions were assessed as independent
Processes; 5) the task needed to be sensitive to
important, or “real” in an applied sense, perfor-
mance deficits; and 6) reasonable training periods
should result in asymptotic levels of performance.

Thus, the following set of tasks, which demon-
strated high reliability with relatively minor train-
ing requirements and allowed for the study of a
relatively broad range of workloads, was selected for
the MTPB. Detailed descriptions of the tasks in the
current battery are provided in the methods section
of this paper; however, the original tasks included:

1)Monitoring static processes. This category re-
lated to the operational environment, within
which an operator was concerned with assuring
that no malfunction or other type of emergency
had occurred by scanning a display, lights, or
dials. This measured the Operator’s perceptual
recognition of a non-normal state. In the original
battery, this included red and green lights, as
well as an auditory task.

2)Monitoring dynamic processes. In this task,

the indicators exhibited dynamic continuous

changes. The operator determined whether or
not the fluctuating process was within prescribed
limits. This measured the operator’s Perceptual
recognition and dynamic monitoring abilities.



Table 23
Means and Standard Deviations for Target Identification Percent Correct

Study Day cD1

A2

o1 D2 N

cp2

Session 1

Younger_ Mean 86.8

90.6

8.1

6.4

Older 88.5

5.6

48

5.5

Younger__Mean

SD

Older Mean

SD

Session 2 Mean

SD

Session 3

Younger__Mean

SD

Older Mean

SD

Session 3 Mean

sD

Table 24

MANOVA Summary Table for Target Identification Percent Correct

Source of Variation

Degrees of
Freedom

Sums of Squares

Mean Squares

1

1871.99

1871.99

Between Subjects

17

16320.33

960.02

Day of Study

1676.38

186.26

| Age by Day

301.77

33.53

Within Subjects

6447.72

42.14

Session

241.99

120,99

| Age by Session

72.79

36.40

Within Subjects.

663.18

19.51

Day by Session

491.95

27.33

| Age by Day by Session

294.10

16.34

Within Subjects

6827.47

*p<.05
**p<.001



tion was based on analysis of the composite scores.
Based upon these initial analyses, CD1, the last day
of the MTPB training week, was originally selected
as a day shift baseline day, ideally for comparison to
the effects of the 2-2-1, Performance, however,
Continued to improve well into the 2-2-1 week
(through Wednesday). The Older subjects appeared
to learn more slowly, but attained the same level of
performance as the Younger group by the end of
Wednesday (D1). The subjects had completed 46
hours of working on the full battery by this day.
Examination of the full 86 hours of MTPB perfor-
mance data during the present protocol revealed
that better stabilization probably occurred in the
Present study closer to the 48 hours of practice
reported by Chiles, et al. ( 1968). Although learning
curves were not within the. scope of the Present
report, significant differences existed between per-
formance on Wednesday (D1) of the 2-2-1 week
and Thursday of the final week (CD4), indicating
that performance continued improvement through-
out the three weeks of the study. The subjects,
themselves, presaged this finding in post-study
debriefings, in which they described modifications
to their time-sharing strategies that continued
through the middle of the 2-2-1 week. As with
studies on other computerized batteries (Damos,
1989), this finding was not entirely unexpected;
however, it did substantially complicate the data
analyses. It would suggest that for future studies
utilizing a similar MTPB 2-hour task schedule, a
minimum of 48 hours practice be provided prior to
experimental interventions.

The results of the Presence study suggest that the
problems a counterclockwise, rapidly-rotating shift
schedule poses for complex task performance may
be localized to the night shift, and that such prob-
lems could be addressed directly through fatigue
and sleepiness countermeasures. The detrimental
effects of the schedule on performance were not
evident in this study until the Night shift, even
though the sleep/wake cycle data demonstrated
significant disruption. The finding of a perfor-
mance decline on the Night shift was predicted by
the chronobiology, and was, therefore, not surpris-
ing. A basis for the performance effects on the night

20

shift was further established as the 2-2-1 progressed
with the phase advances and sleep loss patterns.
The night shift followed 1) three phase advances, 2)
an average period of 3.7 hours of sleep (Della Rocco
& Cruz, 1995), and 3) testing that occurred during
the circadian troughs of day-oriented individuals.

Damos (1989) reviewed studies on the circadian
thythm variability in performance of selected infor-
mation processing tasks. Her review, after substan-
tial cautions about methodological problems,
indicated that the range of differences between
mean performance and either the maximum or
minimum performance due to circadian effects were
less than 10%. Similar findings of performance
decrements of approximately 8% were found in the
phase-shift studies on the MTPB teported by
Higgins et al. (1975, 1976). In these studies,
performance decrements were evident after sleep
restriction to 3 hours in their Protocol and during
testing between 2400-0800, as they phase-shifted
their subjects, The majority of findings from MTPB
performance in the Present study ranged between
0-12% decrements on the Night shift during the 2-
2-1, with the exception of response time on Target
Identification (a 23% decrement). As such, it re-
mains unclear whether the performance decrements
were due primarily to the sleep loss just prior to the
Night shift, or whether the decrements might be
due solely to the effects of circadian variation.
Because the observed decrement was within the
range of previously reported effects of either sleep
loss or circadian thythm variability, it did noe
appear that an adverse additive interaction resulted
ftom the combination of sleep loss and time of day.

In her review of the circadian rhythm variability
on individual tasks, Damos questioned the opera-
tional significance of such a decline that only varied
by 10% from the mean. However, she suggested
that effects may have been masked, due to method-
ological inadequacies of the studies reviewed. Monk
(1990), while also noting methodological flaws in
the historical data base, cautioned that circadian
variation was a robust fluctuation, as well as the
result of the confluence of a number of factors,
including time-of-day, sleep distuption and loss,
and disruption of social and domestic status. Higgins


Table 7
Means and Standard Deviations for Passive Composite Scores

Study Day cD1 Al A2 1 D2 N cb2

Passive Composite
Session 1

Younger Mean 495

SD. 43

Older Mean 489

SD 25

Session 1 Mean | 492
SD 35.

Session 2
Younger Mean
sD
Older Mean
sD

Session 2 Mean
SD

Session 3
Younger Mean
SD
Older Mean
sD

Session 3 Mean
SD

Table 8
MANOVA Summary Table for Passive Composite Scores

Degrees of
Source of Variation Freedom Sums of
Squares
| Age 14451.51

Between Subjects 601116.63

Day of Study 7532.08
| Age by Day 27721.67
Within Subjects 144596.73

Session 4178.61
| Age by Session 1181.83
Within Subjects 29194.93

Day by Session 18523.61

| Age by Day by Session 10426.85

Within Subjects 137469.23
*p<.05
**p<.001



“Hath
ntl

ayer

The present study addressed only the acute ef-
fects of working one week of the 2-2-1 schedule.
Future research should address the effects of work-
ing a quick-turn-around schedule on a chronic
basis, as well as identification of individual differ-
ences in response to adaptation to the quick-turn-
around schedules.

REFERENCES

Chiles, W., Alluisi, E., & Adams, O. (1968), Work
schedules and performance during confinement.
Human Factors, 10 (2) : 143-196,

Chiles, W., Jennings, A., & West, G. (1972). Muttiple
sash performance as a predictor of the potential of air
traffic controller trainees (DOT/FAA/AM-72.5).
Washington, DC: Federal Aviation Administra-
tion, Office of Aviation Medicine.

Chiles, W. & West, G. (1974). Multiple task perfor-
mance as a predictor of the potential of air traffic
controller trainees: A followup study (DOT/FAA/
AM-74-10). Washington, DC: Federal Aviation
Administration, Office of Aviation Medicine.

‘Collins, W. & Mertens, H. (1988), Age, alcohol, and
simulated altitude: Effects on performance and

breathalyzer scores. Aviation, Space, and Envi-
ronmental Medicine, 59: 1026-1033.

Collins, W., Mertens, H., & Higgins, E. (1987),
Some effects of alcohol and simulated altitude on
complex performance scores and breathalyzer
readings. Aviation, Space, and Environmental
Medicine, 58: 328-332.

Colquhoun, P. (1982). Biological rhythms and per-
formance. In Wilse Webb (Ed.), Biological
rhythms, sleep, and performance, (pp. 59-86).
Chichester, England: John Wiley & Sons, Ltd.

Cruz, C., Della Rocco, P., & MacLin, O, (1993).
Stabilization of performance on a computer-
based version of the Multiple Task Performance

Battery. Proceedings of the Seventh International
Symposium on Aviation Psychology, 2: 843-848,

Damos, D. (1989). A review of circadian offects on
selected human information processing tasks
(NAMRL Monograph 37). Pensacola, FL: Naval

Air Station, Naval Aerospace Medical Research
Laboratory.

Della Rocco, P. & Cruz, C. (1995). Shifiwork, age and
performance: I. Sleephuake cycle in laboratory.
based investigation of the 2-2-1 shiff schedule used in
air traffic control facilities, (DOT/FAA/AM-95/
19). Washington, DC: Federal Aviation Admin-
istration, Office of Aviation Medicine.

Folkard, S. (1975). Diurnal variation in logical rea-
soning. British Journal of Psychology, 66: 1-8.

Folkard, S. & Monk, T. (1985). Circadian perfor-
mance rhythms. In S. Folkard and T. Monk
(Eds.) Hours of work: Temporal factors in work

scheduling, (pp. 37-52). New York: John Wiley
& Sons Ltd.

Higgins, E., Chiles, W., McKenzie, J., Funkhouser,
G., Burr, M., Jennings, A., & Vaughan, J.
(1976). Physiological, biochemical, and mutltiple-
task-performance responses to different alterations of
the wake-sleep cycle (DOT/FAA/AM-76-11),
Washington, DC: Federal Aviation Administra-
tion, Office of Aviation Medicine.

Higgins, E., Chiles, W., McKenzie, J., Iampietro, P.,
Winget, C., Funkhouser, G., Burr, M., Vaughan,
J., & Jennings, A. (1975). The effects of a 12-hour
shift in the wake-sleep cycle on physiological and
biochemical responses and on muttiple task perfor.
mance (DOT/FAA/AM-75-10), Washington,
DC: Federal Aviation Administration, Office of
Aviation Medicine,

Klein, K. & Wegmann, H. (1974). The tesynch-
ronization of human circadian rhythms after
transmeridian flights as a result of flight direc-
tion and mode of activity. In L. Scheving, F.
Halberg, & J. Pauly (Eds.), Chronobiology (pp.
564-570). Tokyo: Igaku.

Kleitman, N. (1963). Sleep and wakefulness. Chicago:
University of Chicago Press,


Table 25

Means and Standard Deviations for Target Identification Response Time

Study Day cp1| At | A2| bt p2[ N_[cp2 {cps | cps | cps
Session 1

Younger_Mean | 2.4 2.2 2.1 2.2 2.1 24 22 2.2 2.3 2.1

SD | 0.7 0.4 0.3 0.3 0.3 07 0.3 03 0.4 0.3

Older Mean |_2.2 21 22 2.1 21 2.0 21 2.0 2.0 2.0

SD| 04 04 0.5 0.4 03 0.4 0.4 0.5 04 04

Session 1 Mean | 2.3 21 2.2 21 21 2.2 2.2 2.1 2.1 21

SD | 06 0.4 0.4 0.3 | 0.3 0.5 0.4 0.4 0.4 0.3

Session 2

Younger Mean | _2.4 2.2 2.4 22 24 2.4 2.6 2.2 27 2.2

SD | 0.6 0.4 0.4 0.3 06 0.5 0.8 0.4 13 0.3

Older Mean | 2.1 21 21 23 2.2 2.5 21 21 2.0 24

Session 2 Mean |_ 2.3 22 2.3 2.2 2.3 2.5 24 2.2 2.3 2.2

SD] 05 04 0.4 0.4 0.5 09 0.7 0.4 1.0 0.4

Session 3

Younger Mean | 2.4 2.4 22 22 23 2.8 2.2 23 2.3 2.2

SD | 0.4 0.3 0.2 0.4 06 1.0 0.4 05 05 0.4

Older Mean | 2.1 23 21 24 2.1 2.6 2.1 2.0 2.0 24

SD} 0.4 0.6 0.5 04 0.4 1.1 0.5 0.5 0.4 0.5

Session3 Mean | 2.2 2.3 2.2 21 2.2 27 2.2 22 2.1 21

SD] 0.4 O5 0.4 04 | 05 1.0 05 0.5 0.4 0.5

Table 26
MANOVA Summary Table for Target Identification Response Time
Degrees of Sums of Squares | Mean Squares
Source of Variation Freedom F
| Age 1 4.73 4.73 N.S.
Between Subjects 17 86.55 5.09
Day of Study 9 4.38 49 2.54"
| Age by Day 9 1.63 18 NS.
Within Subjects 153 29.32 19
Session 2 1,39 -70 6.14"
Age by Session 2 18 09 N.S.
Within Subjects 34 3.85 Aa
Day by Session 18 3.00 7 2.50°*
[ Age by Day by Session 18 2.16 12 1.80"
Within Subjects, 306 20.37 07
*p<.05
“p<.001

A-13


Results of the MANOVA for response times on
the Green Warning Lights revealed a significant
interaction for Age by Day, E(9, 162) = 3.43,
p<.001, as well as a main effect for Day, F(9, 162)
= 4.48, p<.001. Planned comparisons failed to
reach statistical significance for the Age by Day
interaction or the Day main effect.

Workload

This section presents the descriptive statistics for
the Passive Composite and Active Composite Scores
by Session and by 15-minute interval for the Night
shift. It should be noted that workload varied from
Interval 1 to Interval 8 in terms of the number of
active tasks being presented along with the passive
tasks. During Intervals 1 and 8, only the Passive
tasks were presented (low workload). Active tasks
were only present during Intervals 2 through 7.
Intervals 2, 4, 5, and 7 represented medium
workload conditions in which one active task was
presented along with the passive tasks. Finally,
intervals 3 and 6 represented high workload condi-
tions in which two active tasks were presented along
with the passive tasks.

Figure 18 and Table 39 present descriptive sta-
tistics for the Passive Composite Scores during the
Night shift. Table 40 presents the MANOVA sum-
mary table for Passive Composite Scores by 15-
minute interval during the Night shift.

Results of the 2 x 3 x 8 MANOVA for the Passive
Composite Scores on the Night shift revealed a
significant three-way interaction of Age by Interval
by Session, F(14, 252) = 2.02, p<.05, a two-way
interaction for Interval by Session, F(14, 252) =
5.41, p<.001, as well as a significant main effect for
Interval, F(7, 126) = 9.08, p<.001. Planned com-
parisons to examine the Session by Interval interac-
tion investigated performance changes within each
interval across each Session. Results revealed: 1)
Interval 2 (medium workload) for Session 3 (M =
490) was significantly lower than for Session 1 (M
= 524), £(18) = 4.48, p<.05, representing a 6%
decline in performance; and 2) Interval 5 (medium
workload) for Session 2 (M = 479) was significantly
lower than Session 1 (M = 523), 1(18) = 5.05,
p<.05, representing an 8% decline.

17

Figure 19 and Table 41 presents the descriptive
statistics for the Active Composite Scores by Session
and Interval during the Night shift. Table 42
presents the MANOVA summary table of Active
Composite Scores by Interval during the Night shift.

Results of the 2 x 3 x 6 MANOVA for the Active
Composite Scores on the Night shift revealed a signifi-
cant interaction of Interval by Session F(10,180)=2.66,
p<.05, a main effect for Interval F(5,90)=6.97,
p<.001, as well as a significant main effect for
Session F(2,36)=6.98, p< .001, Examination of the
planned comparisons revealed no significant differ-
ences between Sessions, suggesting that subjects
protected their performance on the Active Tasks,
but failed to maintain a similar level of performance

for the Passive Tasks.

Critical Tracking

Figure 20 and Table 43 present the descriptive
statistics for the median lambda scores for the
Critical Tracking Task from days CD1 through
CD5 for the pre-MTPB Session 1 and the post-
MTPB Session 3. Higher scores indicate better
performance. Table 44 presents the MANOVA
summary table for Critical Tracking.

The results of the 2 x 10 x 2 MANOVA revealed
a significant three-way interaction of Age by Day by
Session, F(9, 162)=3.08, p<.05, a significant two-
way interaction of Day by Session, F(9,162)=2.91,
p<.05, and a significant main effect for Day, F(9,
162)=17.7, p<.001. There was no significant main
effect of Age Group. Planned multiple comparisons
to assess the Day by Session interaction revealed that:

1) Performance was significantly better, com-
pared to the pre tracking session on CD1 (M=3.98),
for the pre tracking session on D2 (M=4.42),
£(18)=3.74, p<.05; N (M=4.48), ¢(18)=4.02,
p<.05; CD2 (M=4.48), 1(18)=4.03, p<.05; and
CD3 (M=4.56), £(18)=4.13, p<.05.

2) Post tracking performance on CD3 (M=4.68)
was significantly better than on CD1 (M=4.20),
£(18)=4.84, p<.05.

Planned multiple comparisons to assess the main
effect for Day did not reach statistical significance.
The Age by Day by Session interaction was most
evident on the recovery from the Night shift to


Table 2
Schedule of Tasks by 15-Minute Segment

1 2 3
TASK 0-15 15-30 30-45
Monitoring Lights x x x
Monitoring Meters x x x
Arithmetic x x
Code Lock x
Target ID

Time Segment
4 § 6 7 8
45-60 60-75 75-90 90-105 105-120
x x x x x
x x x x x
x x x
x x

to recall the sequence from memory after a 15-
second delay. A panel below the CRT was equipped
with five push buttons labeled A through E. Lights
indicating 1) that the task was active, 2) correct and
incorrect button presses, and 3) when a sequence
had been decoded correctly, appeared in the middle
of the lower quarter of the CRT. Subjects were
instructed to decode the series of five letters using
a left-to-right search pattern. This resulted in a
predictable number of errors if the subject main-
tained the requested search pattern. When a subject
received an indication of an incorrect response, the
decoded portion of the sequence had to be re-
entered before proceeding with the left-to-right
search pattern to find the next letter. A correctly-
entered sequence was followed by a 15-second
delay, after which subjects re-entered the correct
sequence again from memory. Performance mea-
sures were mean response latency and percent cor-
rect for both the solution and the recall portions of
the task.

6 Critical Tracking. The Critical Task Tester
MK 10 (Systems Technology, Inc., Hawthorne,
CA) consisted of a Commodore $X-64 computer, a
custom ROM program module, a CRT display
(mounted above the main CRT display of the
MTPB), and a custom manual controller (Smith &
Jex, 1986). Critical Tracking was not combined
with the other five tasks within the battery, but
rather, was presented before and after each 2-hour
MTPB session. Each presentation of the Critical
Tracking task involved five trials. During each trial,
subjects attempted to stabilize an arrow in the

center of the screen by using the custom controller.
The arrow became increasingly unstable as the task
progressed, until the subject was no longer able to
control it, and it went out of bounds to the left or
right. Lambda was a value of the instability in the
system, which increased steadily as the task pro-
gressed. The median lambda score from the five
trials represented the score for that session.

The above tasks, with the exception of Critical
Tracking, were variously combined into a two-hour
protocol. Critical Tracking was administered im-
mediately before and after each MTPB session. The
order of presentation of MTPB tasks across each
two-hour session was constant throughout the study.
Tasks were added or removed to vary the workload

every 15 minutes, according to the schedule pre-
sented in Table 2.

Procedures

The MTPB Laboratory was designed with five
workstations. Thus, four groups of five subjects
completed the protocol between September 1992
and February 1993, Each group of five subjects was
balanced for subjects from the Older and Younger
age groups (i.e., one group consisted of two subjects
from the Older group and three from the Younger
group, while the next group consisted of three
subjects from the Older group and two from the
Younger group).

Subjects reported to the laboratory from Monday
through Friday, but continued wearing the por-
table physiological monitor throughout the week-
ends. Start dates for each of the groups varied due to


Table 19

Means and Standard Deviations for Code Lock Recall Percent Correct

Study Day cpt Al A2 Di D2 N co2_| cp3 | cpa cDs
Session 1
Younger _Mean| 96.4] 96.8 | 98.0| 972| 9711 056 96.5 | 96.9 | 95.1 | 97.0
SD 3.2 3.8 1.3 26| 22{ 421 26] 42 43| 38
Older Mean 925] 95.2| 939] 952] 95.6 94.9] 93.6] 96.1 96.6 | 96.1
SD 58] 23[ 0 34 24{ 23{ 27[ 45] 35 26] 3.0
Session 1 Mean 945 | 96.0] 96.0] 962] 96.4 95.2 | 95.1 | 96.5 95.8 | 96.6
sp 5.0] 32{ 34 26| 23] 34/7 397 38 3.6 | 3.4
Session 2
Younger_Mean| 97.5] 96.4{ 969] 9761] o6D 948] 95.6] 96.3] 944[ 962
SD 22{ 34 2.9 15|_ 37| 647 34] 28 74/34
Older ___Mean|__95.0 | 92.5|~ 945] 9341 052] 009 94.8] 968| 96.0[ 966
SD 25 3.1 2.2 3.0 27 3.6 3.4 3.3 2.3 24
Session 2 Mean 96.3 | 94.5] 95.7] 95.5] 95.7 93.5 | 95.2[ 96.6 95.2 | 96.4
SD 2.6 3.6 28 3.2 3.2 5.2 3.3 3.0 5.4 2.9
Session 3
Younger Mean | 96.2 |" 97.8 | 985| 974| 965] 050 96.1] 97.0| 95.4] 96.0
sD 35 17{ 12 21 32) 44] 45] 37 34] 45
Older___Mean| 93.1 | 94.0| 94.6{ 97.1] 046] 903 95.7| 965] 968] 95.9
SD 33] 3.0| 23 22| 34) 64 16] 29 27] 40
Session3 Mean| 947 959| 965] 9721 955| 000 95.9| 96.8 | 96.1 | 96.0
sD 37] 34 27 21] 3.3 59] 33] 33 3.1 44
Table 20
MANOVA Summary Table for Code Lock Recall Percent Correct
Degrees of Sums of Squares | Mean Squares
Source of Variation Freedom F
| Age 1 408.03 408.03 N.S.
Between Subjects 18 2028.89 112.72
Day of Study 9 321.34 35.70 3.62**
| Age by Day 9 352.28 39.14 3.97""
Within Subjects 162 1596.22 9.85
Session 2 14.94 7.47 N.S.
| Age by Session 2 3.09 1.54 N.S.
Within Subjects 36 361.43 10.04
Day by Session 18 170.92 9.50 N.S.
Age by Day by Session 18 154.24 8.57 N.S.
Within Subjects 324 2360.96 7.29
*p<.05
**p<.001

A-10



Table 13
Means and Standard Deviations for Arithmetic Response Time
Study Day CDi Al A2 D1 D2 N Ccb2 | CD3 | cbd4 | CDs
Session 1
Younger _Mean| 85 | 85 | 78 | 7.7 | 7.8 | 83 | a7 [ 84 8.9 8.2
SD/ 16 | 19 | 17 | 16 [| 19 [ 22 [25 [ 22 | 23 18
Older Mean | 9.3 8.8 86 86 8.4 87 8.3 84 8.1 8.5
SD] 17 | 16 | 14 | 16 115 [15 [1.7 [19 1.3 1.2
Overall Mean! 8.9 86 8.2 8.2 81 8.5 8.5 8.4 8.5 8.3
So{ 16 | 1.7 | 16 [16 [17 | 19 [ 21 | 20 18 15
Session 2
Younger_Mean| 8.1 | 7.9 | 7.6 | 7.6 | 85 | 85 [| 80 | 80 85 8.0
SD] 15 | 47 | 15 | 15 | 20 | 24 [19 [ 20 2.2 1.6
Older Mean | 8.9 8.6 8.6 8.3 8.2 8.5 83 8.1 7.9 8.1
SD/ 18 | 19 | 15 | 15 | 14 [| 17 [14 [ 15 1.3 15
Overall Mean| 85 | 8.2 | 81 | 7.9 | 84 | 85 | 62 | 84 8.2 8.1
so] 17 | 48 {15 [145 [1.7 [20 | 16 [ 17 1.8 1.5
Session 3
Younger__Mean | _7.9 8.0 7.8 76 | 7.9 | 85 | 82 8.1 7.8 79
So] 14 113 | 16 | 16 | 18 [ 18 [21 [ 24 1.6 1.9
“Older Mean | 8.9 9.0 85 8.4 83 89 8.4 8.0 78 81
Sp] 18 | 20 | 1.7 | 15 | 14 7 18 [16 [15 11 1.5
Overall Mean | 8.4 8.5 8.1 8.0 8.1 8.7 3.3 8.0 78 8.0
SD] 1.6 18 1.6 16 1.6 1.8 1.8 2.0 13 17
Table 14
MANOVA Summary Table for Arithmetic Response Time
Degrees of Sums of Squares | Mean Squares
Source of Variation Freedom F
1 17.86 17.86 N.S.
Between Subjects 18 1384.46 76.91
Day of Study 9 21.61 2.40 3.27%"
| Age by Day 9 26.90 2.99 4.07 **
Within Subjects 162 118.90 73
. Session 2 6.37 3.18 12,86"
Age by Session 2 98 49 N.S.
Within Subjects 36 8.91 25
Day by Session 18 9.00 50 N.S.
| Age by Day by Session 18 6.84 38 NS.
Within Subjects 324 105.52 33
*p<.05
“p<.001

A7



“quick turn-around” (between the second
afternoon shift and the first day shift) due
to partial sleep loss and/or the phase-
advancing properties of the 2-2-1.

b) There would be a significant decrement in
performance on the night shift due to
circadian performance troughs, cumula-
tive partial sleep loss, the phase-advancing
properties of the 2-2-1, and/or an interac-
tion of all of these factors.

2)There would be an interaction between age
and the adverse effects of shift work schedules on
performance. Specifically, it was hypothesized
that there would be a main effect of age on the
analyses conducted on sleep and performance,
such that the older group would show signifi-
cantly greater effects of the 2-2-1 schedule. In
addition, it was hypothesized that biochemical
measures of the stressor effects of the 2-2-1
schedule would indicate that the older group
experienced the schedule as significantly more
stressful.

.3)Performance measures would demonstrate a
recovery period after resuming a day shift. Spe-
cifically, the following hypotheses were tested.

a) Performance scores on the first day shift
after a 2-2-1 schedule would be signifi-
cantly lower than the second afternoon
shift of the 2-2-1 or subsequent days dur-
ing the final week of day shifts.

b) The older subjects’ performance scores
would be significantly lower than the
younger group’s on the first day shift after
a 2-2-1 shift and would take longer to
recover.

METHODOLOGY

A four-week protocol was designed to investigate
the effects of the 2-2-1 quick-turn-around sched-
ule. The first week of the protocol was allocated for
subject adaptation to wearing physiological moni-
tors 24 hours per day. The remainder of the proto-
col involved an A-B-A work schedule design, whereby
subjects worked straight days (0800-1630) during
the second week of the study, the 2-2-1 schedule
during the third week, and returned to a straight

Table 1
Study Protocol

DAYS LABEL PROTOCOL
Week1 Baseline Adaptation to
Vitalog Monitor

1 B1 0800-0900

2 B2 0800-0900

3 B3 0800-0900

4 B4 0800-0900

5 BS 0800-0900

6 wi

7 we

Week2 DAYS1 Straight Day Shift

8 1 0800-1630

9 T2 0800-1630

10 3 0800-1630

Ww T4 0800-1630

12 cDi 0800-1630

13 Ww3

14 W4

Week 3 2-2-1 2-2-1 Schedule

15 Al 1600-2430

16 A2 1400-2230

17 D1 0800-1630

18 b2 0600-1430

19 N 2400-0830

20 W5

21 W6

Week4 DAYS2 Straight Day Shift

22 cb2 0800-1630

23 cD3 0800-1630

24 CcD4 0800-1630

25 CDS 0800-1630

26 CD& 0800-1200
LEGEND

B=Baseline W=Weekend

T=Training CD=Control Day

A=Afternoon Shift D=Day Shift

N=Night Shift



3) Stimulus discrimination (target identification).

The operator was required to make simultaneous

or successive comparisons of stimuli, and judge

the similarity or differences of one or more pa-
rameters of the stimuli.

4)Information processing (arithmetic computa-

tion). Operators in an aviation-related environ-

ment must carry out a variety of tasks that
require processing information received from
various kinds of displays. Mental computation is
common to a number of the tasks. Therefore,
mental arithmetic was chosen as the information
processing task. It required short-term memory
involved in sequential mental operations, and
long-term memory required for mental arith-

metic operations. It was also identified as a

means of using up “mental channel capacity.”

5) Procedural performance (code-lock). This pro-

vided a measure of the operator’s ability to carry

out procedures, and problem solving. In the
original battery, this was a group coordinated
activity and involved communication among

“crew members.”

Chiles, et al. (1968) reported the results from 13
studies and 139 subjects, conducted over an eight-
year period. Among their findings were: 1) perfor-
mance on the battery of tasks reached asymptote
after 48 hours of practice, 2) test-retest reliabilities
for the tasks were very good, and 3) when perfor-
mance was measured around-the-clock, diurnal
variations in performance tended to parallel varia-
tions in psychophysiological measures.

Use of the MTPB allows the investigation of
Knowles’ (1963) theories of measurement of
workload. One of Knowles’ theories stated that an
efficient way to assess workload was through the
effect of performance of a task of primary interest to
the subject on the subject’s performance of a sec-
ondary task. Thus, with the MTPB, the monitoring
tasks provide secondary “passive” tasks, against
which the addition of primary “active” tasks (men-
tal arithmetic, code lock, and target ID) can be
assessed.

Significant differences between 15-minute seg-
ments were reported by Chiles, et al. (1968) in
performance of the monitoring tasks alone, versus

the full battery. In summary, the monitoring data
indicated that working on the entire battery of tasks
constituted an increased workload relative to the
monitoring tasks alone. The heaviest workload was
found in the arithmetic with code lock and target
ID with code lock conditions. ’

By 1968, Chiles was employed by the FAA at
CAMI. Over the next decade, Chiles conducted a
number of studies with the MTPB, investigating
parametric dynamics of such variables as signal
presentation rates for both the static and dynamic
warning lights, and the investigation of the exist-
ence of a separate time-sharing ability.

Finally, Chiles, Jennings, and West (1972) and
Chiles and West (1974) examined the MTPB as a
predictor of the potential of ATCSs to successfully
complete the FAA Academy nonradar training pro-
gram, and succeed in field training. This pair of
studies demonstrated the predictive validity of the
MTPB measures for Academy training and subse-
quent retention/termination status of trainees 2-
2.5 years post-hire.

The MTPB has continued to be a valuable re-
search tool as a synthetic work environment for
studies of the effects of various stressors on complex
task performance (Collins, Mertens, & Higgins,
1987; Collins & Mertens, 1988). The present
study introduced a new, graphical CRT implemen-
tation of this battery. This version of the battery
included monitoring of red and green warning
lights (static stimuli), monitoring of probability
meters (dynamic stimuli), mental arithmetic, tar-
get identification, and code lock solution and recall.

Research Hypotheses

Based upon the review of the literature, the
following hypotheses were generated for investiga-

tion in the present study:
1)There would be a significant decrement in
performance on complex tasks during the 2-2-1
work week because of the phase-advancing char-
acteristics of the 2-2-1 schedule and the circa-
dian performance trough on the night shift.
Specifically, the following hypotheses were tested:
a) There would be a significant decrement in
performance on the day after the first


CD2. Up until CD2, the Older and Younger group’s
performance had been quite comparable for the pre
and post tracking sessions, On CD2, however, this
pattern did not hold true on the post tracking
session where the older group outperformed not
only the younger group but their own performance
on the pre tracking session. There was, however,
strong continuous learning evidenced in this
measure that continued throughout the duration
of the study.

DISCUSSION

This report presented the performance data from
a laboratory-based investigation of a unique, rap-
idly-rotating shift schedule, the 2-2-1, commonly
used by Air Traffic Control Specialists. While a
series of previous field studies on ATCSs had in-
cluded investigation of the 2-2-1 schedule, none
had involved controlled laboratory-based research,
nor had any included performance measures, Be-
cause air traffic control is a safety-related occupa-
tion, it was important to investigate the extent to
which the 2-2-1 schedule could result in possible
adverse effects, such as performance decrements.

Subjects participated in a four-week study in
which the first week was a baseline, followed bya
three week, A-B-A designed work week schedule,
comparing straight day schedule (A condition) per-
formance to performance on the 2-2-1 schedule
(the B condition). The A-B-A design, in combina-
tion with instructions to subjects to maintain stable
sleep/activity patterns, was structured to ensure, as
nearly as possible, that subjects were day-oriented
in their circadian rhythms Prior to the 2-2-1, and
then to assess any disruption and recovery due to
the 2-2-1.

The study addressed the issue of whether or not
the subjects working the 2-2-1 were able to main-
tain a relatively stable day orientation, or whether
the phase-advancing Properties of the schedule
would be so disruptive as to manifest in subject
performance. Four specific hypotheses were investi-
gated to determine the extent to which the 2-2-1
schedule: 1) disrupted sleep patterns and resulted

18

2) resulted in

in cumulative partial sleep loss;
performance decrements on a complex cognitive

task in the synthetic work environment; 3) inter-
acted with age to cause greater adverse effects in
older subjects; and 4) caused changes in measures
that continued into the day shift week following the
2-2-1 and required a tecovery period.

The present study introduced a new, computer-
ized version of the MTPB. The MTPB had histori-
cally provided a motivating synthetic work
environment over extended periods of time for
Purposes of investigating air crew staffing schedules
(Chiles et al., 1968) and had been validated as a
predictor of success in ATCS training (Chiles &
West, 1974). With the exception of a substantial
learning curve, subjects maintained telatively stable
performance over the required three-week protocol
in this study.

One important contribution of the Present study
resided in the outcome of the performance data
under the 2-2-1 schedule. The analyses focused
primarily on the two quick-turn-arounds in the 2-
2-1, a possible recovery period, and the specific
performance on the Night shift, with the hypoth-
eses that each of these characteristics of the schedule
would lead to performance decrements, The effect
of the 2-2-1 on complex task performance was
investigated on three levels: 1) Composite scores for
Total, Passive and Active tasks for each 2-hour
session, 2) each individual task measure, and 3) 15-
minute Workload changes during the Night shift.

The results from analyses of the composite scores
revealed that the only significant decrement in
performance occurred on the Night shift. Signifi-
cant decrements were found in both Active and
Passive Composite scores during the third session of
the Night shift. Thus, the hypothesis that both quick-
turn-arounds within the 2-2-1 would result in perfor-
mance decrements was only partially supported,

The composite scores, however, combined speed
and accuracy measures. Thus, even though re-
sponse times were converted such that higher scores
indicated faster performance, opposing changes in
speed or accuracy due to time of day or fatigue
effects could have been masked or minimized by the


MTPB Tasks. The MTPB tasks included moni-
toring tasks, a tracking task, and information pro-
cessing tasks that involved mental arithmetic,
complex visual discrimination, and problem solv-
ing. These tasks measured basic psychological or
behavioral functions relevant to control of complex
systems in general, and ATC and pilot tasks in
particular. A brief description of each task follows.

1, Red and green light monitoring. These were
static monitoring tasks. Five pairs of lights (one red
and one green per pair) were graphically repre-
sented at each corner and in the center of the CRT.
Corresponding red and green push buttons were
located next to each light just outside the CRT,
with the buttons for the center lights located below
the CRT. In each pair, the upper light was red and
the lower one was green. The normal state for the
red lights was “off,” and for the green lights was
“on.” A signal consisted of a change in the normal
state of either light to on or off, respectively.
Subjects were instructed to respond to the signal by
pushing the button corresponding to the light that
chairged. A response returned the signal to the
normal state. The light returned automatically to
the normal state if no response was initiated within
15 seconds of signal onset. The performance mea-
sures for these two tasks were mean response latency
and percentage of correct responses. Response time
was recorded in hundredths of a second separately
for the red and green lights.

2. Meter monitoring. This task was a dynamic
monitoring task. Four graphic representations of
meters, with full-scale values from -50 to +50, were
presented in the upper quarter of the CRT. A signal
was present on a meter if the needle on the meter
deflected by an identifiable amount to either the
right or the left of center. The needle was in a
constant state of “random” background disturbance
(“noise”). When no signal was present, the needle
deviated unpredictably with an average position of
zero. With a signal present, the average position of
the needle was shifted. A row of four pairs of buttons
was mounted above the CRT, corresponding to
each meter. Subjects were asked to respond to a
signal by pressing one of the corresponding buttons
to indicate a right or left deflection of the needle.

When a button for a given meter was depressed, the
background noise was removed and the pointer
stopped on its “true” average value, giving immedi-
ate feedback as to the accuracy of the response. The
background noise then began again. The measures
of performance were mean response latency for all
signals and percentage of correct responses. Re-
sponse time was recorded in hundredths of a sec-
ond.

3. Mental arithmetic. This task was presented
graphically on the CRT about 1/3 of the distance
from the bottom of the display. Problems consisted
of three two-digit numbers in the following form:
“XX + YY - ZZ = .” The subject was instructed to
enter the answer in reverse serial order through the
“10 key” keypad on the keyboard. The response was
displayed on the CRT and the subject could correct
the answer before pressing the enter key using the
backspace key. If the answer was correct, a blue box
appeared next to the answer. If the response was
incorrect, a yellow-orange box appeared. The per-
formance measures were mean response time for all
problems and percent correct. Response time was
measured between the time the problem was pre-
sented and a press of the enter key.

4. Target Identification. This was a pattern
recognition task: requiring mental rotation. This
task was graphically presented in a square box
between the meters and the mental arithmetic on
the CRT. Response buttons were located on the
right side of a panel below the CRT. A standard
histogram pattern of six bars of varying height was
presented. Two comparison patterns, which may
have been rotated 0, 90, 180, or 270 degrees, were
subsequently presented in succession. The subjects
were to decide if one, both, or neither of the
comparison patterns matched the initial target, and
then press the appropriate button. If the response
was correct, a blue box appeared next to the task on
the CRT. An incorrect response resulted in the
presentation of a yellow-orange box. Performance
measures wete mean response latency for all prob-
lems and percentage of correct responses.

5. Code Lock. This self-paced task involved two
parts: 1) following procedures to decode a five-
letter sequence, and 2) utilizing short-term memory



APPENDIX A
TABLES


Technical Report Documentation Page

7. Report No. 2. Government Accession No. 3. Reciplent’s Catalog No.
DOT/FAA/AM-96/23

Title and Subtitle 8, Report Date

Shift Work, Age, and Performance: Investigation of the 2-2-1 Shift September 1996
Schedule Used in Air Traffic Control Facilities I. Laboratory

Performance Measures

6. Performing Organization Code:

7. Author(s) 8. Performing Organization Report No.
Pamela S. Della Rocco and Crystal E. Cruz

9. Performing Organkation Name and Address 10. Work Unit No. (TRAIS)
FAA Civil Aeromedical Institute

P.O. Box 25082 Ti. Contract or Grant No.
Oklahoma City, OK 73125

12, Sponsoring Agency name and Address 13. Type of Report and Period Covered
Office of Aviation Medicine
Federal Aviation Administration
800 Independence Ave., S.W.

Washington, DC 20591 14. Sponsoring Agency Code

15. Supplemental Notes
“a

16. Abstract

Many Air Traffic Control Specialists (ATCSs) work a counterclockwise rotating shift schedule, called the “2-2-1,” or some
variation of the schedule. The 2-2-1 involves rotating from two afternoon shifts to two mornings, and finally, to a midnight shift
over the course of one work week. The purpose of the present study was to investigate the effects in two different age groups of
working the 2-2-1 schedule, as compared to a straight day schedule on measures of complex task performance in a laboratory-
based synthetic work environment. It was hypothesized that the counterclockwise rotations would result in performance
decrements over the course of the 2-2-1 week. Four groups of five male subjects between the ages of 30 to 35 (n=10) and 50 to
55 (n=10) participated in the four-week study. Subjects were screened on medical and cognitive criteria. The Multiple Task
Performance Battery (MTPB) was utilized to provide a motivating synthetic work environment. Subjects worked three 2-hour
sessions on the MTPB per eight-hour day for three weeks of a four-week protocol. During the second and fourth weeks,
subjects worked day shifts (0800-1630). During the third week, subjects worked the 2-2-1 schedule. Performance measures
were analyzed for each of the five tasks in the MTPB. Composite scores were also computed. Significant performance
decrements were observed primarily on the night shift for both age groups. The older group demonstrated decrements in
accuracy of recall on the code lock task following both rapid rotations during the 2-2-1 schedule. This study was part of a
research program designed to develop fatigue countermeasures for Air Traffic Control Specialists. The hypothesis that the
rapid, counterclockwise rotations would result in performance decrements was partially supported. Data suggest that initial
interventions should be directed toward maintaining alertness and performance on the night shift.

17. Kay Words 18. Distribution Statement
Shift Work, Performance, Document is available to the public through the
Multiple Task Performance Battery, National Technical Information Service
Age Springfield, Virginia 22161
19, Security Classif. (of this report) 20. Securtty Classi. (of this page) 21. No. of Pages 22, Price
Unclassified Unclassified 60
Form DOT F 1700.7 (8-72) Reproduction of completed page

authorized



Total Composite Scores

‘# Younger ¢ YoungerSD -* Older 4 Older SD J

620
580
540
500

460

Standardized Scores

420

380

oo or
rn

poppe py pe pe
TT or a a a

Session1 23123123123123123123123123123

Day CD1 | Al A2 D1 D2 N | CD2 CD3 CD4 CD5

340 Ft

Day 2-2-1 Shift Day Shift

Figure 1. Means and standard deviations for Total Composite Scores by Age
group and by Session.

B-3



Table 3

Sample Daily Experimental Protocol

Time Activity

0800-0830 Arrive at the laboratory and download Physiological data
0830-0835 Tracking and Questionnaires
0835-1035  MTPB Session 1

1035-1045 Tracking and Questionnaires
1045-1130 Meal Break

1130-1135 Tracking and Questionnaires
1135-1335  MTPB Session 2

1335-1345 Tracking and Questionnaires
1345-1405 Break

1405-1410 Tracking and Questionnaires
1410-1610 MTPB Session 3

1610-1615 = Tracking and Questionnaires
1615-1630 Debriefing, supplies
Table 4

The Study 2-2-1 Shift Schedule

Day 2-2-1 Hours Between Shifts
1 1600-2430 13.5
2 1400-2230 95
3 0800-1630 13.5
4 0600-1430 95
5 0000-0830

ll


various scheduling difficulties. Groups 1 and 3
began their protocols as scheduled on a Monday
(Day 1). Group 2, however, did not begin until
Wednesday (Day 3), and Group 4 started the study
on a Tuesday (Day 2).

MTPB Measures

MTPB performance was assessed on three levels:
1) Composite scores combining performance on all
tasks into one of three scores (total composite [TC],
passive task composite [PC], and active task com-
posite [AC]) for each two-hour session; 2) raw scores
for each task; and 3) composite scores for Passive
tasks during each 15-minute interval (see Table 2)
within each session.

Composite scores were computed using the pro-
cedure reported by Mertens, McKenzie, and Higgins
(1983). Raw scores for each task measure were
standardized, with a mean of 500 and standard
deviation of 100 across each 15-minute interval of
every session from Day CD1 through CD4. Re-
sponse time measures were multiplied by -1, so that
higher scores represented faster response times, and
lower scores represented slower response times.
Composite scores were derived by averaging the
various measures recorded for each task, such that
each task contributed equally to the composite
score. Specifically then, three task composites were
computed: 1) an AC score (average of arithmetic,
target identification, and code lock composite
scores), 2) a PC score (average of red and green
warning lights, and probability meter composite
scores), and 3) a TC score (average of both active
and passive task composite scores).

Because this was the first time the computerized
MTPB had been used extensively, periodic equip-
ment failures were expetienced in five of 120 ses-
sions. In these cases, the session was restarted at the
closest 15-minute interval to the time of the failure.
Equipment failure on Session 1 of D2 for Group 2
(Day shift on Thursday of the 2-2-1 week) resulted
in loss of the entire two hours of data. Performance
during this session was estimated utilizing mean
substitution computed from means for each task
during day shifts, Session 1 on days CD1, D1,
CD2, CD3, and CD4, which provided control for

10

time of day and learning effects. This was done only
after analysis of the impact of the estimate on the
overall outcome of the MANOVA was determined
to have no effect. To assess this, MANOVAs were
conducted on the data 1) without Group 2, 2)
without D2, 3) without Session 1, and 4) with
estimates for Group 2 on D2 Session 1. Each
MANOVA revealed the same pattern of significance
for main effects and interactions on composite
scores. Therefore, scores were estimated.

Critical Tracking data were analyzed separately.
The median lambda score (as a measure of a subject’s
control of the instability in the task) from the five
trials per session was used as the score for each
session.

Protocol. On the start date of the four-week
protocol, subjects reported to the laboratory from
0800 to 1200 for orientation and training on use of
the Vitalog physiological monitoring equipment.
For the remainder of the first week, subjects re-
ported to the laboratory for approximately one hour
at 0800 each day. Researchers met with each sub-
ject individually to assess any reported problems,
verify completion of logbooks, and download physi-
ological data to a computer from the Vitalog moni-
tors.

During the second week, subjects began a three-
week period of working 8.5 hour days at the labo-
ratory, Monday through Friday. Week 2 consisted
of straight day shifts from 0800-1630. Subjects
began training on the MTPB on the first day of the
second week. By the second day of that week, a daily
protocol was established. Table 3 presents a sample
daily protocol for the day shift. The procedures
were the same during the 2-2-1 schedule.

During the third week of the protocol, the sub-
jects worked a 2-2-1 shift (Melton, 1982). The
daily protocol detailed in Table 3 was followed
during all shifts. The 2-2-1 was scheduled as shown
in Table 4.

Subjects returned to working straight day shifts
(0800-1630) during the fourth and final week of
the protocol. Only two MTPB sessions were com-
pleted on the final day of the study, and the

remaining time was used for collecting equipment
and debriefing.


Table 41

Means and Standard Deviations for Active Composite Scores by Session
and Interval for the Night Shift

Session Interval 2 3 4 5 6 7
Session 1

Younger Mean | 502 506 §23 621 479 436
SD 101 58 38 39 71 167
Older Mean | 473 492 514 544 494 520
SD 7 39 44 30 41 60

Session1 Mean | 488 499 518 533_ | 486 478
sD 88 49 40 36 57 129

Session 2
Younger Mean | 523 505 530 503 472 407
SD 84 73 51 70 93 156
Older Mean |__509 472 513 508 406 448
sD 71 72 43 43 125 187
Session2 Mean | 516 488 522 505 439 428
sD 76 73 46 56 112 169
Session 3

Younger Mean | 530 509 522 509 427 391

sD 65 57 42 63 144 195
* Older Mean | 488 457 464 448 429 428
sD. 83 74 77 154 69 191

Session3 Mean |_509 483 493 479 | 428 409
$b. 76 70 67 119 110 189

Table 42

MANOVA Summary Table for Active Composite Scores by Session and 15-minute
Interval for the Night Shift

Degrees of Sums of Squares | Mean Squares

Source of Variation Freedom FE
| Age 1 10049.75 1049.75 NS.

Between Subjects 18 1510991.60 83943.98

interval (Workload Condition) 5 240085.83 48017.17 6.97**
| Age by Interval 5 67153.60 13430.72 NS.

Within Subjects 90 619814.07 6886.82

Session 2 84283.64 42141.82 6.98"*.
| Age by Session 2 25058.70 12529.35 N.S.

Within Subjects 36. 247477.07 6041.03

Interval by Session 10 101256.53 10125.65 2.66"

Age by Interval by Session 10 46250.83 4625.08 N.S.

Within Subjects. 180 685270.79 3807.06

*p<.05
**p<.001

A-21


Table 17
Means and Standard Deviations for Code Lock Solution Response Time

Study Day CDi Al A2 D1 D2 N cp2 cD3 cD4 | CDS

Session 1

Younger Mean 17.3| 149] 13.3] 14.0| 13.8] 148] 14.9 13.4 14.3 | 13.0

8) 7.9 5.8 3.8 5.3 4.6 45 5.8 4.3 3.6 3.1

Older Mean 20.1 17.8] 168] 147] 147] 142] 14.4 14.8 13.9 | 13.5

SD 6.9 5.9 47 3.0 3.6 3.1 3.3 3.6 29 2.5

Session 1_Mean 18.7 | 16.4 | 15,1 14.3 | 14.3] 145] 14.6 141 14.1 | 13.2

sD 7.4 5.9 45 4.2 41 3.8 46 3.9 3.1 2.8

Session 2

Younger__Mean 16.7 | 144] 134] 141) 142] 143] 14.1 13.4 16.0 | 13.0

SD 8.0 45 3.9 5.2

Older Mean 18.2] 153, 144] 150] 142] 163) 149 13.7 13.5 | 13.2

sD 6.9 3.9 3.1 3.0 3.0 45 2.7 2.8 2.0 2.3

Session 2 Mean 17.4| 148] 139) 145) 142] 15.3] 14.5 13.5 14.8 | 13.1

sD 7.3 4d 3.5 4.2 3.7 45 3.7 3.1 66 27

Session 3

Younger__Mean 15.4] 143] 135] 128] 13.7] 154] 13.3 12.5 12.8) 12.5

SD 6.6 42 45 3.4

“Older Mean 16.6 | 15.7 | 14.7] 143] 139] 167] 144 13.4 13.1 | 12.8

ES) 41 5.0 3.1 3.6 29 5.0 3.6 27 2.3 1.9

Session 3 Mean 16.0) 15.0] 14.1 13.6 | 13.8] 16.1] 13.8 12.9 12.9 | 12.7

sD 5.4 45 3.8 3.3 3.3 46 3.5 27 23 21

Table 18
MANOVA Summary Table for Code Lock Solution Response Time
Degrees of Sums of Squares | Mean Squares
Source of Variation Freedom F
‘Age 1 109.35 109.35 N.S.
Between Subjects 18 6977.95 387.66
: Day of Study 9 814.82 90.54 8.05"
Age by Day 9 96.79 10.75 N.S.
Within Subjects 162 1822.93 11.25
Session 2 70.38 35.19 5.76"
Age by Session 2 11.28 5.64 N.S.
Within Subjects 36 219.99 6.11
Day by Session 18 140.73 7.82 2.06"
| Age by Day by Session 18 79.74 4.43 N.S.
Within Subjects. 324 1228.37 3.79
*p<.05
**p<.001

AD



| Passive Task Composite Scores

4# Younger ¢ Younger SD -* Older 4 Older soy

600

550

Standardized Score

350

300
Session 9231281231291231291231231291 28
Day cbt | Al A2 D1 p2 N cb2 CD3 CD4 CDS
Day 2-2-1 Shift Day Shift

Figure 2. Means and Standard Deviations for Passive Composite Scores by
Age group and by Session.

Active Task Composite Scores

“&Younger_ ¢ Young SD Older 4 Oider SO

600

550

500

450

400

Standardized Score

gs0 b------enecccece

300
Session 923123123812812312312312312312 3

Day CD1|; Al A2 D1 D2 N | cbp2 cp3 CD4 CDS
Day | 2-2-1 Shift | Day Shift

Figure 3. Means and standard deviations for standardized Active Composite

Scores by Age group and by Session for those days included in the analysis.

B-4



Table 15

Means and Standard Deviations for Code Lock Solution Percent Correct

Study Day cp1

Al A2

D2

cb2 cD3

Session 1

Younger Mean

98.1

SD

15

Older Mean

96.4

sD.

40

Session 1 Mean

SD

3.1

Session 2

Younger__Mean

SD.

Older Mean

SD

Session 2 Mean

sp

Session 3

Mean

Younger
—

sD.

Older Mean

SD

Session 3 Mean

sD

Table 16

MANOVA Summary Table for Code Lock Solution Percent Correct

Source of Variation

Degrees of
Freedom

Sums of Squares

Mean Squares

m

1

303,23

303.23

Between Subjects

18

1994.15

110.79

Day of Study

54.93

6.10

Age by Day

59.24

6.58

Within Subjects.

527.21

3.25

Session

2.91

1.45

Age by Session

4.76

2.38

Within Subjects.

56.15

1.56

Day by Session

65.97

3.66

Age by Day by Session

43.37

2.41

Within Subjects

414.25

1,28

*p<.05
“*p<.001



day schedule for the fourth week. A synthetic work
environment was created by using the Multiple
Task Performance Battery (MTPB). The protocol is
represented in Table 1. (All times are based upon
the 24-hour clock notation.)

To assess the effect of the schedule on perfor-
mance, circadian rhythms, sleep/wake cycles, and
subjective experiences of mood and sleepiness, a
number of measures were collected during the
study: 1) Performance on the MTPB; 2) physiologi-
cal measures (core body temperature, heart rate,
and activity level); 3) daily logs of sleep/wake times
and sleep quality ratings; 4) neuroendocrine mea-
sures; and 5) mood and sleepiness scales. As previ-
ously noted, only the performance data are presented
here. The methodology is described in more detail
in the first report (Della Rocco & Cruz, 1995).

Subjects

Twenty male subjects were selected from two
different age groups for this study. Ten subjects
were between the ages of 30-35, with a mean age of
32.0 years. These subjects were termed the
“Younger” group. The second group of 10 subjects
was between the ages of 50-55, with a mean age of
52.4 years. These subjects comprised the “Older”
group. The younger age range was selected to be
representative of ATCSs after reaching full perfor-
mance level, and the older age range was selected
because ATCSs must stop controlling air traffic
when they reach age 56. Subject selection was
restricted to males in order to minimize cyclic
variations that might have interacted with or masked
circadian variations in female subjects. Subjects
were screened on a number of selection criteria,
including medical, intelligence test scores, and
drug, alcohol, tobacco and caffeine use (Della Rocco
& Cruz, 1995).

Human Subject Utilization Committee Reviews.
The study protocol and subject consent forms were
approved by the University of Oklahoma Institu-
tional Review Board. In addition, the study proto-
col was reviewed and approved through the research
review process of the FAA Office of Aviation Medicine.

Subject Demographics. Seventeen of the 20 male
subjects were Caucasian. Two subjects, one in each
age group, were African-Americans. One subject in
the Younger group was American Indian. Fifteen
subjects were married. Half of the subjects reported
prior military experience, eight of whom were in the
Older group. One subject held a Master’s degree,
eight subjects had completed a Bachelor’s degree,
and three subjects had completed an Associate’s
degree. Five additional subjects reported having
attended college. The remaining subjects had com-
pleted high school, with the exception of one sub-
ject who reported attaining a GED. Eight subjects
reported being employed at the time of their par-
ticipation in the study. Three subjects from the
Older group were retired. Six of the subjects re-
ported previous employment in an aviation-related
field. One subject in the Older group was a former
air traffic controller with the Air Force.

Apparatus

Multiple Task Performance Battery. The CAMI
MTPB was used to collect the measures of perfor-
mance. The MTPB provided an established ap-
proach to an intrinsically-motivating synthetic work
situation, requiring time-shared performance of
several tasks under varying workload conditions.
This is because time-sharing and variation in
workload are essential features of the ATC work
environment. The MTPB consisted of six tasks that
could be presented singly or in any combination.
The tasks were computerized to control all signal
presentations.

MTPB Equipment. The MTPB was based on a
Digital Equipment Corporation MicroVAX II cen-
tral processing unit and five TEKTRONIX Model
4125 color graphics workstations. The subject re-
sponse panels were custom designed to operate in
conjunction with the TEKTRONIX keyboard for
subject inputs. Response times on the input devices
ranged from 100 micro-seconds for the push but-
tons, to 10 milliseconds for responses from the
keyboard. The CRT’s dimensions were 15" w x
11.5" h (19" on the diagonal), with a graphics
resolution of 1280 x 1024 pixels.


et al. (1975) recommended restricting an
individual’s performance to something other than
the performance of complex tasks after a sleep
period as short as 3 hours until subjects achieved a
normal night of sleep.

Previous CAMI field studies on the 2-2-1 re
vealed the schedule to be an improvement over the
straight-5 rotation, but probably slightly more
stressful than straight days (Melton, 1982). A
recent field study compared a 10-hour schedule to
variations of the 2-2-1 and found that working a
schedule of four 10-hour shifts was not worse than
the 2-2-1 (Schroeder, Rosa, & Witt, 1995). The
present study compared the 2-2-1 to day shifts and
added laboratory-based controls and performance
measures to the knowledge base. Even though the
2-2-1 was found to substantially disrupt sleep
patterns, performance decrements were apparent
only on the night shift.

The findings in this study may be conservative in
estimating the disruptive effects of the 2-2-1 sched-
ule for the following reasons: 1) subjects only
worked one 2-2-1 rotation, whereas, in the ATCS
work force, working the schedule can be a chronic
exposure for a number of years; 2) instructions to
the subjects, as well as the study protocol, effec-
tively required that subjects restrict their life styles
to unusually stable patterns, although some activi-
ties, such as jogging and refereeing basketball games
were allowed; and 3) subjects were matched on
mental abilities, which would not necessarily be the
case in the work force, especially in the older age
range.

The present study failed to find as many age-
related differences as were predicted from the litera-
ture review. This could possibly be attributed to
the restriction in range, due to the strict subject
screening criteria used. Subjects were selected based
upon intelligence test data normed on newly hired
ATCS students in the FAA Academy. The average
age of the normative group was 25.2. Therefore, the
failure to identify a greater number of differences in
the age groups should not be generalized to the
broader work force.

21

SUMMARY AND
RECOMMENDATIONS

Findings presented from this study demonstrated
that the 2-2-1 shift schedule utilized by ATC
facilities substantially disrupted the sleep/wake cycle
(Della Rocco & Cruz, 1995). The disruption took
the form of a single phase delay of 2-hours, followed
by three phase-advances of both asleep and awake
times. The mean sleep duration was not signifi-
cantly affected until the quick-turn-around before
the night shift, when subjects were only able to
sleep for an average of 3.7 hours. Consequences of
the disruption were not substantially evident in the
MTPB performance until the night shift. Perfor-
mance was found to decline over the course of the
night shift and was particularly manifest in the
active task scores. Of particular note was the night
shift decrement in speed and accuracy on Target
Identification, a spatial perceptual task, measuring
abilities required in ATC.

The study was conducted using non-ATC sub-
jects in a laboratory environment; and therefore,
the results may be conservative estimates of the
effects of the 2-2-1. However, it was encouraging
that: 1) the sleep patterns were similar to field
studies with ATC personnel, and 2) that perfor-
mance levels were maintained on the MTPB for the
duration of the study. Thus, the results obtained
from this study should have applicability to serve as
a basic foundation for development of a research
Program on countermeasures and coping strategies.
For any resolution of the discussion of the impact of
the 2-2-1, the circadian, physiological, and addi-
tional data must be analyzed.

As a result of the findings in this study, three
areas were suggested for examination as candidates
for countermeasures. These included the develop-
ment of direct interventions to improve alertness on
the night shift (bright light exposure and/or nap-
ping), sleep management education for employees
designed to coincide with the basic tenants of the 2-
2-1 schedule design, and finally, schedule redesign

to minimize the number of quick-turn-arounds.


Table 31

Means and Standard Deviations for Red Warning Lights Percent Correct

Study Day cbt Al A2 1 b2 N cbd2 cD3
Session 1
Younger_Mean | 99.6 | 100.0 100.0 {| 100.0 99,7 | 100.0 | 100.0 | 700.0
sD 1.1 0.0 0.0 0.0 1.0 0.0 0.0 0.0
Older Mean | 100.0 | 100.0 | 100.0 100.0 99.5 | 100.0 | 100.0] 99.5
sD 0.0 0.0 0.0 0.0 1.5 0.0 0.0 1.5
Session1 Mean | 99.8| 100.0] 1 00.0 | 100.0 99.6 | 100.0 | 100.0 | 99.8
sD 0.8 0.0 0.0 0.0 12 0.0 0.0 1
Session 2
Younger Mean | 100.0 [ 100.0 | 100.0 99.3 | 98.3 | 400.0] 100.0 | 99.4
SD 0.0 0.0 0.0 2.3 4.0 0.0 0.0 1.4
Older Mean | 99.5 | 100.0 | 100.0 100.0 | 100.0 | 100.0 | 100.0 | 100.0
$D. 15 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Session 2 Mean | 99.8 | 100.0 100.0 99.6 | 99.2 | 100.0] 100.0] 99.7
sD 14 0.0 0.0 16 29 0.0 0.0 1.0
Session 3
Younger Mean | 99.1] 100.0 100.0 99.7 99.8 | 100.0 98.6 | 100.0
SD 3.0 0.0 0.0 1.0 0.8 0.0 3.2 0.0
Older Mean | _99.7 | 100.0 [ 100.0 99.5 | 100.0 | 100.0 | 100.0 100.0
sD 1.0 0.0 0.0 1.5 0.0 0.0 0.0 0.0
Session 3 Mean | 99.4 | 100.0 100.0 99.6 | 100.0 | 100.0 | 99.3 | 100.0
sD 2.2 0.0 0.0 1.2 0.6 0.0 2.3 0.0
Table 32
MANOVA Summary Table for Red Warning Lights Percent Correct
Degrees of Sums of Squares | Mean Squares
Source of Varlation Freedom
Age 1 8.53 8.53
Between Subjects 18 72.08 4.00
Day of Study 9 16.09 1.79
| Age by Day 9 8.18 91
Within Subjects 162 194.21 1.20
Session 2 5.34 2.67
| Age by Session 2 7.65 3.83
Within Subjects 36 72.85 2.02
Day by Session 18 22.87 1.27
Age by Day by Session 18 30.39 1.69
Within Subjects 324 410.68 1.27
“p<.05
**p<.001



Table 33

Means and Standard Deviations for Red Warning Lights Response Time

Study Day cp1 Al A2 Di D2 N_ | CD2 | cD3 cbD4 | CDS
Session 1
Younger Mean | 1.8 1.7 1.6 0.6 1.6 17 1,7 1.7 1.7 2.0
SD] 04 04 0.3 0.4 0.5. 0.6 0.5 0.5 0.4 0.8
Older Mean | 1.9 2.0 1.6 1.7 1.8 1.6 1.7 1.8 1.6 1.8
SD] 04 0.3 0.4 0.3 04 0.3 0.4 0.4 0.3 0.5
Session1 Mean | 1.8 1.9 1.6 1.7 1.7 1.7 17 1.7 1.6 1.9
SD] 0.4 04 0.3 0.3 0.4 0.5 0.4 0.5 0.4 0.7
Session 2
Younger Mean} 1.6 1.6 17 1.7 21 1.9 1.9 2.2 2.3 1.8
SO] 04 0.3 0.4 07 11 0.6 0.7 1.3 15 06
Older Mean | 2.0 1.9 1.9 1.8 1.7 21 17 1.8 1.7 1.9
SD | 06 0.4 0.6 0.4 0.4 0.7 0.3 0.3 0.4 0.3
Session 2Mean| 1.8 1.8 1.8 1.8 19 2.0 1.8 2.0 2.0 1.8
SD] 05 A 5 5 9 & 5 9 AP 5
Session 3
Younger Mean | 1.9 1.6 1.5 17 2.0 2.0 2.0 2.0 2.0 18
SD | 06 0.3 0.4 0.7 1.2 0.5 0.9 0.9 0.5 06
fe Older Mean | 1.8 1.9 1.7 18 1.7 2.0 1.7 1.8 1.9 17
SD] 0.3 05 0.4 0.4 0.4 0.6 0.4 0.5 0.3 0.4
Session 3 Mean | 1.9 1,7 1.6 1.8 1.9 2.0 1.9 19 1.9 17
SD] 05 0.4 0.4 0.6 09 0.5 0.7 0.7 0.4 05
Table 34
MANOVA Summary Table for Red Warning Lights Response Time
Degrees of Sums of Squares | Mean Squares
Source of Variation Freedom F
| Age 1 04 04 NS.
Between Subjects 18 97.75 5.43
Day of Study 9 2.04 23 N.S.
| Age by Day 9 4.75 53 2.66"
Within Subjects. 162 32.10 .20
Session 2 1.95 97 6.83*
Age by Session 2 10 05 N.S.
Within Subjects. 36 5.13 14
Day by Session 18 3.74 21 N.S.
| Age by Day by Session 18 2.62 15 NS.
Within Subjects 324 44.70 14
*p<.05
“*p<.001



Red Warning Lights

Younger * Young SD -*-Older 4 Older SD J

108
104
100

96
92
88
84
80

Percent Correct

76
72
68

64
Session 123123123123123123123123123123
Day CD1 | Al A2 D1 b2 N || cD3 CD4 CD5
Days 2-2-1 Days2

Figure 14. Means and standard deviations for Red Warning Lights
Percent Correct by Age group by Session from day CD1 (week 2) to day
CDS5 (week 4).

Red Warning Lights

Younger ¢ Young SD -*-Older 4 Older SD j

Response Time (Seconds)

Session 1.23123123123129129128125128123
Day | Al A2 D1 D2 N | CD2 CD38 CD4 CD5
Days1 2-2-1 Days2
Figure 15. Means and standard deviations for Red Warning Lights

Response Time by Age group by Session from day CD1 (week 2) to day
CD5 (week 4).

B-10



Table 9

Means and Standard Deviations for MTPB Active Composite Scores

SHIFT DAY 2-2-1 DAY
Study Day cD1 Al A2_| D1 D2 N_ | cb2 cD3 cb4 | CDS
Active Composite
Session 1
Younger Mean 481 497 523 519 | 518 492 | 504 506 496 525
1) 48 42 33. 36 40 66 51 53 62 42
Older Mean 452 | 472 | 472 494 | 506] 504| 494 513 513 514
SD. 55 56 56 35 37 37 49 51 37 27
Overall Mean 467 484 498 506 | 512 498 | 499 510 505 520
sD 53 50 52 37 38 53 49 51 50 35.
Session 2
Younger Mean 494 501 512 524 | 494 485 | 490 510 471 514
SD 51 43 Al 40 59 61 73 55 127 38
Older Mean 474 484 | 496 494 | 508 470 | 495 514 514 516
sD 54 37 28 50 Al 86 40 33. 23 49
Overall Mean 484 493 504 509 | 501 478 | 493 512 492 §15
sD 52 40 35. 47 50 82 57 44 92 43
Session 3
Younger Mean 496 | 509 | 523 525 | 506| 474] 507 511 502 514
sD 40 37 37 45 66 93 55 61 50 52
“Older Mean 478 473 496 509 | 504 454 | 511 517 522 516
SD 45 66 54 34 38 89 38 49 30 46
Overall Mean 487 491 510 517 | 505 464 | 509 514 512 514
sD 43 55 AT 40 53 89 46 54 41 48
Table 10
MANOVA Summary Table for Active Composite Scores
Degrees of Sums of Squares | Mean Squares
Source of Variation Freedom F
Age 1 9986.13 9986.13 N.S.
Between Subjects 18 1025358.94 56964.39
Day of Study 9 91672.86 10185.87 6.50°*
‘Age by Day 9 42891.19 4765.69 3.04"
Within Subjects 162 253854.70 1567.00
Session 2 4781.51 890.75 N.S.
Age by Session 2 2369.08 1184.54 N.S.
Within Subjects 36 27502.95 763.97
Day by Session 18 26540.50 1474.49 2.33"
Age by Day by Session 18 11069.58 614.98 N.S.
Within Subjects 324 204920.50 632.47
*p<.05
**p<.001

A-S



Critical Tracking

= Pre-MTPB Young -*Post-MTPB Young -+Pre-MTPB Old -« Post-MTPB Old

6

5.5

5

45

Lambda Score

4

3.5

Day ay Al A2 D1 D2 N || CD2 CD38 CD4 CD5
Days 2-2-1 Shift Days2

Figure 20. Means for Median Lambda Scores on Critical Tracking by
Age Group for Pre-‘and Post-workday performance from day CD1
(week 2) to day CD5 (week 4).

B ‘WYUS. GOVERNMENT PRINTING OFFICE: 1996 - 760-002/40009
-13



control subjects’ meal times or the content of meals,
thereby ignoring the potential confound of a pos-
sible “post-lunch dip” in performance. Monk (1990)
echoed Damos’ criticism regarding practice effects
and added that, “... differences in such chance
factors as the subjects’ motivation, perception of
the task, and distraction by some non-task event,
can tender performance measurement notoriously
inaccurate” (p.186). He characterized the circadian
performance rhythms, however, as non-trivial, ro-
bust fluctuations of significant magnitude, when
adequate care is given to methodological measure-
ment problems.

Phase Shift Studies

The relationship between circadian rhythm dis-
ruption and performance has been examined in
phase shift studies that were designed to modify the
phasic relationship between circadian rhythms and
time. A review of the literature was provided in
more detail in the first report of this series (Della
Rocco & Cruz, 1995). In a series of studies, Taub
and Berger (1973) phase-shifted sleep periods and
examined effects on performance. Compared to
baseline sleep periods, phase-shifted experimental
conditions resulted in performance deficits on two
tasks, calculation and vigilance. Other studies, par-
ticularly those on jet-lag (Wegmann & Klein, 1985;
Monk, Moline, & Graeber, 1988) indicated that
interruptions of sleep were more detrimental to
performance than sleep loss.

Of particular interest to the present study were
the investigations of researchers from the FAA’s
Civil Aeromedical Institute during the mid-1970s.
The Multiple Task Performance Battery (MTPB)
provided a synthetic work environment in which
the influence of various stressors, such as a phase
shift of the sleep/wake cycle, on complex task
performance could be systematically investigated in
the laboratory. Higgins, et al. (1975) reported the
effects of a 12-hour phase shift in the work day.
Performance on the MTPB revealed that decre-
ments in performance were found on the day follow-
ing the short three-hour sleep period; an 8% drop
from the first session of the day to the last. In
addition, performance on the first three days fol-

lowing the phase shift was relatively high during
four of the five one-hour MTPB sessions, but fell off
significantly during the last session. The end-of-
the-day drop in performance was eliminated by
days 4-6 after the phase shift, with little variation
across each day. A reversal of the diurnal pattern of
performance was shown during the last three days of
the study such that the performance peak after the
phase shift was shifted 12 hours from the pre-phase
shift peak. MTPB scores were lower, in general, on
the last three days of the study, probably as a result
of an end-of-the-study effect.

In a follow-up study, Higgins, et al. (1976)
explored a laboratory analog of both a six-hour
phase advance and a six-hour phase delay. Perfor-
mance on the MTPB revealed that the phase-
advanced group had the greatest deficit in
performance while the phase-delayed group had the
best post-phase-shift performance. However, there
was a confound in the number of hours slept after
the “flight” to London, making it difficult to gener-
alize these effects.

A Simulated Work Environment—The Multiple
Task Performance Battery

Time-sharing ability and the ability to perform
under varying workloads are critical to performance
in both the cockpit and air traffic control. The
MTPB was established to provide a laboratory
approach to studying complex performance under
these conditions. The MTPB provides a motivating
synthetic work environment in which workload can
be varied and performance under different experi-
mental conditions can be measured. Originally
developed to study the performance of air crews, the
battery is well known in the performance literature
through the work of researchers such as Alluisi,
Chiles, Adams, Mertens, and Morgan.

In 1956, the Aerospace Medical Research Labo-
ratories at Wright-Patterson Air Force Base began a
program of research on crew performance in aircraft
applicable to advanced systems of the future (Chiles,
Alluisi, & Adams, 1968). At that time, the United
States Air Force (USAF) was developing aircraft
nuclear propulsion (ANP) that would provide a
greatly-increased range of flight operations. The


APPENDIX B
FIGURES

B-1



Table 43
Means and Standard Deviations for Critical Tracking

Younger Older Overall
Mean sD Mean SD Mean SD
cD1 :
Pre 4.08 -70 3.88 72 3.98 70
Post 4.13 54 4.28 42 4.20 48
Al
Pre 3.99 66 4.24 45 4.12 56
Post 4.05 61 3.83 74 3.94 67
A2
Pre 4.25 62 4.29 56 4.27 58
Post 4.17 77 4.28 66 4.22 -70
D1
Pre 4.21 69 4.61 57 4.41 65
Post 4.31 71 4.44 70 4.38 69
D2
Pre 453 64 4.31 70 4.42 66
Post 4.39 69 4.53 71 4.46 68
N
‘*
Pre 4.51 57 4.46 68 4.48 61
Post 4.13 1.05 4.19 .73 4.16 88
cD2
Pre 4.56 62 4.41 58 4.48 59
Post 4.19 69 4.74 62 “4.46 70
CD3
Pre 4.55 82 4.57 65 4.56 72
Post 4.62 69 4.74 64 4.68 -65
cD4
Pre 4.69 90 4.85 86 4.77 86
Post 4.66 74 4.71 81 4.68 76
cps
Pre 4.81 67 4,72 57 4.76 61
Post 4.91 82 4.93 77 4.92 77

A-22



i |

Passive Composite Scores. Figure 2 and Table 7
Present descriptive statistics for the Passive Com-
Posite Scores. Table 8 presents the MANOVA
summary table for the Passive Composite Scores,

Results of the 2 x 10 x 3 MANOVA for Passive
Composite Scores revealed significant interactions
for Age by Day, F(9, 162) = 3.45, p<.001, and Day
by Session, F(18, 324) = 2.03, p<.05. Planned
multiple comparisons on the Age by Day interac-
tion failed to attain significance. However, planned
multiple comparisons on the Day by Session inter-
action revealed that performance on the passive
tasks declined significantly over the course of the
Night shift. Paired t-tests among the sessions of the
Night shift revealed that the Passive Composite
Scores for Session 2 (M = 493), £(18) = 3.82, p<.05,
and Session 3 (M = 479), (18) = 3.75, B<.05, were
significantly lower than scores during Session 1 (M
= 510). No significant differences were found be-
tween the sessions on the day before and the day
after the quick-turn-arounds, A2-D1 and D2-N,
respectively, or on the comparison of D2 to CD2.
“« Active Composite Scores, Figure 3 and Table 9
Present descriptive statistics for the Active Com-
Posite Scores. Table 10 Presents the MANOVA
summary table for the Active Composite Scores.

Results of the 2 x 10 x 3 MANOVA for Active
Composite Scores revealed a significant interaction
for Age by Day, F(9, 162) = 3.04, p<.05, and for
Day by Session, F(18, 324) = 2.33, p<.05, and a
main effect for Day of the study, E(9, 162) = 6.50,
R<.001, Planned multiple comparisons for the Age
by Day interaction failed to reach statistical signifi-
cance. Planned paired t-tests comparing the Day by
Session interaction revealed no significant differ-
ences between sessions on A2 and D1 on the first
quick-turn-around, or between D2 and N Sessions
1 and 2, or between D2 and CD2. Active Compos-
ite Scores were significantly lower, however, on N
Session 3 (M = 464) than D2 Session 3 (M = 505),
(18) =3.51, p<.05, Multiple comparisons for the
main effect of Day revealed that performance on the
Night shift (M = 480) was significantly lower than
performance on D2, the prior Day shift (M = 506),
1(18) = 3.17, p<.05,

14

MTPB Individual Tasks

This section presents the data analyses of perfor-
mance of each of the six individual tasks in the
MTPB: Arithmetic, Code Lock, Target Identifica-
tion, Probability Meters, Red Warning Lights, and
Green Warning Lights. For each task, measures of
accuracy (Percent Correct) and speed (Response
Time) were reported here, Code Lock was composed
of two parts: Solution and Recall. Data for accuracy
and speed were teported for each part separately.

Arithmetic. Figure 4 and Table 11 Present de-
scriptive statistics for Arithmetic Percent Correct.
Table 12 presents the MANOVA summary table
for Arithmetic Percent Correct.

Results of the 2 x 10 x 3 MANOVA for Arith-
metic Percent Correct revealed a significant interac-
tion for Age by Day, E(9, 162)=2.01, p<.05, and
significant main effects for Day, F(9, 162)=6.25,
R<.001, and Session, F(2, 36)= 7.39, R<.05. Planned
multiple comparisons for the Age by Day interac-
tion and main effect of Day failed to reach statistical
significance. The comparisons for main effect of
Session revealed that Arithmetic Percent Correct
improved significantly between Session 1 (M=95.1)
and Session 3 (M=96.1), 1(18) = 3.47, R<.05.

Figure 5 and Table 13 Present descriptive data
for Arithmetic Response Time. Table 14 presents
the MANOVA summary table for Arithmetic Re-
sponse Time.

Results of the 2 x 10 x 3 MANOVA for Arith-
metic Response Time revealed a significant interac-
tion for Age by Day of the study, F(9, 162) = 4.07,
R<.001, as well as significant main effects for Day,
E(9, 162) = 3.27, R<.001, and Session, F(2, 36) =
12.86, p<.001. Planned comparisons on the inter-
action of Age by Day, as well as the main effect for
Day failed to reach statistical significance, How-
ever, as with Arithmetic Percent Correct, perfor-
mance improved after the first Session. Response
Times. were significantly faster during Session 2 (M
= 8.2 seconds), £(18) = 4.40, R<.05, and Session 3
(M = 8.2 seconds), 1(18) = 3.61, p<.05) than
during Session 1 (M = 8.4 seconds) .

Code Lock. The Code Lock Task involved two
Parts, solution and recall. Percent correct and re-
Sponse times are presented for each of these parts



Passive Composite Scores by Interval

~* Session 1 Younger -* Session 2 Younger -©-Session 3 Younger
~* Session 1 Older -*-Session2 Older _- Session 3 Older
8
g
E
i=
s
a
15-Minute Interval
Night Shift

Figure 18. Means of the Passive Composite Scores by Age group and by
15-minute Interval for the three sessions of the Night shift.

Standardized Scores

400
375

350
2

Active Composite Scores by Interval

+ Session 1 Younger -® Session 2 Younger -@ Session 3 Younger
Session 1 Older + Session2 Older © Session 3 Older

15-Minute Interval

Figure 19. Means of the Active Composite Scores by Age group and by
15-minute Interval for the three sessions of the Night shift.

B-12



Figure 11 and Table 25 presents descriptive
statistics for Target Identification Response Time.
Table 26 presents the MANOVA summary table
for Target Identification Response Time.

Results of the 2 x 10 x 3 MANOVA revealed a
significant three-way interaction for Age by Day by
Session, F(18, 306) = 1.80, p<.05, and a significant
two-way interaction for Day by Session, F(18, 306)
= 2.50, p<.001. In addition, significant main ef-
fects were found for Day, F(9, 153) = 2.54, p<.05,
and Session, F(2, 34) = 6.14, p<.05. Planned
multiple comparisons for the Day by Session inter-
action revealed a significant slowing of the Re-
sponse Time for Target Identification during Session
3 of the Night shift (M = 2.7 seconds) compared to
Session 3 of the previous Day shift, D2, (M = 2.2
seconds), 1(18) = 3.84, p<.05. Planned compari-
sons on the Day main effect revealed no significant
differences. Comparisons for the Session main effect
revealed that Target Identification Response Time
was significantly slower during Session 2 (M = 2.2
seconds) than during Session 1 (M = 2.1 seconds),
(18) = 2.75, p<.05, across the duration of the study.

Probability Meters. Figure 12 and Table 27
presents descriptive statistics for Probability Meters
Percent Correct. Table 28 presents the MANOVA
summary table for Probability Meters Percent Cortect.

The results of the 2 x 10 x 3 MANOVA for
Probability Meters Percent Correct revealed only a
significant Day by Session interaction, F(18, 324)
= 1.90, p<.05. Multiple comparisons for the Day
by Session interaction revealed no significant differ-
ences on Probability Meter monitoring accuracy
measures comparing Sessions on the days before and
after both quick-turn-around shift changes or the
first day shift after the 2-2-1.

Figure 13 and Table 29 present descriptive sta-
tistics for Probability Meters Response Time. Table
30 presents the MANOVA summary table for Prob-
ability Meters Response Time.

Results of the 2 x 10 x 3 MANOVA revealed
significant two-way interactions for Age by Day,
E(9, 162) = 2.65, p<.05, as well as Day by Session,
E(18, 324) = 2.71, p<.001. Planned multiple com-
parisons for the Age x Day and the Day x Session

16

interactions revealed no significant differences for
Probability Meter Response Times for the quick-
turn-around shifts or the first Day shift after the 2-2-1.

Red Warning Lights. Figure 14 and Table 31
present descriptive statistics for Red Warning Lights
Percent Correct by Age group, Day of the study,
and Session. Table 32 presents the MANOVA
summary table for Red Warning Lights Percent
Correct. No significant differences in performance
were found on this task due to Age, Day, or Session.
Performance on this task was maintained at nearly
100% accuracy for the duration of the study.

Figure 15 and Table 33 present descriptive sta-
tistics for Red Warning Lights Response Time.
Table 34 presents the MANOVA summary table for
Red Warning Lights Response Time.

Results of the 2 x 10 x 3 MANOVA for Red
Warning Lights Response Time revealed that, al-
though there was no significant performance decre-
ment in Percent of Correct responses on this task,
there were significant decrements on the Response
Times. Analyses resulted in a significant Age by
Day interaction, F(9, 162) = 2.66, p<.05, and a
significant main effect for Session, E(2, 36) = 6.83,
p<.05. Planned multiple comparisons failed to reach
statistical significance for the Age by Day interac-
tion; however, for the Session main effect, Response
Times to Red Warning Lights were significantly
faster during Session 1 (M=1.73 seconds) than
either Session 2 (M=1.87 seconds), (18) = 3.13,
p<.05, or Session 3 (M=1.83 seconds), (18)
2.65, ps.05.

Green Warning Lights. Figure 16 and Table 35
present descriptive statistics for Green Warning
Lights Percent Correct.Table 36 presents the
MANOVA summary table for Green Warning Lights
Percent Correct, Results revealed that, as with the
Red Warning Lights, there was no significant per-
formance decrement on accuracy of responding to
the Green Warning Lights.

Figure 17 and Table 37 present descriptive sta-
tistics for Green Warning Lights Response Time.
Table 38 presents the MANOVA summary table
for Green Warning Lights Response Times.


reported a distinction between the more “strictly
mental” processes and the more “motor” functions.
Performance on mental activities reached a maxi-
mum later in the morning and showed decrements
in the afternoon. Performance of motor tasks, how-
ever, demonstrated a continuous increase in effi-
ciency over the course of the day. “Mental fatigue”
that accrued over the course of the day was postu-
lated to be the controlling mechanism for the
observed decline in mental performance.

A major researcher to address the issue initially in
the 1930s, was Kleitman (1963). Kleitman re-
ported a rise in performance from early morning to
a peak in the afternoon and then a decline toward
the evening hours. Concurrent body temperature
measurements that tracked the performance pat-
terns suggested to Kleitman that there was a causal
relationship between the two (Folkard & Monk,
1985). Thus, he proposed the Basic Rest-Activity
Cycle (BRAC) theory. Kleitman utilized simple
repetitive tasks (e.g. card dealing) for these studies.
Many studies after Kleitman focused upon the
parallel relationship between various performance
measures and the circadian temperature curve
(Folkard & Monk, 1985).

However, at least two lines of evidence ran counter
to such a simplistic relationship (Folkard & Monk,
1985). The first was the “post-lunch dip,” an
observed decline in performance following the mid-
day meal. The second was a decrease in performance
over the day on memory tasks such as digit span.
Blake (1967) investigated performance rhythms in
a number of “immediate information-processing
tasks” (cited in Colquhoun, 1982). These tasks
included card sorting, vigilance, letter cancellation,
serial reaction time, calculations, and digit span.
Blake demonstrated that performance appeared to
track the increase in body temperature (apart from
a post-lunch dip in performance) on all tasks except
digit span. Peaks in performance on all other tasks
were found to reach a maximum around 2100,
which coincided with the peak in body tempera-
ture. Performance on digit span, however, peaked in
the morning and showed a continuous decline over
the course of the day, with the lowest measures
found around 2100.

Folkard and Monk (1985) reviewed studies on
working memory. They characterized working
memory tasks as involving both short-term storage
and the processing of information. Therefore, such
tasks might be expected to show a different pattern
than short-term memory tasks alone. In fact, data
from Laird (1925) on mental arithmetic (cited in
Colquhoun, 1982) and Folkard (1975) on two
verbal reasoning tasks demonstrated a pattern in
which peak performance was found around midday.
Task demands were found to impact the findings,
however. Folkard systematically varied the memory
load involved with a visual search task. Performance
on the visual search task in a low load condition
paralleled the daily curve of body temperature.
However, with increasing memory load, the peak
shifted toward earlier in the day and was reversed in
the high load condition compared to the low load
condition. Folkard and Monk (1985) found that
performance on more complex tasks of immediate
memory, requiring subjects to recall information
presented in passages of prose, declined over the
day.

Rutenfranz, Aschoff, and Mann (1972) found
signal detection and mean response time to signal
detection to parallel the course of the body tem-
perature rhythm. Klein and Wegmann (1974) mea-
sured psychomotor, cancellation, addition, and
flight simulator performance over 124 hours. They
found that these measures also appeared to parallel
body temperature.

These studies demonstrated a variety of circadian
performance rhythms that can vary with changing
demands of the task. The degree to which the
variations have practical significance has been ques-
tioned by Damos (1989). In a selective review of
circadian effects on simple information processing
tasks for the Navy, she concluded that the effect did
not appear to be large but, due to methodological
problems in existing studies, the extent of the
effects may have been masked. She noted three
common methodological flaws in this kind of re-
search: 1) failure to train subjects on a task before
collecting data, thereby confounding any time-of-
day effect with practice effects; 2) assuming equiva-
lence of subjects’ circadian cycles; and 3) failure to


Table 29

Means and Standard Deviations for Probability Meters Response Time

Study Day cb1 Al A2 Di D2 N cD2 | CD3 cb4 | CDS
Sesslon1
Younger Mean |__10.4 9.3 9.1 9.9 9.3 9.3 9.4 9.4 9.5 10.3
sD. 3.3 2.9 2.2 3.8 3.2 3.1 2.8 3.4 3.5 3.7
Older Mean | 10.3] 10.5] 10.9] 10.0] 10.1 10.1 | 10.0] 10.4 9.8 10.0
sD. 26 3.8 45 3.0 3.8 40 3.7 41 3.6 46
Session 1 Mean | 10.4 9.9 | 10.0 9.9 9.7 9.7 9.7 9.9 9.6 | 10.1
sb 29 3.3 3.6 3.3 3.4 3.5 3.2 3.7 3.5. 41
Session 2
Younger Mean] 9.7] 88| 91{ 94] 101[ 98] 100] 98] 106 9.8
SD 2.8 25 2.6 3.2 3.8 3.7 3.2 3.9 45 3.7
Older Mean| 11.5] 103] 10.8| 10.0| 10.2| 11.3) 10.7] 10.4 9.4 9.8
sD. 2.8 3.3 3.6 3.9 3.5 47 45 42 4.0 47
Session 2 Mean | 10.6 9.6 9.9 9.7 | 10.1] 10.6 | 10.4] 10.1 10.0 9.8
sD 2.9 3.0 3.2 3.5 3.6 4.2 3.8 3.9 42 41
Session 3
Younger Mean 9.9 9.0 8.7 91 9.6 | 10.9) 10.1 9.8 10.4 9.9
sD. 28 2.5 2.5 2.6 4.0 3.9 3.9 45 4.0 40
Older Mean| 10.5] 11.3} 109] 11.0] 10.3] 12.5 | 10.3 9.8 9.6 | 10.2
sD. 3.2 3.4 43 43 43 5.7 45 45 4.4 5.1
Session 3 Mean | 10.2 | 10.2 9.8 | 10.1 9.9 | 11.7 | 10.2 9.8 10.0 |_ 10.1
sD 29 3.2 3.6 3.6] 41 48 41 44 41 45
Table 30
MANOVA Summary Table for Probability Meters Response Time
Degrees of Sums of Squares | Mean Squares
Source of Variation Freedom FE
[ Age 1 85.59 85.59 NS.
Between Subjects 18 6731.55 373.97
Day of Study 9 35.06 3.90 N.S.
| Age by Day 9 74.46 8.27 2.65"
Within Subjects 162 505.53 3.12
Session 2 8.74 4.37 N.S.
| Age by Session 2 2.17 1.08 N.S.
Within Subjects 36 51.36 1.43
Day by Session 18 49.83 2.77 2.71°*
| Age by Day by Session 18 34.36 1.91 N.S.
Within Subjects 324 330.92 1,02
*p<.05
**n<.001

A-I5S



Table 5

Means and Standard Deviations for MTPB Total Composite Scores

Study Day coi | ai [| a2 | pi [ p27] N | cb2 | cb3 | cb4 | cps
Totat Composite

Session 1

Younger Mean 488 | 504 | 518 514| 514) 504] 509 509 505, 514
SD 36 28 27 32 36 43 34 43 45 41

Older Mean 471 474 | 481 498 | 501 504 | 498 506 511 510

sD 31 43. 40 22 33 28 37 38 25 29

Session1 Mean | 479| 489[ 500|~ 506/ 508| 504 | 503| 507 508 512
sp 35 39 38 28 | 35 35 35 40 36 35

Session 2

Younger Mean 500 | 508} 511 516 | 491 495 | 498 502 471 508

SD 30 29 31 36 64 55 48 62 113 40

Older Mean | 480] 487| 486| 495[ 506] 476] 498] 506 5it 510
SD 31 27 32 34 30 60 32 31 20 35

Session 2 Mean 490 | 499] 499 505 | 498 | 485| 498 504 491 509

sD 31 29 33 36 49 57 40 48 82 37

Session 3
Younger Mean 496 | 514} 521 519 | 503} 484/ 502 505 501 509

SD 32 26 27 38 61 60 46 59 38. 40

Older Mean | 482] 478| 494/ 498] so3| 4s59/ 506| 509 514 512

SD 30 46 42 36 31 76 33 33 29 32

Session3Mean| 489} 496| 508| 509/ 503| 472| 504] 507 508 510
SD 31 40 37 37] 47 68 39 47 34 36

Table 6
MANOVA Summary Table for MTPB Total Composite Scores
Degrees of | Sums of Squares Mean F
Source of Variation Freedom Squares
Age 1 670614.83 37256.38 N.S.
Between Subjects 18 12115.37 12115.37
Day of Study 9 36442.37 4049.15 4.60"*
Age by Day 9 32867.15 3651.91 4.15°*
Within Subjects 162 142542.03 879.89
Session 2 1574.64 787.32 N.S.
| Age by Session 2 1648.00 824.00 NS.
Within Subjects, 36 20209.80 561.38
Day by Session 18 17553.38 975.19
2.76"*
| Age by Day by Session 18 7406.50 411.47 N.S.
Within Subjects 324 114622.09 353.77
*p<.05
**p<.001

A-3



SuirT Work, AGE, AND PERFORMANCE: INVESTIGATION OF THE 2-2-1 SHirT
SCHEDULE Usep IN Air TRAFFIC CONTROL FACILITIES
II. Lasorarory PERFORMANCE MEASURES

INTRODUCTION

This report is the second in a series on the
findings from a study on the 2-2-1 shift schedule
used in the Federal Aviation Administration’s (FAA)
air traffic control facilities, The 2-2-1 is a counter-
clockwise, rapidly rotating shift schedule that re-
quires employees to work two afternoon shifts,
followed by two morning shifts, and finally, a night
shift, within a five-day period (Price & Holley,
1990). Little evidence was available in the litera-
ture about the relationship between performance
and counterclockwise, rotating schedules.

This laboratory-based study was designed to
empirically investigate the extent to which the 2-2-
1 schedule resulted, or failed to result, in sleep and
circadian rhythm disruption, performance decre-
ments, and changes in subjective measures of sleepi-
ness and mood. Age was investigated as a factor in
the study utilizing two different age groups to
examine the response to the shift schedule. The
background on the research issues related to air
traffic control specialists (ATCSs) and the sleep data
was provided in the first report of this series (Della
Rocco & Cruz, 1995). This report presents data on
the performance measures.

The ATCS’s job requires complex cognitive per-
formance. This includes activities such as monitor-
ing complex traffic patterns to ensure aircraft
separation through application of established rules
and procedures, resolution of potential aircraft con-
flices, traffic sequencing, assessing developing
weather patterns, and providing appropriate ad-
justments to routing. In 1987, Computer Technol-
ogy Associates, Inc. (CTA) completed a job task
analysis. They identified 14 cognitive/sensory at-
tributes required for performing the tasks of ex-
treme or high criticality associated with performance
of computer and radar workstation jobs in the
current ATC system. These included coding, move-
ment detection, spatial scanning, filtering, image/

pattern recognition, decoding, visualization, short-
term memory, long-term memory, deductive rea-
soning, inductive reasoning, mathematical/
probabilistic reasoning, prioritizing, and verbal
filtering. Many of these cognitive abilities have
demonstrated circadian variations and susceptibil-
ity to circadian disruption (Monk, 1990). There-
fore, an ATCS’s performance of tasks requiring
these specific skills and abilities could be expected
to 1) demonstrate circadian variability and 2) be
susceptible to the disruptive effects of shift work on
circadian rhythms.

Several theoretical lines of investigation relate to
the question of the relationship between age and
performance of complex tasks under a stressor such
as shift work. Specifically, these include circadian
rhythms (biological, sleep/wake, and performance),
disruption of those rhythms due to shift work, and
their relationship to an employee’s performance.

Performance Rhythms

Evidence of time-of-day effects associated with
performance dates back to the late 1800s and early
1900s. Research on biological rhythms during this
century has elucidated some of the parameters of
these effects. A review of this research follows with
particular attention paid to the types of tasks used
to measure performance in the present study.

Ebbinghaus (1885) reported that learning non-
sense syllables was more rapid in the morning (cited
in Colquhoun, 1982). Other researchers of the
same era reported that slowest speed occurred in the
afternoon (cited in Colquhoun, 1982). Thus, by
the end of the 19th century, a pattern was described
in which performance was found to be better in the
morning (sometimes with a “warm-up” period re-
quired), while a trough in performance was de-
scribed after the midday meal in the afternoon.

Gates (1916) conducted a series of studies ad-
dressing the optimal time of day for teaching aca-
demic subjects (cited in Colquhoun, 1982). Gates


Arithmetic

~* Younger # YoungSD -*-Older 4 Older SD J

108
104
100
96
92
88
84
80
76

Percent Correct

72
68

64
Session 123123123123123123123123123123
Day CD1 | Al A2~ D1 D2 N \~ CD3 CD4 CD5

Days1 2-2-1 Days2

Figure 4. Means and standard deviations for Arithmetic Percent Correct by
Age group and by Session.

Arithmetic

‘Younger * YoungSD Older 4 Older SD j

Response Time (Seconds)

Session 123123123123123123123123123123

Day CD1 | Al A2 D1 D2 N ||CD2 CD3 CD4 CD5
Days1 2-2-1 Days2

Figure 5. Means and standard deviations for Arithmetic Response Time by
Age group by Session from day CD1 (week 2) to day CD5 (week 4).

B-5



Table 21

Means and Standard Deviations for Code Lock Recall Response Time

Study Day cD1 Al A2 DI D2 N cD2 cD3 cbD4 CDS
Session 1
Younger Mean |_5.7 49 45 48 4.8 5.6 49 5.0 5.3 5.0
sD. 18 1.6 4.2 1.0 1.0 1.8 1.4 17 1.7 1.8
Older Mean | 5.9 5.0 5.5 5.0 49 5.1 5.3 49 44 45
sD 15 13 1.5 1.2 1.4 1.4 1.8 1.8 1.2 1.0
Session 1 Mean 58 5.0 5.0 49 48 5.4 5.4 5.0 49 47
SD} 16 14 1.5 11 12 1.6 16 17 1.5, 1.4
Session 2
Younger Mean| 49 47 46 44 5.4 5.6 5.0 47 8.0 49
SD 1.4 1.0 0.9 1.0 18 23 1,7 12 9.4 1.0
Older Mean {5.4 5.2 5.4 5.4 49 6.2 48 49 49 45
sD V1 1.0 1.0 1.4 1.5 27 13 11 1.2 1.2
Session 2 Mean |_ 5.1 5.0 5.0 49 5.0 5.9 49 48 6.5 47
SD | 13 1.0 1.0 1.3 1.6 24 15 1.2 6.7 1,4
Session 3
Younger Mean | 5.0 46 4.4 44 5.0 5.6 5.0 48 5.4 49
sb 1.4 1.0 1.0 tA 1.2 17 1.4 13 1.3 1.4
‘4 Older Mean 5.4 5.6 47 46 5.4 7.0 49 46 4.3 47
sb 1.4 1.6 1.3 1.4 1.5 3.2 1.4 1.2 0.9 1.5
Session 3 Mean | 5.2 5.1 45 AS 5.2 6.3 5.0 47 49 48
sD 1.4 14 1.2 1.3 1.4 26 1.3 1.2 1.2 1.4
Table 22
MANOVA Summary Table for Code Lock Recall Response Time
Degrees of Sums of Squares | Mean Squares
Source of Varlation Freedom F
Age 1 72 72 N.S.
Between Subjects 18 772.78 42.93
Day of Study 9 66.94 7.44 2.92"
| Age by Day 9 66.80 7.42 2.91"
Within Subjects. 162 412.66 2.55
Session 2 3.14 1.57 NS.
| Age by Session 2 1.54 77 NS.
Within Subjects 36 102.57 2.85 :
Day by Session 18 52.02 2.89 N.S.
| Age by Day by Session 18 29.65 1.65 N.S.
Within Subjects 324 650.37 2.01
*p<.05
TMp<.001



Table 39

Means and Standard Deviations for Passive Composite Scores by Session and
15-Minute Interval for the Night Shift

Session interval 1 2 3 4 5 6 7 8
Session 1

Younger Mean | 525 521 506 | 510 | 532 | 509 | 515 513
SD] 40 25 40 48 13 30 33 41
Older Mean | 528 527 497 | 497 | 515 | 463 | 486 520
SD 20 14 57 47 36 64 57 26

Overall Mean | 527 | 524 | 501 | 504 523 | 486 | 501 516
SD] 31 20 48 46 28 54 48 34

Session 2
Younger Mean | 515 516 508 509 496 | 488 500 505
8) 47 44 31 A 47 47 42 47
Older Mean | 521 518 462 | 480 463 | 437 479 491
SD] 35 28 69 61 50 91 68 60
Overall Mean | 518 | 517 | 485 | 494 479 | 462 | 489 | 498
SD]! 40 36 57 53 50 75 56 53
Session 3

Younger _Mean | 510 | 493 | 487 | 478 | 510 466_| 501 | 495

SD | 45 53 47 60 30 82 48 45
“ Older Mean | 507 488 | 434 | 454 | 437 [ 419 | 476 502
SD] 48 45 95 101 108 102 68 34

Overall Mean | 508 [490 | 461 | 466 473 | 442 | 488 | 498
SD] 45 48 78 82 86 933 59 39

Table 40

MANOVA Summary Table for Passive Composite Scores by Session and
15-minute Interval for the Night Shift

Degrees of Sums of Squares | Mean Squares

Source of Variation Freedom F

Age 1 54107.84 54107.84 N.S.

Between Subjects 18 693417.32 38523.18

Interval (Workload Condition) 7 140687.87 20098.27 9.08**

Age by interval 7 29017.44 4145.35 N.S.

Within Subjects 126 278982.83 2214.15

Session 2 2459.56 1229.78 N.S.

Age by Session 2 277.83 138.91 N.S.

Within Subjects 36 53821.17 1495.03

interval by Session 14 82143.40 5867.39 5.41**
| Age by Interval by Session 14 30656.70 2189.76 2.02*

Within Subjects 252 273399.62 1084.92

*p<.05
**p<.001

A-20



Table 11
Means and Standard Deviations for Arithmetic Percent Correct

Study Day cpt Al A2 D1 b2 N_| cb2 | cbD3 CD4 CDs

Session 1
Younger Mean | _ 94.1] 95.6] 96.0| 97.6| 96.1] 96.1| 963] 96.1 96.3 98.5

SD 5.5 1.7 27 24 23 3.6 2.9 3.7 1.6 1.7

Older Mean | 91.1 | 90.1 | 91.5] 93.7] 947] 95.3| 93.7] 96.9 95.4 96.0

SD 69 6.6 8.1 5.4 3.4 47 45 3.7 29 3.9

Session1 Mean} 92.6 | 92.9| 93.7 | 95.7| 95.4 | 95.7] 95.0| 965 95.9 | 97.2
sD 6.3 5.4 6.3 44| 2.9 4A 3.9 3.6 2.3 3.2

Session 2
Younger Mean | 95.9! 95.4| 97.3/ 98.0] 96.1] 97.6] 964]! 966 96.9 | 96.8

SD 3.6 44 2.8 16} 30 22| 46 41 3.4 3.1

Older Mean | 92.7 | 93.0] 95.0] 95.4] 965] 96.6| 94.4] 95.1 95.1 96.9

sD 5.3 3.7 5.7 4.5 3.5 36] 43 45 3.0 3.4

Session 2 Mean | 94.3 | 94.2] 96.2| 96.7 | 96.3[ 97.1 | 95.4] 95.8 96.0 | 96.9
sD 47 41 45 3.5 3.2 3.0 | 4.5 4.3 3.3 3.2

Session 3 *
Younger Mean | 95.3| 97.0] 97.1] 97.5| 95.9| 98.3| 97.1] 98.0 96.8 96.6

sD 4.3 2.2 2.8 1.7 3.7 2.0 3.3 25 1.9 29

Older Mean| 94.1] 935] 949] 946] 96.1] 95.4] 96.3[ 96.1 95.8 | 95.8

SD 47 5.3 6.1 42 27 24 25 44 45 5.7

Session3 Mean | 94.7 | 95.2 | 96.0] 96.0| 96.0/ 96.9| 96.7| 97.0 96.3 | 96.2
sD 44 43 48 3.4 | 3.1 2.6 2.9 3.6 3.4 44

Table 12
MANOVA Summary Table for Arithmetic Percent Correct

Degrees of Sums of Squares {| Mean Squares
Source of Variation Freedom E
[Age 1 548.65 548.65 NS.
Between Subjects 18 4125.04 229.17
Day of Study 9 529.46 58.83 6.25 **
| Age by Day 9 170.41 18.93 2.01*
i Within Subjects. 162 1524.38 9.41
Session 2 122.67 61.33 7.39"
| Age by Session 2 18.91 9.45 N.S.
Within Subjects. 36 298.62 8.29
Day by Session 18 157.26 8.74 N.S.
| Age by Day by Session 18 113.94 6.33 N.S.
Within Subjects 324 2486.46 7.67
“p<.05
**p<.001

A-G



Design and Data Analyses

The study was a mixed-model design with one
between-subjects factor and two repeated-measures
factors. The between-subjects factor was Age Group.
The within-subjects factors were Day of the study
and Session (or Sample in the case of neuroendo-
crine measures), Analyses and factorial models were
specific to each dependent measure. Data analyses
were conducted utilizing the SPSS statistical pack-
age, version 4.1 for VAX/VMS. For the majority of
the analyses, the SPSS MANOVA procedure for
repeated measures was employed.

Multiple comparisons were conducted utilizing
procedures prescribed by Toothaker (1991) when
significant interactions or main effects resulted
from the MANOVA. The multiple comparison
procedure (MCP) involved a series of paired t-tests
on planned comparisons. The comparisons were
developed as a result of application of chrono-
biological principles to the 2-2-1 work schedule.
The control for probability of Type I error was
established by referring the t-value to a Dunn
csitical value with parameters df = J(n-1) and C =
K(K-1)/2, where J equals the number of between-
subject groups, n equals the number of subjects per
group, and K equals the number of repeated mea-
surements for computation of all pairwise compari-
sons. If fewer than all possible pairwise comparisons
were computed, then C equaled the number of
planned comparisons (Toothaker, 1991). Each
analysis of a dependent measure utilized a slightly
different factorial design, based upon when measures
were collected and the specific hypotheses tested, as
follows.

The MTPB performance data were analyzed us-
ing a 2 (Age Group) x 10 (Day) x 3 (Session) mixed-
model design. Age group represented the
between-subjects factor. Both Day and Session were
repeated measures factors. The 10 study days in-
cluded in the analyses were a) the final day of the
first week of day shifts, control day 1 (CD1), b) the
five work days of the 2-2-1 shift week, including
Afternoon 1 (Al), Afternoon 2 (A2), Day 1 (D1),
Day 2 (D2), and the Night shift (N), and c) the first
four days of the final week of the study, which
served as control days 2-5 (CD2, CD3, CD4, and

12

CD5). The first four days of DAYS] week were
dedicated to training and practice, and were not
used in this analysis. Therefore, the first day consid-
ered a day shift control or baseline, CD1, was the
last day of DAYS1. The last day of the protocol
during DAYS2 was excluded from the analyses to
avoid any end-of-study effect.

To simplify the MTPB multiple comparison
analyses and reduce the probability of a Type I
error, the following pre-planned comparisons were
developed to focus specifically on the effects of the
2-2-1 shift quick-turn-arounds, anticipated Night
shift performance decrements, and possible recov-
ery period:

1)The first quick-turn-around: Performance on

A2 (second afternoon shift of the 2-2-1) was

compared to performance on D1 (first day shift

of the 2-2-1),

2)The second quick-turn-around: Performance

on D2 (second day shift of the 2-2-1) was

compared to performance on N (the night shift).

This transition was the second quick-turn-around

during the week and was predicted to result in

the worst performance on N of any shift during
the week.

3)Performance on Session 1 of the Night shift

was compared.to Sessions 2 and 3 of the same

shift.

4) Performance on Control Day 2 (CD2), the

first day of the final week of straight day shifts,

was compared to performance on D2, the second
day shift of the 2-2-1. This comparison was
designed to assess the possibility of continuing
petformance decrement following the 2-2-1 that

may have persisted into the final week of day
shifts.

The described pre-planned analyses resulted in
11 comparisons with 18 degrees of freedom when
comparing Age x Session or Day x Session interac-
tions and 3 planned comparisons with 18 degrees of
freedom for multiple comparisons on main effects of
Days or Sessions. The uninterpolated Dunn’s criti-
cal values used for each of these cases were 3.48 and
2.69 (p<.05) for two-way interaction and main effect
comparisons, respectively (Toothaker, 1991, p. 145).



Code Lock Solution

* Younger ¢ YoungSD -*-Older 4 Older SD j
108

Percent Correct

Session 123123123123123123123123123123
Day CDi | Al A2 Di Dd2 N | CD3 CD4 CDS

Days1 2-2-1 Days2

Figure 6. Means and standard deviations for Code Lock Solution Percent
Correct by Age Group by Session from day CD1 (week 2) to day CD5
(week 4).

Code Lock Solution

Younger ¢ YoungSD -+Older 4 Older SD]
28

Response Time (Seconds)

0
Session 123123123123123123123123123123

Day D1 | Al =A2 D1 ope ON | Cb2 CD3 CD4 CDs
Days1 224 Days2

Figure 7. Means and standard deviations for Code Lock Solution Response
Time by Age group by Session from day CD1 (week 2) to day CD5 (week 4).

B-6


Target Identification

Younger * YoungSD -*Older 4 Older SD j

108
104
100

96
88

84
80
767 -
72
68

64
Session 123123123123123123123123123123
Day CD1 | Al A2 Di D2 N | Cb2 CD3 CD4 CDSs

Days! 2-2-4 Day

Figure 10. Means and standard deviations for Target Identification

Percent Correct by Age group by Session from day CD1 (week 2) to day
CD5 (week 4).

Percent Correct

Target Identification

Younger ¢ YoungSD -+Older 4 Older SD j

Response Time (Seconds)

Session 1 23123125123123123123128123108
Day sil Al A2 Di D2 N CD2 CD3 CD4 CDS
bays 2-2-1 | Days2
Figure 11. Means and standard deviations for Target Identification

Response Time by Age group by Session from day CD1 (week 2) to day CD5
(week 4).

B-8



separately. Figure 6 and Table 15 present descrip-
tive statistics for Code Lock Solution Percent Cor-
rect. Table 16 presents the MANOVA summary
table for Code Lock Solution Percent Correct.

Results of the 2 x 10 x 3 MANOVA for Code
Lock Solution Percent Correct revealed a significant
three-way interaction for Age by Day by Session,
F(18, 324) = 1.88, p<.05. Two-way interactions
were found to be significant for Age by Day, E(9,
162) = 2.02, p<.05, and Day by Session, F(18,
324) = 2.87, p<.001. None of the planned compari-
sons for the Age by Day or the Day by Session
interactions were found to be significant.

Figure 7 and Table 17 present descriptive statis-
tics for Code Lock Solution Response Time. Table
18 presents the MANOVA summary table for Code
Lock Solution Response Time.

Results of the 2 x 10 x 3 MANOVA for Code
Lock Solution Response Time revealed a significant
Day by Session interaction, E(18, 324) = 2.06,
p<.05, as well as a significant main effect for Day,
E(9, 162) = 8,05, p<.001, and Session, E(2, 36) =
5.76,*p<.05. Planned multiple comparisons for the
Day by Session interaction revealed that solution
time was significantly slower on N Session 3 (M =
16.1 seconds) than on D2 Session 3 (M = 13.8
seconds), 4(18) = 3.97, p<.05. Planned compari-
sons for differences between Days revealed that
Code Lock Solution Time was significantly slower
on the Night shift (M = 15.3 seconds) than on the
prior Day (D2) shift (M = 14.1 seconds), 1(18) =
3.12, p<.05. Code Lock Solution Time was found
to improve over Sessions, such that subjects solved
the Code Lock problem significantly faster during
Session 3 (M = 14.1 seconds) than Session 1 (M =
14.9 seconds), 1(18) = 3.07, p<.05 over the course
of the study.

Figure 8 and Table 19 present descriptive statis-
tics for Code Lock Recall Percent Correct. Table 20
presents the MANOVA summary table for Code
Lock Recall Percent Correct.

Results of the 2 x 10 x 3 MANOVA for Code
Lock Recall Percent Correct revealed a significant
Age by Day interaction, F(9, 162) = 3.97, p<.001,
as well as a significant main effect for Day of the

15

study, F(9, 162) = 3.62, p<.001. Multiple com-
parisons for the Age by Day interaction revealed a
significant difference between Age groups on D1,
after the first quick-turn-around, £(18) = 3.93,
p<.05. The mean percent correct for the Older
group, 95.26, was greater than one standard devia-
tion below the mean for the Younger group, 97.38.
The decline in Code Lock Recall Percent Correct
from 95.87 on D2 to 93.92 on N was also found to
be significant, (18) = 3.16, p<.05.

Figure 9 and Table 21 present descriptive statis-
tics for Code Lock Recall Response Time. Table 22
presents the MANOVA summary table for Code
Lock Recall Response Time.

Results of the MANOVA on Code Lock Recall
Response Time revealed a significant Age by Day
interaction, F(9, 162) = 2.91, R<.05, and a signifi-
cant Day effect, F(9, 162) = 2.92, p<.05. Planned
comparisons for the Age x Day interaction revealed
no significant differences between Age groups.
Multiple comparisons for the Day main effect re-
vealed that mean Code Lock Recall Response Time
was significantly slower on the Night shift (M =
5.85 seconds) compared to the previous Day (D2)
shift (M = 5.0 seconds) by nearly 1 second, (1 8) =
2.85, pe.05.

Target Identification. Figure 10 and Table 23
present descriptive statistics for Target Identifica-
tion Percent Correct. Table 24 presents the
MANOVA summary table for Target Identification
Percent Correct.

Results of the 2 x 10 x 3 MANOVA for Target
Identification Percent Correct revealed significant
main effects for Day, F(9, 153) = 4.42, p<.001, as
well as Session, F(2, 34) = 6.20, p<.05. Planned
multiple comparisons for Day of the study revealed
that accuracy was lower on the Night shift (M =
85.76) than the previous Day shift (M = 90.31),
4(18) = 3.71, p<.05. Results of planned compari-
sons on the main effect of Session revealed that
performance on Sessions 2 (M = 89.12), 2(18) =
2.80, p<.05, and 3 (M = 89.13), £(18) = 2.99,
R<.05 was significantly lower than on Session 1 (M
= 90.52).