EUROPEAN ORGANISATION FOR THE SAFETY OF AIR NAVIGATION EUROCONTROL EXPERIMENTAL CENTRE OBJECTIVE EVALUATION OF PHYSIOLOGICAL BEHAVIOUR AND WORKLOAD OF CONTROLLERS EEC Report No. 339 Project HUM-7-E2 Issued: August 1999 The information contained in this document is the property of the EUROCONTROL Agency and no part should be reproduced in any form without the Agency’s permission. The views expressed herein do not necessarily reflect the official views or policy of the Agency. EUROCONTROL
Transcript
EUROPEAN ORGANISATIONFOR THE SAFETY OF AIR NAVIGATION
EUROCONTROL EXPERIMENTAL CENTRE
OBJECTIVE EVALUATION OF PHYSIOLOGICALBEHAVIOUR AND WORKLOAD
OF CONTROLLERS
EEC Report No. 339
Project HUM-7-E2
Issued: August 1999
The information contained in this document is the property of the EUROCONTROL Agency and no part should bereproduced in any form without the Agency’s permission.
The views expressed herein do not necessarily reflect the official views or policy of the Agency.
The MILAN 99 real-time Simulation, carried out at The EUROCONTROL Experimental Centre (EEC) inJanuary/February 1999 was concerned with the reorganisation of the Milan Terminal Management Area(TMA), in view of the opening of the new Malpenza Airport. Sleep logs, workload assessment and fatigueevaluation questionnaires were employed, with Event Related Potential for mental fatigue assessmentand salivary cortisol for workload and stress assessment on selected working positions.
Psychophysiological observations suggested that time of day and day within the week significantlyaffected fatigue and workload measures, so that subjective measures taken on, for example, Mondaymorning and the last day of the simulation may be distorted. Controllers’ experience in the specificworking positions should also be taken into account. Observations also suggested that adaptationcontinues well into the measured phase of such a simulation, and should be controlled or balanced injudging the conclusions.
This document has been collated by mechanical means. Should there be missing pages, please report to:
OBJECTIVE EVALUATION OF PHYSIOLOGICAL BEHAVIOUR AND WORKLOAD
OF CONTROLLERS
By
P. Cabon, B. Farbos, S. Bourgeois-Bougrine, R. Mollard,LAA, Université René Descartes - Paris V
The MILAN 99 real-time Simulation, carried out at The EUROCONTROL ExperimentalCentre (EEC) in January/February 1999, was concerned with the reorganisation of the MilanTerminal Management Area (TMA), in view of the opening of the new Malpenza Airport. EEChas carried out studies of psychophysiological methods in small-scale simulation, and ofcontrollers’ adaptation to altered interfaces in real-time Simulation (SweDen 98). In MILAN99 these methods were applied to an organisational simulation.
Sleep logs, workload assessment and fatigue evaluation questionnaires were employed, withEvent Related Potential for mental fatigue assessment and salivary cortisol for workload andstress assessment on selected working positions.
Psychophysiological observations suggested that time of day and day within the weeksignificantly affected fatigue and workload measures, so that subjective measures taken on,for example, Monday morning and the last day of the simulation may be distorted.Controllers’ ‘real-life’ experience in the specific working positions affects their responsesmeasurably, and should also be taken into account. Observations also suggested thatadaptation continues well into the measured phase of even an organisational simulation, andshould be controlled or balanced in judging the conclusions.
It is clear that psycho-physiological measures, chosen to fit the aims of an operationalsimulation, can contribute significantly to the assessment of alternative organisations, bothdirectly, and indirectly by warning of extraneous fatigue and learning effects, which maydistort subjective conclusions.
2.5 - OBJECTIVE MEASURES -............................................................................................................................... 92.5.1 - Stress -................................................................................................................................................ 92.5.2 - Mental fatigue through the Event Related Potential (ERP) - ............................................................ 9
2.6 - OTHER DATA - ........................................................................................................................................... 142.7 - DATA COLLECTION SCHEDULE -................................................................................................................ 14
A N N E X ............................................................................................................................................................ 59
ix
ABBREVIATIONS
ANOVA ANALYSIS OF VARIANCE
ATC AIR TRAFFIC CONTROL
AU ARBITRARY UNIT
EEC EUROCONTROL EXPERIMENTAL CENTRE
EEG ELECTRO-ENCEPHALOGRAM
EOG ELECTRO-OCULOGRAM
EUROCONTROL EUROPEAN ORGANISATION FOR THE SAFETY OF AIR NAVIGATION
IANS INSTITUTE OF AIR NAVIGATION SERVICES
ISA INSTANTANEOUS STRESS ASSESSMENT
NASA NATIONAL AVIATION AND SPACE AGENCY
NASA-TLX NASA TASK LOAD INDEX
RT Simulation REAL-TIME SIMULATION
SA SALIVARY CORTISOL
TMA TERMINAL MANOEUVRING AREA
TRACON TERMINAL RADAR APPROACH CONTROL (SIMULATOR)
UACC MAASTRICHT UPPER AIRSPACE CONTROL CENTRE
x
Intentionally Left Blank
xi
FOREWORD
One of the main purposes of the establishment of Independent Research Fellows at theEurocontrol Experimental Centre is the search for and introduction of advanced methodsfor research in Air traffic control.
The need for more ‘objective’ measures of the effects of Air Traffic Control on controllershas long been apparent, and various studies have been undertaken at EEC on potentialmethods of measuring these effects (EEC Reports 64, 164, 183, 219, 226, 228, 323 and334).
The Laboratoire d’Anthropologie Appliquée of the Université de Paris V (Université RenéDescartes), under the direction of Professor Alex Coblentz, has carried out a series ofstudies of fatigue, sleep disorders and associated strain among airline pilots (Cabon etasl 1996), car drivers (Cointot et al, 1997) and Air Traffic controllers (Mollard et al, 1996)among others.
In accordance with our policy of maintaining awareness of developments, we becameaware that the development of EEG studies (in particular the technique of CorticalEvoked Potential) and of salivary cortisol analysis were potentially useful measures.
We therefore commissioned the Laboratoire d’Anthropologie Appliquée, as a leadingpractitioner of these techniques, to undertake a feasibility study of the use of thesetechniques at the EEC. This study was reported in EEC Report No. 323, and a furtherstudy was reported in EEC Note No. 16/98.
Selected methods were then transferred to a real-time simulation (Sweden-Denmark) asreported in EEC Report No. 334. This simulation involved the evaluation of an unfamiliarhuman-computer interface.
The real-time simulation MILAN 99 concerned the evaluation of changes in sectorisationin the Milan TMA, using a close approximation to the existing system. The opportunitywas taken to apply psychophysiological methods in an ‘organisational’ as opposed to a‘research’ simulation. This report describes the application of these methods.
On behalf of the Director EEC, the experimenters of the Laboratoire d’AnthropologieAppliquée and ourselves, the Project Officers wish to thank the controllers and the EECstaff involved in the running of the MILAN 99 simulation, who co-operated so actively inthis research.
Francoise CalooHugh David
EEC Project Officers
xii
ACKNOWLEDGEMENTS
The LAA would like to express their gratitude to the Eurocontrol team in charge
of the real time simulation, especially to Yann KERMARQUER, Adrian GIZDAVU and
Peter SLINGERLAND.
These evaluations could not have been undertaken without the active
cooperation of Italian Controllers involved in this study. The help of Pietro PAGLIA was
greatly appreciated.
Finally, the authors would like to thank the EEC project officers
Françoise CALOO and Hugh DAVID for their practical help in the organisation of this
study.
* * * *
A N T H R O P O L O G I E A P P L I Q U E E
45, rue des Saints-Pères 75270 PARIS Cedex 06Téléphone : 01 42 86 20 37- 01 42 86 20 41 -Télécopie : 01 42 61 53 80
Figure 9.Mean difference of P300 amplitude after-before the sessions as a
function of traffic volume (n = 4).
-0,2
-0,15
-0,1
-0,05
0
0,05
0,1
0,15
0,2
T99 T02 T05
Traffic level
Mea
n d
iffe
ren
ce a
fter
-bef
ore
th
ese
ssio
ns
of
P30
0 am
plit
ud
e (µ
V)
-
+F
atig
ue
Figure 8.Mean difference of self evaluation of fatigue after-before the sessions as
a function of traffic volume (n = 19).
24
The figure 9 depicts the evolution of the mean difference between the P300
amplitude after the session and before the session. An increase of the negative values
constitutes an objective index of mental fatigue. The results obtained on the sub
sample of 4 Approach Controllers, show a decrease of mental fatigue as a function of
the traffic volume and are consistent with the subjective evaluations collected on the
whole sample of Controllers.
3.2.4 - Stress -
As for the ERP, the stress level of Controllers is assessed by computing the
difference between the excretion of cortisol after and before the sessions (figure 10).
All the differences are negative because the cortisol level show a diurnal variation with
a decrease along the day. A reduction of the decrease, however, is usually related to a
stress. The figure 10 show that the results of cortisol are consistent with those of the
perceived workload (cf. figure 7). The difference between after and before tends to
decrease from T99 to T05. Therefore these results even if they are not significant show
that the increase of traffic increased the level of stress of controllers.
3.2.5 - Controllers orders to pilots -
The orders provided by the Controllers to the pilot provides information about
some aspects of the performance of the Controllers during the simulation. The figure
11 shows the results of the total number of orders by week divided by the number of
aircraft, i.e. the frequency of orders per aircraft. It can be observed a decrease of this
frequency from T99 to T05 simulations. This decrease can be explained by two main
factors. The first deals with a learning process. As the situation of a RTS is not strictly
as the reality, most Controllers have stated that they « learned » the simulation
regarding the procedures, the aircraft behaviours,... The second explanation lies on the
improvement of the different airspace organisations which were tested in the third
week. These two factors will be further discussed in the general discussion of results.
25
-1
-0,9
-0,8
-0,7
-0,6
-0,5
-0,4
-0,3
-0,2
-0,1
0
T99 T02 T05
Traffic levelM
ean
dif
fere
nce
aft
er-b
efo
re t
he
sess
ion
s o
f co
rtis
ol s
ecre
tio
n (
ng
/ml)
Figure 10.Mean difference after-before the sessions
of salivary cortisol secretion as a function of traffic volume (n = 8).
26
1
1,1
1,2
1,3
1,4
1,5
1,6
1,7
1,8
1,9
2
T99 T02 T05
Traffic level
Nu
mb
er o
f co
ntr
olle
rs o
rder
s / N
um
ber
of
airc
raft
Figure 11.Number of controllers orders divided by the number of aircraft
as a function of traffic volume (n = 15).
27
3.3 - Organisation effect -
3.3.1 - Perceived Workload -
The results of perceived workload are presented on the figure 12 for the three
weeks. During the first week, the organisation A+ leads to the highest scores of
workload and the organisation B to the lowest. During the second week, the
organisation E showed the lowest scores of workload while the highest are observed
for the B. In the third week, the workload remains at a moderate level in E and F. The
organisation FW (windy condition) increased the perceived workload of Controllers
regarding mental, physical and temporal demands. The mental demand shows the
highest values, around 60. The self assessment of performance slightly decreased
during the organisation FW compared to the other organisations. On the contrary, the
windy condition associated with the organisation E (EW) leads to a moderate level of
workload and a higher self assessment of performance than the FW. This suggests
that the organisation E allowed the Controllers to cope with this condition.
3.3.2 - Self-rating of fatigue -
The figure 13 shows the data collected before and after the sessions. The
results are presented as a function of the day of week (from Monday to Thursday)
expect for the week 3 as various organisations were played everyday during this week
(cf table 2.3). For the three weeks, the self-rating of fatigue appears to be influenced by
the day of week with a level reaching a maximum the Monday and decreasing during
the other days. This is related to the effect of the week-end which changes the sleep-
wake patterns with a delay in the sleep schedules. On Monday morning these changes
lead to an increase of fatigue which can persist along the day. Some effects of the
organisations can be observed when the differences between after and before values
are computed (figure 14). During the first week the organisation B leads to the lowest
level of fatigue and A (on Monday) to the highest level. The organisation C showed the
lowest levels in the second week. In the third week, the lowest difference is observed
for FW and EW.
28
This could be related to the fact that these 2 organisations were played in the
very last day of the RTS. On the contrary, the same day, the organisation F leads to a
significant increase of fatigue. Therefore this suggests that the amended procedures
allow to reduce the level of fatigue.
29
20304050607080
A B C A+
Organisation
A.U
.
-
+
20304050607080
A B C A+
Organisation
A.U
.
-
+
Week 1
A.U. : Arbitrary Units.
Figure 12.Self-evaluation of Workload (NASA-TLX)
as a function of the organisations for the 3 levels of traffic (n = 19).
- : low ; + : high.
Mental Demand
Physical Demand
Temporal Demand
PerformanceEffortFrustration Level
20304050607080
A B C E
Organisation
.U.
-
+
20304050607080
A B C E
Organisation
A.U
.
-
+
Week 2
20304050607080
E F FW EW
Organisation
A.U
.
-
+
20304050607080
E F FW EW
Organisation
.U.
-
+
Week 3
30
NB : Various organisations were played everyday during the third week (cf. table 2.3)
0102030405060
A B C A+Organisation
A.U
.
-
+ **
*
-202468
101214
A B C A+Organisation
Mea
n d
iffe
ren
ce o
fse
lf e
valu
atio
n o
ffa
tig
ue
(A.U
.)
Week 1 (T99)
0102030405060
A B C E
Organisation
A.U
.
-
+* * *
-202468
101214
A B C E
Organisation
Mea
n d
iffe
ren
ce o
fse
lf e
valu
atio
n o
fat
igu
e (A
.U.)
Week 2 (T02)
0102030405060
E F FW EWOrganisation
A.U
.
-
+ * *
-202468
101214
E F FW EW
OrganisationM
ean
dif
fere
nce
of
self
eva
luat
ion
of
fati
gu
e (A
.U.)
Week 3 (T05)
Week 1 (T99)
Week 2 (T02)
Week 3 (T05)
Figure 13.Mean values of self evaluation of fatigue
before and after the sessions as a functionof the organisations for the 3 levels of traffic (n = 19).
- : fresh ; + : tired.
Figure 14.Mean difference of self evaluation of fatigue
after-before the sessions as a functionof the organisations for the 3 levels of traffic (n = 19).
Before After * : Statistical significant difference at .05.
31
3.3.3 - Objective evaluation of mental fatigue by the ERP’S -
During the first week, Controllers showed the most important level of mental
fatigue after the organisation A+ and the lowest level after the organisation B
(figure 15). The results of the second week are consistent with those of the first week
as fatigue was prominent for the organisations A and C and the less important after the
organisations B and E. Therefore these data seems to support the choice of the
organisation B and E. The third week, the results confirm those of the NASA-TLX with
the highest mental fatigue observed for the organisation FW and the lowest levels for
the organisation E. However it is not possible to compare these results with the
organisation EW as the data cannot be processed for technical reasons. Thus, these
results suggest that the windy condition leads to a greater effort compared to the
normal conditions and that the E and F lead to the minimum of fatigue. Moreover,
compared to subjective evaluations of fatigue, these results show that Controllers have
underestimated their level of fatigue in the windy condition (cf. figure 14).
3.3.4 - Stress -
The results concerning the first week (figure 16) show that the highest increase
of salivary cortisol is observed for the organisation C. During the second week the
lowest variation is noted for the organisation E, supporting the previous results of
workload and fatigue. The data of the last week are also consistent with the other data.
The highest level of stress is observed after the organisation FW (windy condition) and
the lowest levels of stress are noted for the organisation E as for the ERP values.
32
3.3.5 - Controllers orders to pilots -
The frequency of Controllers orders per aircraft is presented for each
organisation on figure 17. A decrease of this parameter can be observed from the first
to the last week. However, during the two first weeks, the frequency shows a peak for
the organisation C and organisation B. In the third week, the organisation E was
associated with a lower frequency than during the organisation E of the previous week.
The lowest value is associated with the organisation EW and the highest is observed
for the organisation FW. It is interesting to notice that the windy condition had more
impact on the organisation F than on the organisation E. Taken as a whole the level
reached during this week is the lowest level of all the organisations throughout the 3
weeks. These results suggest an improvement of performance due to the organisation
or to a learning process phenomena.
33
No dataavailable
Week 3 (T05)
-0,2-0,15
-0,1-0,05
00,050,1
0,150,2
A B C A+Organisation
Mea
n d
iffe
ren
ce o
f P
300
amp
litu
de
(µV
) +F
atigu
e
Week 1 (T99)
Week 2 (T02)
Figure 15.Mean difference of P300 amplitude after-before the sessions
as a function of the organisations for the 3 levels of traffic (n = 4).
-0,2-0,15
-0,1-0,05
00,050,1
0,150,2
A B C EOrganisation
Mea
n d
iffe
ren
ce o
f P
300
amp
litu
de
(µV
) +
Fatig
ue
-0,2-0,15
-0,1-0,05
00,050,1
0,150,2
E F FW EWOrganisation
Mea
n d
iffe
ren
ce o
f P
300
amp
litu
de
(µV
) +
Fatig
ue
34
No dataavailable
-4-3-2-101234
A B C A+Organisation
Mea
n d
iffe
ren
ce o
f sa
livar
y co
rtis
ol (
ng
/ml) *
Week 3 (T05)
Figure 16.Mean difference of salivary cortisol secretion
after-before values as a function of the organisations for the 3 levels of traffic (n = 8).
-4-3-2-101234
A B C EOrganisation
Mea
n d
iffe
ren
ce o
f sa
livar
y co
rtis
ol (
ng
/ml)
-4-3-2-101234
E F FW EWOrganisation
Mea
n d
iffe
ren
ce o
f sa
livar
y co
rtis
ol (
ng
/ml)
* : Statistical significant difference at .05.
*
35
1,4
1,5
1,6
1,7
1,8
1,9
2
A C B E E FW
Organisation
Nu
mb
er o
f co
ntr
olle
rs o
rder
s / N
um
ber
of
airc
raft
T99 T02 T05
Figure 17.Number of controllers orders divided by the number of aircraftas a function of organisations for the 3 levels of traffic (n = 19).
A
B A+ A C F EW
36
3.4 - Effects of experience on the position -
As a significant difference was observed for the experience on the position as a
function of age and of genders (see § 2.1) the data were analysed only as a function of
the experience of Controllers. Therefore, the sample was divided into 2 sub-groups :
Controllers having an experience lower than 20 months and Controllers having an
experience higher than 20 months. The effect of this factor are presented for fatigue,
perceived workload and stress.
3.4.1 - Fatigue -
No effect of experience was observed on the level of fatigue.
3.4.2 - Perceived workload -
All the scales of the NASA-TLX except the frustration level show a significant
effect of the experience (figure 18) : the less experienced Controllers perceived less
workload than experienced Controllers.
3.4.3 - Stress -
Effect of experience on stress is opposite to the perceived workload (figure 19) :
the high experienced Controllers showed less increase of secretion of salivary cortisol
than low experienced Controllers. Therefore, a dissociation between the perception of
Controllers and their objective reaction to the simulation in terms of stress can be
noticed. This dissociation is an important point as it means that less experienced
Controllers probably underestimate their workload. On the contrary, experienced
Controllers have probably a good appraisal of their own level of workload as the level is
lower than 50 for all the scales of NASA-TLX.
37
PhysicalDemand
Performance FrustrationLevel
0
20
40
60
80
100
MentalDemand Temporal
DemandEffort
A.U
.< 20 months of experience
≥ 20 months of experience
-
+
** *
*
*
-1
-0,8
-0,6
-0,4
-0,2
0
0,2
0,4
0,6
0,8
1
< 20 months of experience ≥ 20 months of experience
Mea
n d
iffe
ren
ce a
fter
-bef
ore
th
e se
ssio
ns
of
cort
isol
sec
reti
on
(ng/
l)
*
A.U. : Arbitrary Units,- : low ; + : high.
Figure 18.Effects of the experience of the position
on perceived workload (NASA-TLX) - n = 19.
Figure 19.Effects of the experience of the position on difference of salivary cortisol secretion
(after-before the sessions) - n = 8.
* : Statistical significant difference at .05.
* : Statistical significant difference at .05.
PhysicalDemand
Performance FrustrationLevel
38
3.4.4 - Controllers orders to pilots -
The effect of experience on Controllers orders to pilots is depicted on the figure
20. Two statistical significant differences are observed.
First, the high experienced Controllers show a significant reduction of their
orders between T05, T99 and T02, while no significant variation was observed for the
Controllers having less than 20 months of experience. Secondly, during the whole
simulation, the low experienced Controllers showed lower number of orders compared
to the high experienced Controllers. The composition of this group can explain these
results. In fact, all Controllers which have less than 20 months of experience are all En
route Controllers and therefore have less orders to provide to pilots.
Furthermore, the results of the low experienced Controllers seem to suggest the
absence of a learning process during the simulation in so far as none reduction of
orders was observed for the 3 levels of traffic.
3.4.5 Approach versus En-route sectors
3.4.5.1 Traffic effect
As mentioned earlier, the sector per sector analysis leads to an insufficient
number of data to reveal statistical results, especially for objective data which were
focused on approach sectors. However, some interesting trends can be observed when
the data are averaged for en-route and approach sectors. The figure 21 shows a
comparison of fatigue and global score of the NASA-TLX for the two kinds of sectors. It
is worth to note that both en-route and approach Controllers rated their workload as
increasing as a function of the traffic, but only the approach Controllers felt an increase
of fatigue with traffic. This results is consistent with the results of experience presented
in the previous section as the en-route Controllers were also the less experienced.
39
Figure 20.Effect of the experience of the position on the numberof controllers orders divided by the number of aircraft
as a function of the 3 levels of traffic (n = 19).
0,08
0,10
0,12
0,14
0,16
T99 T02 T05
Nu
mb
er o
f co
ntr
olle
rs o
rder
s / N
um
ber
of
airc
raft
*
*
**
****
* : Statistical significant difference at .05 between eachlevel of traffic
** : Statistical significant difference at .05 betweenthe two groups according to the level of traffic.
< 20 monthsof experience
≥ 20 monthsof experience
40
40
45
50
55
60
Traffic 1999 Traffic 2002 Traffic 2005
Mea
n N
AS
A-T
LX
sco
re (
A.U
.)MILAN 99 - REAL TIME SIMULATION -
0
5
10
15
Traffic 1999 Traffic 2002 Traffic 2005
Mea
n d
iffe
ren
ce o
f se
lfev
alu
atio
n o
f fa
tig
ue
(A.U
.)
En routecontrollers TiredFresh Å
1000Å Approachcontrollers
Approachcontrollers Low Å :
En routecontrollers
High
1000 Å
Figure 21.Mean difference of self evaluation of fatigue and Mean NASA-TLX score for
En route and Approach controllers as a function of traffic.
A.U. : Arbitrary Units.
41
MILAN 99 - REAL TIME SIMULATION
30
40
50
60
70
A B C A+
Mea
n N
AS
A-T
LX
sc
ore
(A
.U.)
-10
0
10
20
30
40
A B C A+
Mea
n d
iffe
ren
ce o
f se
lf e
valu
atio
n o
f fa
tig
ue
(A.U
.)
30
40
50
60
70
E F FW EW
Mea
n N
AS
A-T
LX
sc
ore
(A
.U.)
-10
0
10
20
30
40
E F FW EW
Mea
n d
iffe
ren
ce o
f se
lf e
valu
atio
n o
f fa
tig
ue
(A.U
.)
30
40
50
60
70
A B C E
Mea
n N
AS
A-T
LX
sc
ore
(A
.U.)
-10
0
10
20
30
40
A B C E
Mea
n d
iffe
ren
ce o
f se
lf e
valu
atio
n o
f fa
tig
ue
(A.U
.)
En route controllersTiredFresh Å
1000 Å Approach controllers HighLow
100 0 Å
WEEK 1
WEEK 2
WEEK 3
Figure 22.Mean difference of self evaluation of fatigue and Mean NASA-TLX score
for En route and Approach controllers as a function of organisations.
A.U. : Arbitrary Units.
Å
42
No dataavailable
-4-3-2-101234
A B C A+
Mea
n d
iffe
ren
ce o
f co
rtis
ol s
ecre
tio
n (
ng
/ml)
MILAN 99 - REAL TIME SIMULATION
-4-3-2-101234
E F FW EW
Mea
n d
iffe
ren
ce o
f co
rtis
ol s
ecre
tio
n (
ng
/ml)
En route controllers
Approach controllers
-4-3-2-101234
A B C E
Mea
n d
iffe
ren
ce o
f co
rtis
ol s
ecre
tio
n (
ng
/ml)
WEEK 1
WEEK 2
WEEK 3
Figure 23.Mean difference of salivary cortisol secretion
for En route and Approach controllers as a function of organisations.
43
T99 T02 T05
Figure 24.Number of controllers orders divided by the number of aircraft as a function of
organisations and type of sectors for the 3 levels of traffic (n = 19).
W = Wind
1,2
1,4
1,6
1,8
2
2,2
2,4
2,6
A B C A+ A B C E E F FW EW
Nu
mb
er o
f co
ntr
olle
rs o
rder
s / N
um
ber
of
airc
raft
Approach sector
En-Route sector
44
3.4.5.2 Organisations effect
The figure 22 shows that both fatigue and workload are rated lower for the en-
route Controllers for the organisation B and C during the first week. During the second
week, the en-route Controllers were more tired than the approach Controllers in, the
organisation C and E. However, the workload remains exactly at the same level for the
2 groups of Controllers. In the third week, the workload remains at the same level for
the two groups but fatigue shows a different trend with a peak for the en-route
Controllers during organisation FW. Therefore it seems that the en-route Controllers
were more affected in terms of fatigue by the windy condition associated with the
organisation F while they do not felt a higher level of workload. This result is still
consistent with those presented in the previous sections on the effect of experience
showing that the less experienced Controllers tend to underestimate their workload.
The results of salivary cortisol are presented on figure 23. It can be observed
that, generally speaking, en-route Controllers showed higher positive difference in
salivary cortisol. That means that their level of cortisol tends to increase more than for
approach Controllers, i.e. they had more stress related to the task. However, the
difference between the two groups of Controllers is especially high in the organisation
B of the second week. It is also worth to notice that both groups were affected by the
wind (FW).
The figure 24 compares the number of orders to pilots for en-route and approach
Controllers. As it could be expected, the number of orders are higher for approach
Controllers than for en-route Controllers. However, the evolution of this parameter
through the organisations is parallel for the two groups of Controllers.
45
4 - DISCUSSION -
The aim of the Milan 99 RTS was to identify the best airspace organisation to
implement in the Milan TMA. The airspace organisation to keep is intended to ensure
that Controllers will be able to perform a safe and efficient control with a reasonable
level of workload, despite the foreseen increase of traffic. With this aim in view, 3
organisations (A, B, C) were tested in the first week at the current level of traffic
observed in the area of Milan. During a second week, a new organisation (E) was
designed in collaboration with the Italian Controllers and tested at the level foreseen in
2002. The third week, based on a first data analysis and Controllers’ opinions, the
organisation E and the organisation F (a variant of organisation E) were tested with the
level of traffic foreseen in 2005 including 2 windy simulations.
In addition to the traditional evaluation used at EEC, a set of data were collected
in order to support the operational choices in terms of airspace organisation. These
data cover the following topics that could not be evaluated only by subjective tools :
fatigue, workload and stress. The main results are summarised into the table 3. This
table shows the effects that can be statistically demonstrated as well as the main
trends which do no reach a statistical level. In fact, as the objective measures were
collected on sub-groups, even when the differences are large the amount of data is not
sufficient to gives statistical results.
From the results, it can be noticed that the increasing level of traffic yields to
an increasing level of workload and stress. However, it should be keep in mind that
the levels of workload remain at a moderate level, lower than 50 on the NASA TLX
even for the highest traffic volume (2005). In the real world, the same evaluations are
frequently higher than 50.
46
Paradoxically, a slight decrease of fatigue, both subjective and objective is
observed. This finding could be explained by the progressive adaptation of the
Controllers to their stay in Paris in unusual conditions (i.e. the hotel, the hours of
work,...). This hypothesis is supported by the results of sleep quality which tends to
improve during the second and third week. However, two other factors dealing with the
RTS itself can explain this result. First, during the debriefing the Controllers have
stated that they need some time to adapt to the simulator which does not reflect exactly
the reality of their real work conditions. Therefore, the learning of the simulator
reaction had probably helped the controllers to slightly decrease their fatigue despite
the increase in traffic. The second factor concerns the organisation which have been
improved from the first to the third week on the basis of Controllers’ opinions.
47
Levelof traffic
Organisations(associated with
the lowest values)
Experienceof the position
Approach versus En-route sectors
Perceived
workload
(NASA-TLX)
(n=19)
Increase with
traffic (S)
Week 1 : B (NS)
Week 2 : E(NS)
Week 3 : E and F (NS).
Lower for less
experienced
Controllers (S)
Lower for en-route
than approach during
the first week. Higher
during the organisation
FW for approach (NS)
but lower for approach
for EW (NS)
Self rating of
fatigue
(n=19)
Decrease with
traffic (NS)
Week 1 : B (S)
Week 2 : C (S)
Week 3 : FW (S)
No effect. Lower for en-route
than approach during
the first week. Higher
during the organisation
FW for en-route (NS)
Objective
mental fatigue
assessed by the
Event Related
Potentials
(n=4)
Decrease with
traffic (NS)
Week 1 : B (NS)
Week 2 : B, E (NS)
Week 3 : E (NS)
Insufficient number
of data
En-route Controllers
were not recorded
Stress
assessed by the
salivary cortisol
(n=8)
Increase with
traffic (NS)
Week 1 : A+ (S)
Week 2 : E (NS)
Week 3 : E (S)
Higher for less
experienced
Controllers (S)
Insufficient number of
data
Frequency of
Controllers
orders to pilots
(n=19)
Decrease with
traffic (NS)
Week 1 : A+ (NS)
Week 2 : A (NS)
Week 3 : E and EW
(NS)
Higher for high
experienced
Controllers (S)
Higher for Approach
Controllers (NS)
NS : Not statistically SignificantS : Significant at P<.05
Table 3.Synthesis of results.
48
The feeling of a better organisation, well adapted to the level of traffic, could also have
a positive effect on fatigue. It is thus likely that the adaptation to the living conditions,
the learning of the simulator reaction as well as the improvement in the organisations
had played together a role in the slight reduction of fatigue. This is consistent with the
fact that the Controllers reduced the frequency of orders to pilots. However, due to the
scheduling of the simulations, it is difficult to identify which are the most contributing
factors.
Based on the results summarised in the table 3, it is difficult to clearly
differentiate all the organisations. This statement supports partially the Controllers’
opinions.
In the first week, the lowest levels of workload and fatigue was observed for the
organisation B which was considered as a good one according to the Controllers point
of view. Moreover, the organisation E was derived from this organisation. However, the
Controllers orders to the pilots (index of activity) and stress level (objective measures)
were the lowest for A+.
The second week, two organisations : B and E are associated with the lowest
values of perceived workload, objective fatigue and stress, but Controllers orders to
pilots were still the lowest for the organisation A.
In the third week, most of values suggest that the organisation E is the most
adapted. However, it is necessary to remain very careful in the interpretation. In fact, it
is possible that the learning process of the simulation already mentioned has
influenced the results in maintaining their workload at a moderate level for the
organisations E tested with the highest level of traffic. This hypothesis is supported by
the fact that the frequency of Controllers orders to the pilots decreased from the first to
the third week. Moreover, the organisation E of the third week leads to a lower number
of Controllers orders than during the second week while the traffic had increased.
As the other organisations (A, B and C) were not replayed with the 2005 traffic,
the comparison of all the organisations with the same level of traffic is not possible.
49
Some remarks can also be addressed from results reported in table 3
concerning the individual differences. Significant differences on stress, perceived
workload and number of manipulations appear between low and high experienced
Controllers. As mentioned before, it seems that the low experienced Controllers
underestimate their workload : they assess their workload lower than the experienced
Controllers although a stress reaction can be observed for them but not for
experienced Controllers. During the Sweden-Denmark RTS, strong individual
differences have been also revealed as a function of previous experience of the
interface. For Milan 99, the results of workload were contrary : the low experienced
Controllers had more workload than high experienced Controllers. This difference
could be explained by the fact that a totally new interface was tested in the Sweden-
Denmark campaign while Milan 99 involved new airspace organisations with the same
interface. Furthermore, most of the Italian Controllers included in the low experienced
group were only planning Controllers while the Swedish and Danish Controllers who
had no previous experience of the interface were all qualified as Executive Controllers.
The comparison of the data for the en-route and the approach sectors does not
revealed any significant differences due to the low number of Controllers in each of
these two groups.
50
Intentionally Left Blank
51
5 - CONCLUSION - PROSPECTS -
From the data collected in this RTS specific outcomes regarding the objectives
of Milan 99 can be addressed :
- the workload of Controllers was maintained at a moderate level for all the
organisations,
- the organisation E seems to be the most adapted as it induces less workload,
stress and fatigue. However, further investigations should be performed to
evaluate this organisation in different situations, e.g. fog (which is more frequent
in this area than wind), technical problems on aircraft,... and to determine
whether this organisation is still adapted. In addition, it should be worth to test
this organisation with Controllers who had not worked on previous exercises on
the simulator to avoid any learning effect.
From a more general point of view, these results have also some important
implications for further RTS :
- the day to day effect (e.g. increased level of fatigue and workload on Monday
morning, underestimation of fatigue on the last day of simulation) has to be taken
into account in the interpretation of subjective data,
- when setting up a group of controllers to be involved into a RTS it is necessary to
take into account the previous experience of Controllers on the position. If it is
not possible, the data processing has to be done separately for the high and low
experienced Controllers as the results would be significantly different for most
evaluations,
- due to the progressive adaptation of the Controllers to the general conditions of
the simulations and the learning process of the simulator, the scheduling of the
simulation should be also designed carefully to avoid misinterpretation. For the
specific case of Milan 99, this effect cannot be excluded and thus can mask
some aspects in the third week. Therefore, a training and familiarisation phase
should be planned before to start any evaluation on a simulator. This
familiarisation period should be representative of the exercises that will be
tested. Another method to avoid this learning effect should be to counterbalance
the order of the organisations from one week to another.
* * * *
52
Intentionally Left Blank
53
6 - REFERENCES -
CABON (P.) ; MOLLARD (R.) ; COINTOT (B.) ; MARTEL (A.) ; BESLOT (P.).-Elaboration of a method for the assessment of psychophysiological states of Air Trafficcontrollers in simulation. EEC Report N° 323, 1997, 64 p.
CABON (P.) ; FARBOS (B.) ; BOURGEOIS (S.) ; COINTOT (B.) ; MOLLARD (R.).-Objective evaluation of the learning process of controllers adapting to a new HMI forATC. EEC Note No 16/98, 1998, 26 p.
CABON (P.) ; FARBOS (B.) ; MOLLARD (R.) ; COBLENTZ (A.).- Objective evaluation oflearning process in Air Traffic Control Simulation. The Tenth International Symposium onAviation Psychology, Colombus, Ohio, USA, May 3 -6, 1999, 6 p.
DAVID (H.) ; CABON (P.) ; BOURGEOIS-BOUGRINE (S.) ; MOLLARD (R.).-Psychophysiological measures of fatigue and somnolence in simulated Air TrafficControl. In : Contempory Ergonomics, 1998, Taylor and Francis (ed.) pp. 429-433.
DUNCAN-JOHNSON (C.G.) ; DONCHIN (E.).- On quantifying surprise : The variation inevent-related potentials with subjective probability.- Psychophysiology, 14, 1977, pp.456-467.
FARBOS (B.) ; CABON (P.) ; BOURGEOIS (S.) ; DAVID (H.).- Psychophysiologicalmeasures of fatigue and somnolence in simulated Air Traffic Control. In : Proceedings ofthe Measuring Behavior 98 Conference, Groningen, August 18-21 1998, 2 p.
FARBOS (B.) ; CABON (P.) ; MOLLARD (R.). ; CALOO (F.) ; DAVID (H.).- Evaluationobjective de l'adaptation des contrôleurs aériens à une nouvelle interface homme-machine. Communication présentée au XXXIV Congrès de la Société d'Ergonomie deLangue Française, Caen, 15-17 Septembre 1999.
FIBIGER (W.) ; EVANS (O.) ; SINGER (G.).- Hormonal responses to graded mentalworkload.- European Journal Applied Physiology and Occupational Physiology, 55,1986, pp. 339-43.
JASPER (H.H.).- The ten-twenty electrode system of the International Federation.-Electroencephalography and Clinical Neurophysiology. - 10, 1958, 371-376.
NAVON (D.) ; GOPHER (D.).- On the economy of the human processing system.-Psychological Review, 86, 1979, pp. 214-255.
ZEIER (H.) ; BRAUCHLI (P.) ; JOLLER-JEMELKA (H.I.).- Effects of work demands onimmunoglobulin A and cortisol in air traffic controllers.- Biological Psychology, 42, 1996,pp. 413-423.
* * *
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55
Traduction en langue française
SOMMAIRE
La simulation temps réel MILAN 99 menée au Centre Expérimental Eurocontrol
(CEE) en Jan/Fév 99 avait pour principal objectif la réorganisation de la TMA Milan
dans le cadre de l’ouverture du nouvel aéroport de Malpensa.
Le CEE a réalisé plusieurs études sur des mesures psychophysiologiques et des
processus d’adaptation des contrôleurs à de nouvelles interfaces hommes/machines,
dans un premier temps en laboratoire puis au cours de la simulation temps réel
Suède/Danemark 98.
Des mesures objectives d’évaluation de la fatigue mentale par potentiel évoqué
auditif, de surcharge de travail et de stress par analyse de cortisol salivaire ont été
effectuées sur certains secteurs sélectionnés et complémentées par des mesures
subjectives tels que agendas du sommeil, questionnaires de surcharge de travail et de
fatigue.
Les résultats de ces observations psychophysiologiques suggèrent qu’il existe un
effet de l’heure pendant la journée ainsi que du jour de la semaine pouvant modifier,
de manière significative, les mesures de fatigue et de surcharge de travail , par
exemple, le Lundi et le dernier jour de la simulation, que l’expérience des contrôleurs
en ce qui concerne leurs secteurs a aussi un effet mesurable sur leurs réponses, qui
devra être pris en considération et enfin, que le processus d’adaptation se maintient
durant les exercices faisant l’objet de ces mesures y compris dans une simulation
d’organisation.
Il apparaît clairement que de telles évaluations psychophysiologiques
sélectionnées pour répondre aux objectifs d’une simulation opérationnelle, peuvent
contribuer d’une manière significative à une meilleure évaluation d’organisations
alternatives soit directement soit indirectement en alertant sur une fatigue superflue ou
des effets d’adaptation pouvant influencer des conclusions subjectives.
56
AVANT-PROPOS -
L’un des principaux objectifs du Centre d’expertise “Independant Research” au
Centre Expérimental EUROCONTROL est la recherche et l’introduction de méthodes
de recherches novatrices dans le domaine du contrôle aérien.
Le besoin d’évaluer plus objectivement l’impact du contrôle aérien sur les
contrôleurs est une préoccupation ancienne et de nombreuses études ont été menées
au CEE pour déterminer les méthodes d’investigations les plus adaptées (CEE
Rapports 64, 164, 183,219,226,228, 323 et 334).
Le Laboratoire d’Anthropologie Appliquée de l’Université Paris V (Université
René Descartes) a mené, sous la direction du Pr Alex Coblentz, de nombreuses
études sur la fatigue, les troubles du sommeil et autres troubles associés notamment
sur les pilotes de ligne (Cabon et al 1996) les conducteurs d'automobiles (Cointot et al
1997) et les contrôleurs aériens (Mollard et al 1996).
Conformément à notre politique d’actualisation de nos programme d’études, les
derniers développements dans le domaine d’études EEG et d’analyses de cortisol
salivaire ont retenu notre attention et conduit à penser que de telles mesures pouvaient
se révéler très utiles.
C’est pourquoi, nous avons demandé au Laboratoire d’Anthropologie Appliquée,
leader dans cette spécialité, de conduire une étude de faisabilité sur l’utilisation de ces
techniques au CEE. Cette étude a fait l’objet d’un rapport (CEE n° 323/97) et d’une
étude complémentaire (note CEE n° 16 /98).
Certaines de ces méthodes ont été appliquées à une simulation temps réel
(Suède/ Danemark) et fait l’objet d’un rapport CEE n° 334/99. Cette simulation avait
pour objectif d’évaluer une nouvelle interface homme/machine.
La simulation temps réel Milan 99 concerne l’évaluation de modification de
secteurs dans la TMA Milan, assez proche du système existant. L’occasion nous a été
donnée de pouvoir appliquer ces méthodes psychophysiologiques à une simulation
“Organisationnelle” par opposition à une simulation de “Recherche”. Ce rapport décrit
le transfert de ces méthodes.
Le Directeur du Centre Expérimental, les chercheurs du Laboratoire
d’Anthropologie Appliquée ainsi que les chefs de projets tiennent à exprimer leurs
remerciements aux contrôleurs et aux personnels du CEE pour leur étroite
collaboration à cette étude menée pendant la simulation Milan 99.
57
INTRODUCTION - OBJECTIFS -
Ce document rapporte les résultats des évaluations objectives du comportement
psychophysiologique des Contrôleurs au cours de la simulation temps réel Milan 99 qui
s’est déroulée au Centre Expérimental d’Eurocontrol. Ces évaluations ont pour objectif
d’orienter des choix opérationnels concernant l’organisation du trafic aérien de la
région de Milan dans le contexte de l’ouverture du nouvel aéroport de Malpenza. Après
Suède-Danemark 98, la simulation Milan 99 constitue la deuxième transposition dans
une simulation temps réel de mesures physiologiques validées dans des travaux
menés sur des simulations simplifiées(3) utilisant le logiciel TRACON PRO (Cabon et
coll., 1997, 1999 ; David et coll, 1998 ; Farbos et coll, 1998, 1999). Cependant, alors
que le but de la simulation Suède-Danemark était d’évaluer l’impact d’une nouvelle
interface(4) (Cabon et coll., 1998), l’objectif de la simulation Milan 99 concerne la
comparaison de plusieurs organisations dans leur capacité à gérer l’augmentation du
trafic aérien prévue dans cette région. La méthode utilisée a donc été adaptée aux
objectifs spécifiques de cette simulation. Trois aspects essentiels ont été évalués en
fonction des différentes organisations testées :
• la fatigue,
• la charge de travail,
• le stress.
Dans la perspective de la future organisation du trafic aérien, ces trois aspects
apparaissent essentiels d’un point de vue opérationnel puisqu’ils peuvent dégrader la
performance des Contrôleurs et donc la sécurité. De ce fait, ces évaluations
renforcent la validité des choix opérationnels réalisés au cours de cette simulation
temps réel.
3 EEC report N° 323 et EEC note 16/98.4 Rapport EEC N° 334.
58
CONCLUSIONS - RECOMMANDATIONS -
A partir des données recueillies dans cette simulation, les résultats suivants ont
été mis en évidence :
• la charge de travail des Contrôleurs est restée à un niveau modéré pour toutes les
organisations,
• l’organisation E semble la plus adaptée, car elle induit le moins de charge de travail,
de stress et de fatigue. Néanmoins, des simulations complémentaires devraient être
effectuées pour évaluer cette organisation dans différentes situations, par exemple la
présence de brouillard ou de problèmes techniques survenant sur un avion… et ainsi
déterminer si cette organisation reste toujours adaptée. Par ailleurs, il serait
nécessaire de tester cette organisation avec des contrôleurs n’ayant pas
préalablement effectué d’exercices sur le simulateur afin d’écarter un éventuel effet
d’apprentissage.
D’un point de vue plus général, ces résultats ont des implications importantes
pour les futures simulations temps réel :
• il existe un effet du jour de la semaine (par exemple une augmentation de la fatigue
le lundi matin, une sous-estimation de la fatigue le dernier jour de la simulation) qui
doit être pris en compte dans l’interprétation des données subjectives,
• lors de la constitution du groupe de Contrôleurs qui doivent participer à la simulation,
il est nécessaire de prendre en compte l’expérience passée de ces Contrôleurs sur le
secteur. Si cela n’est pas possible, le traitement des données doit être effectué
séparément pour les Contrôleurs expérimentés et non expérimentés car les résultats
peuvent être significativement différents pour la plupart des évaluations,
• en raison de l’adaptation progressive des Contrôleurs aux conditions générales de la
simulation, la planification de la simulation doit être conçue avec précaution pour
éviter de fausses interprétations. Dans le cas spécifique de Milan 99, cet effet ne
peut être exclu et peut donc masquer certains aspects relatifs aux évaluations
effectuées dans la 3ème semaine. Une période de familiarisation et d’entraînement
doit donc être prévue avant de débuter les évaluations sur le simulateur. Cette
période doit être représentative des exercices qui vont être présentés aux
Contrôleurs. Une autre méthode consisterait à contrebalancer l’ordre des
organisations d’une semaine à l’autre.
* * * *
59
* * *
A N N E X
* * *
QUESTIONNAIRES USED DURING
THE REAL TIME SIMULATION
- SLEEP LOG
- FATIGUE EVALUATION
- NASA-TLX
60
- Agenda de sommeil / Sleep log -
- Une feuille par cycle à détacher et à remettre, chaque jour au médecin ou dans la boite prévue à cet effet -- One sheet per cycle to remove and to give every day to the doctor or to put in the designed box-
Date
Jour Mois Année
Day Month Year
EveilléAwake
FatiguéTired
SomnolentDrowsy
En formeFresh
AU COUCHER / WHEN GOING TO BED
AU LEVER / WHEN GETTING UP
Temps d’endormissement
Time to fall asleep
Heure de réveil
Waking time
Heure de lever
Raise time
Si vous avez des commentaires, inscrivez les au verso de cette feuille / If you have somecomments, write them on the back of this sheet.
Heure de coucher / Bed time
Comment vous sentiez-vous au couchez ? / How did you feel at bedtime ?
Réveil naturel
Natural awakening
Réveil planifié Autres raisons
Other reasons
Réveil provoqué par une gêne
Disturbance
Avez-vous pris un médicament pour dormir / Did you take a drug for sleep ?Si oui, lequel / If yes, which one :
Au cours de la nuit vous êtes-vous réveillé pendant une durée importante/ Did you wake upduring the night for a significant time ?
Si oui, indiquer la durée et les heures approximatives / If yes, indicate the approximate time andduration :
Quelle a été la raison de votre réveil ? / What was the reason for your awakening ?
Planned awakening
Comment vous sentez-vous actuellement ? / How do you feel right now ?
EveilléAwake
FatiguéTired
SomnolentDrowsy
En formeFresh
61
Fresh
Sleepy
Tired
Awake
Date :Time :Name :
Fatigue evaluation( after session)
Did you feel difficulties, to remember information, to concentrate and tomaintain your attention, to interpret information or to estimate time ?
Indicate the degree through which you felt these manifestations :
Did you feel a hearing fatigue (difficulty to hearing) or a visual fatigue ?
Indicate the degree through which you felt these manifestations :
Did you feel headaches, pains in legs, in arms, in the back or in the neck ?
Indicate the degree through which you felt these manifestations :
Did you feel strained, aggressive, irritable, impatient, less interesting inyour surroundings or your environment ?
Indicate the degree through which you felt these manifestations :
HighAver
age
NoneVer
y high
Wea
k
4 - Mood
3 - Physical fatigue
2 - Sensorial fatigue
1 - Mental fatigue
According to your current feeling, write a mark on the following scales :
During the previous period, did you feel the following manifestations related with fatigue
HighAver
age
NoneVer
y high
Wea
k
HighAver
age
NoneVer
y high
Wea
k
HighAver
age
NoneVer
y high
Wea
k
62
On the following pages, you will find six scales concerning different aspects of operational loadwhich may contribute to the overall work load during the flight.Please, indicate on these six scales retrospectively your average load during the last part of theflight.
Scale 1 : Mental Demand
How much mental and perceptual activity was required (e.g. thinking, deciding, calculating,remembering, looking, searching, etc…) ?Was the work easy or demanding, simple or complex, exacting (exigeant) or forgiving ?
Low High
Scale 2 : Physical Demand
How much physical activity was required (e.g., pushing, pulling, turning, controlling, activating,etc…) ?Was the work easy or demanding, slow or brisk (rapide), slack (détendu) or strenuous (soutenu),restful or laborious ?
Low High
Scale 3 : Temporal Demand
How much time pressure did you feel due to the rate or pace (rythme ou cadence) at wich the workhad to be done ?Was the pace slow and leisurely (tranquille) or rapid and frantic (effréné) ?
Low High
NASA-TLX (Task Load Index)
Ce questionnaire en langue anglaise a été validé par la NASA
Néanmoins, certains termes n'étant pas du langage courant, unetraduction est présentée entre parenthèses et en italique
"Task difficulty" evaluation [1-3]
63
Scale 4 : Performance
How successful do you think you were in accomplishing the goals of the tasks set by the respectivework demands ?How satisfied were you with your performance in accomplishing these goals ?
Poor Good
Scale 5 : Effort
How hard did you have to work (mentally or physically) to accomplish your level of performance ?
Low High
Scale 6 : Frustration Level
How insecure, discouraged, irritated, stressed, and annoyed versus secure, gratified, content, relaxedand complacent (confiant) did you feel during the past part of the test.
Low High
"Task difficulty" evaluation [2-3]
How difficult was this session :
Veryeasy
Verydifficult
64
You will see bellow the six TLX scales presented in pairs.Please, mark a cross for the scale in each pair which was more importantin your overall workload
