- Email: [email protected]
Traffic accidents and professional driver characteristics: A follow-up study
II,pp.7-18
Accid Anal & Pm Vol c, Pcrgamon Press Ltd.. 1979
Pnntcd fin Citeal Bruin
TRAFFIC ACCIDENTS AND PROFESSIONAL DRIVER CHARACTERISTICS: A FOLLOW-UP STUDY SAULIHAKKINEN Helsinki University of
Technology,
Otaiaari
4 A, SF-02150
Espoo
15, Finland
Abstract-This is a follow-up study of the driver group reported on in 1958. The accident behavior of 66 professional drivers was followed over a period of IO-27 years. The constancy of the accident coefficients and the prediction power of the test variables were studied with correlations, factor analyses and discriminant analyses. The correlation between the accident coefficient (accidents per man per year) of the basic eight-year period and the follow-up period of nine years (average) was 0.56, corresponding to a reliability of 0.72 for the total exposure time. Correlations between the test variables and accident coefficients for the follow-up period were almost the same size as in the basic period, even though the follow-up period ranged from I to 20 years from the time of testing. Multiple correlations between the accident coefficient and I8 test variables for the basic, follow-up and combined periods were 0.75.0.77 and 0.81. respectively. These and other analyses showed that the accident behavior of professional city drivers is very constant, and this behavior can be predicted with specially planned psychological tests.
INTRODUCTION
Accident proneness, accident liability, accident repeaters, and personal factors in accidents are concepts which have an ambiguous sound in the literature of traffic safety. The reason for this ambiguity is the low reliability of accident figures and many nonsignificant validity correlations when predictor variables have been used. As pointed out many times, the stochastic nature and the rare occurrence of accidents, the variability of circumstances and a continuous selection of drivers make exact studies very difficult. In addition poorly controlled studies and fixed attitudes have minimized the interest in individual differences, as well as the difficult applicability of the selection or screening methods. One epoch of this discussion was the work of Shaw and Sichel [I9711 and the evaluations made of it [Haight, 1972; Klein, 19731. One of the relatively rare studies in which the consistency of individual differences in accident rates has been shown was made in Helsinki in 1958 [Hakkinen, 19581.The reliability of the accidents of bus and streetcar drivers was examined by different methods. When the reliability was found high enough, psychological tests were carried out with 100 drivers. The highest correlations between the accident coefficient and individual test variables were 0.40 and 0.43, and the multiple correlation of five test variables was 0.59, and of ten test variables 0.64. A part of the driver group considered in the basic study continued working in the same company. In the present follow-up study the exposure time (the exact time a man was working as a driver in this company) and the accident figures for the drivers were collected from the whole period of driving for the company. The total exposure time varied from 10.5 to 26.5 years with the mean of 16.6 years. A total of 66 of the original 100 drivers belonged to this follow-up group. A brief summary of the basic study is presented before the results of the follow-up period. SUMMARY
OF
THE
BASIC
STUDY
Statistical phase
In the statistical phase of the study information was gathered on approximately 4400 traffic accidents incurred by about 1000 bus and streetcar drivers employed by the Municipal Transport Company of Helsinki in 1947-54. An accident was defined as any traffic casualty incurred by a driver of a vehicle in motion, of which the management of the traffic establishment had knowledge. Every recorded accident was included without any limitation due to the amount of damage or the guilt of the driver. The mutual relationships of different accident categories were studied. The homogeneity of environmental factors was studied through the calculation of an index for each driver. His exposure time on each route was multiplied by the accident coefficient of
8
S.
HAKKINEN
the route (accidents per driver per year calculated from the whole material). The sum of these products was compared with the actual accident figures of each driver: Number .of accidents Length of time on the route X Act. coeff. of the route The ratio indicates the relative number of accidents per year for each driver after the elimination of the differences between routes. These rates were correlated with the original accident rates of all the drivers. The correlations were of a magnitude of 0.95. This correlation means that drivers had changed routes so many times that the real risk was nearly the same for all, and differences in accident rates were not affected by such environmental factors as routes. The reliability of the accident rates was investigated by the calculation of the correlations between the accidents incurred during two consecutive time periods, by analysis of the distributions of accidents and comparison of the group averages between consecutive time periods. These three methods yielded nearly identical results, and confirmed the assumption that constant personal factors exert a considerable influence upon accident rates. The reliability of accident rates increases with exposure time approximately in accordance with the SpearmanBrown formula (Gulliksen, 1950). Therefore lengthening the exposure time increases the reliability of accident rates, as for instance lengthening a psychological test increases its reliability. The correlations between the accidents in two consecutive years were on the order of 0.25435, and between two consecutive four-year periods on the order of 0.60470 (Table 1). When the exposure time was sufficiently long, eight years for instance, the reliability of accident rates was sufficient to serve as a criterion in experimental studies. In regard to the type of accidents, the total number of accidents proved more reliable than the variables formed on the basis of the various sub-divisions made according to type, size or responsibility. Collisions have, however, at least to some extent, a nature of their own, a finding which appeared ‘in both the statistical and the experimental phases of the study. Table I. Correlations
Length
between accidents in two successive time periods, and the reliabilities for the sum of these periods [Hlkkinen 1958. p. 30. 38, 391 Correlation
of
exposurr
between
year-s
time,
ir,ztcar
::-;,,eri
aus
drivers
calculated r
rEl
,3a
I-
$36
=r.1
.53
IN = 3221
.64
.45
.62
(N = 1411
.35
.52
.:7
4
IN = lcll)
4/4
a
years
l-4/5-4
.67
.dl
.5a
. 73
.3a
.a1
1*3+j+i/ 2.4+6*8
:3 ,N = 44)
Reliability 2r
coefficients
caiculated
:N = 521
from
Spearman-St-own
formula:
Traffic accidents and professional driver characteristics:
a follow-up study
9
Personal factors, as defined in terms of accident rates, may appropriately be split into constant factors, the factors which change with time (such as age, driving experience and the time of employment by the transport firm concerned), and the variable and incidental factors [Htikkinen, 19641.The possibility of revealing the constant factors is decisively influenced by the degree of homogeneity of the groups studied in respect to the changing factors mentioned. If the group is composed of drivers differing in age and length of employment, for example, the effect of the constant factors is overshadowed by that of those factors displaying strong changes. These changes may have opposite effects during the period of exposure, and thus the accident rates seem to have no reliability. Only if the material is well controlled in these respects can the effect of the constant factors be clearly demonstrated.
Experimental
phase
In the statistical phase of the study, individual accident rates were established as reliable enough for use as a criterion in an experimental study. Such a study was carried out with 100 drivers, almost one-half of whom were streetcar drivers and the rest bus drivers. The period of exposure for most of the drivers was about eight years and the reliability of the accident rates was, for both of the groups, more than 0.80. The groups were volunteers, but they were selected so that the means and standard deviations of their accident rates did not differ significantly from those of ail the experienced drivers employed at that time in the company. The psychological testing was performed from five to seven years after the beginning of the exposure time. Fourteen tests were used. A detailed description of the tests and references were given in the original report [Hikkinen, 19581.The tests covered the following areas: 1. Intelligence and mechanical aptitude. Paper and pencil tests with emphasis on reasoning and space perception: The Square Test, The Path-tracing Test and Mechanical Comprehension. 2. Simple motor speed and coordination. Reaction time and two-band coordination: Tapping and Fork. 3. Choice reaction and driving apparatus tests. These consisted of: The Clock Test, which tests for factors such as attention span, anticipation and correct timing. The Driving Apparatus Test (DrT), which is a choice reaction test requiring the subject to respond to four different kinds of stimuli with specified hand and foot movements while keeping a stylus, which is moved by means of a steering wheel, on a winding “highway”. This task as a whole required constant concentration and coordination despite disturbances and increasing difficulties. The subject’s driving experience does not influence his performance on the test. The Expectancy Reaction Test (ERT), which was designed to test whether the speed of motor performance is relatively higher than the speed of perception (i.e. whether a person acts before he really knows what sort of action is required). The test is a visual disjunctive reaction test in which the subject must respond to stimuli of a specified kind with a simple hand movement; the situation is made more difficult by means of distractions included in the test or external to it. 4. Psychomotor personality function. A psychomotor test was regarded as a personality test if the principal aim of the experiment was to draw conclusions concerning the characterologicai attributes of the subject on the basis of motor performances, muscle movements and muscle tension. They consisted of: The Ambiguous Situation Test (AST), in which the graphic record of movement made by the subject in response to certain clear, difficult or ambiguous stimuli, is studied for Lhe way in which the subject organizes his activities for hastiness, indecisiveness, lack of movement control, etc. and also for evidence of neurotic traits which are thought to exert an impairing and paralyzing influence on his performance in stress situations. Myokinetic Psychodiagnosis or Mira Test, in which the subject must retrace-certain simple patterns by drawing with a pencil without being able to see what he is drawing. The rationale behind this test is that certain personality traits are reputed to be associated with certain types of deviation from the original pattern. The Body Sway Test, which tests for suggestibility, and through it, for lability and neuroticism. 5. Questionnaires and interview variables.
IO
S. HAKKINEN
The Personality Inventory, which was derived from the inventory of Murray and that of Eysenck and tests for factors such as neuroticism, emotionality, calmness, self-assertiveness, and aggression. The Traffic Questionnaire, which was designed to test the subject’s attitudes towards traffic rules and regulations and towards accidents. Other interview variables were, for instance, biographical data and ratings on clear and frank vs vague, uncertain and concealed answers, and calmness vs nervousness. The test results were analyzed in a variety of ways: the reliability of the test variables, comparisons between the safe and accident groups, intercorrelations between the test variables themselves and the accident criterion, and a factor analysis of these correlations. Some of the results are presented together with the follow-up study in Tables 5 and 7. Both driver groups were divided into two equal parts on the basis of the accident coefficient. The better half was called a safe group and the worse half an accident group. The results of all 300 test variables were first compared between these groups. They may be summarized as follows: There were no significant differences in intelligence and mechanical aptitude tests between the safe and the accident groups. Reaction time was investigated by means of a number of different tests in simple, disjunctive and choice reaction situations. The differences between the groups were small, and none were significant. The intraindividual variability of reaction times did not prove valid for the accident criterion either. Simple motor speed, as measured, for example, by the Tapping Test, was often somewhat greater for the safe than for the accident groups, while the decline in speed during the test was stronger for the accident groups. None of the variables yielded significant differences however. In eye-hand coordination the accident groups, as a rule, did worse than the safe groups. Significant differences between the averages were found, especially within the streetcar driver groups, for three tests involving coordination. As the work of the streetcar +ivers. does not involve continuous coordination, i.e. steering, the result shows that a general psychomotor factor is concerned. The correlations ranged from 0.10 to 0.35. Two types of choice reaction tests were used. In the Clock Test the stimulus field was in sight throughout the experiment, whereas in two other tests (the Driving Apparatus Test and the Expectancy Reaction Test) the stimuli appeared suddenly. In all three tests the speed was paced and the subject could not alter it. In the Clock Test, which requires correct “timing” and estimation of speed, hardly any significant differences were found. In the Driving Apparatus Test and in the Expectancy Reaction Test several variables were discovered which significantly distinguished the accident groups from the safe ones. The number of correct responses in the Driving Apparatus Test was one of the most valid individual variables registered in the test battery (r = 0.42). Different kinds of error variables also revealed significant differences between the groups. The highest correlations between the accident coefficient and these variables were 0.30-0.42. Three so-called psychomotor personality tests were included in the battery of tests. In the Ambiguous Situation Test the motor disturbances appearing in hand performance were more numerous in the accident than in the safe groups. Susceptibility to disturbances grew stronger when the difficulty of the situation increased. The most significant results were in the differences between the numbers of motor disturbances during so-called “wrong” and “correct” reactions. The highest correlations with the accident criterion were 0.30-0.43. For several variables of the Myokinetic Psychodiagnostic Test the performances of the accident groups deviated from the safe groups in a direction considered to be typical of unstable individuals. The results were not very constant for the variables corresponding to each other or for all of the sub-groups, but there were a few highly significant differences between the groups. In the Body Sway Test swaying under suggestion was almost significantly greater in the accident than in the safe groups, a fact which furnishes additional substantiation for the results of previous tests suggestive of lability. None of the 13 variables of the Personality Inventory including a total of 93 questions yielded significant differences between the groups.
Traffic
accidents
and professional
driver
characteristics:
a follow-up
study
II
The attitudes of the drivers towards traffic regulations and traffic accidents were examined by means of two series of questions. The only significant difference was that the accident groups ascribed traffic accidents to driver fatigue, strictness of schedule and length of shifts more frequently than did the safe drivers. No significant differences between the groups were found for such biographical data as the number of children or other family conditions, obtained from interviews or drawn from other sources. On the other hand, the rating made by the interviewer during the interview on the subjects’s behavior (calmness vs nervousness) distinguished the safe groups significantly from the accident groups. The interviewer did not know the accident history of the drivers. The results were generally similar for the bus and streetcar driver groups. Either no differences were discovered or the accident drivers differed from the safe ones similarly in both groups. This demonstrated a very important point, namely that the characteristics associated with accidents were similar for the bus and streetcar driver groups although the actual driving operations they performed were very different. Therefore, it was possible to combine the two groups into one to gain a general picture of the accident behavior of professional drivers. The factor analysis of 28 variables yielded six factors (Table 7) which may be given the following names: Intelligence. Attention, Coordination, Simple Reaction Time, Involuntary Control of Motor Functions, and Stability of Behavior. Of the criterion variables, the total number of accidents and the general appraisal in merit rating were included in the factor analysis. These two correlated to the extent of 0.60. The accident variable was the most strongly saturated on the Attention factor, which was primarily determined by the correct responses on the Driving Apparatus and the Expectancy Reaction Tests. Merit rating had its highest loading in the Stability of Behavior, which was characterized by certain variables of the Ambiguous Situation Test and the Mira Test, as well as the rating of behavior. Both criterion variables had their next highest loading in the Involuntary Control of Motor Functions. The variables descriptive of poor control were indicative of hastiness, susceptibility to disturbances and motor restlessness. The loadings of the criterion variables in Coordination were relatively low, and in Intelligence as well as in Simple Reaction .Tixne they were close to zero. Following the basic study, cross-validation studies were carried out with three groups comprising 160 drivers (100 streetcar drivers, 30 mail bus drivers and 30 truck drivers). The validity correlations for an abbreviated test battery were significant in every case, and they were of the same magnitude as in the basic study (Hikkinen, 1958, p. 168-177). When different criteria such as accidents, merit ratings and observations of driving were combined into one, the validity correlations increased as in the basic study. FOLLOW-UP
STUDY
Sixty-six of the same drivers continued working from 2.5 years to 18.5 years in the company after the basic eight-year period. Exposure times and accident coefficients of the basic, follow-up and total periods are presented in Table 2. The time span for the whole study was from 1947 to 1973. The psychological testing took place in the years 1952-54. The number of Table
2. Exposure
time and accident
coefficient
of the follow-up
group (N = 66)
Exposure
time
Aooidont
coefficient
Roan
SD
Rem
SD
Basic
7.31
1.06
1.50
0.91
Follow-up
9.32
4.11
1.55
1.29
16.62
4.27
1.52
0.99
Expowre period
Total
Total
period:
Range
of
accidents
Range
of
accident
coefficient
2 -
73
0.16
-
4.16
S. HIKKINEN
12
accidents during the total period ranged from 2 to 73 and the accident coefficient (the number of accidents per year of exposure) ranged from 0.16 to 4.16. The correlation between the exposure time and the accident coefficient for the follow-up period was -0.15, which is insignificant. The correlation between the accident coefficient of the basic eight-year period and the follow-up period was 0.56, corresponding to the reliability of 0.72 for the total exposure time. Therefore the reliability of accidents was on the same order of magnitude (0.80) as in the basic period. The accident behavior of professional city drivers seems to be highly constant over a period of driving of IO-26 years. As shown in the basic study, the differences in accident coefficients were not caused by environmental differences, e.g. by route differences. The same is true for the follow-up period during which each driver changed routes several times. A general conclusion can be drawn on the reliability coefficient for the whole period (0.72). It can be stated that no large changes were possible in the relations between the accident coefficient and test variables because the criterion variable was stable over the entire period. Therefore, many detailed analyses have been omitted in this report because of the similarity to the original results. Selectiveness of the follow-up group
A part of the original group of 100 drivers did not continue their job after the basic period. The differences in age and accident coefficient of these groups are compared in Table 3. The resigned group was older, and it had fewer accidents during the basic period. Both differences were significant at the level of 0.05. The accident history had not caused the job change, but the subjects had moved otherwise to another vocation or retired as seen from the personnel records. In the follow-up group the correlations between age and accident coefficient was -0.26 for the basic period, 0.00 for the follow-up period and -0.10 for the total period. In the earlier stage of age and experience, accidents declined a little, but later the constant nature of the accident history continued, as revealed by the reliability coefficients. The follow-up group was divided into two equal parts according to age, and the accident coefficient was calculated for the basic, follow-up and total periods (Table 4). The accident coefficient of the young sub-group declined and that of the old sub-group grew from the basic to the follow-up period. The changes were not significant, but the direction of the changes revealed a general tendency. The young group entering middle age improved their driving habits and the old group over 50 years of age had some difficulties in traffic (Cresswell and Froggatt, 1963; Hiikkinen, 1954). The significance of the age factor was slight, however, when compared with the significance of stable individual characteristics. Validity of psychological tests based on basic and follow-up accident criterion
As a starting point, the ten highest correlations between the accident coefficient and the test variables for the original and for the follow-up group in different exposure periods are given in Table 5. In the basic period, correlations for the follow-up group were somewhat higher than for the basic group. The differences were not significant, but they showed a tendency similar to the one found in the original study, where validity correlations for the young group was higher than for the old group [Hikkinen, 1958, p. 1671. As presented earlier, the make-up of the follow-up Table
airth
3. .4ge and accident
date
Accioent
coefficients
of the follow-up
and resigned
Follow-up grcup
Resigned gmup
N - 66
N-34
Mean
SD
mean
so
7912.23
5.57
1909.74
5.4i
1.50
0.31
0.98
groups
coefficient
(Basic period1
“J.?B
t - 2.35 p = 0.05 t = 2.42 3 = Cl.05
Traffic accidents and professional driver characteristics:
13
a follow-up study
Table 4. Accident coefficient of the young and old sub-groups Young
group
N = 33
EXpOSUrS
period
Old
group
N -
33
mean
SD
Meen
so
Basic
1.67
0.91
1.33
0.89
Follow-up
1.46
1.12
1.65
1 .46
Total
1.53
0.88
1.46
1.10
Birth
date,
mean
Age in the of follow-up
1916.8
beginning period
Table 5. Highest correlations
1907.7
36 years
47 years
between the accident coefficient and the test variables. The mean exposure time appears in parentheses
_
Basic
Basic (7.23
AST, mtor
2.
DrT, correct
Follow-UP study
N - 100
Test veri&leX
1.
study
disturbewes
I
reactions
3.
DrT, simple
4.
Rating of behavior
steering
N = 66 Basic
yeanl
(7.31
years1
Fol lau-up
Total
(9.32
(16.62
years)
.43
.49
.43
.%I
.42
.49
.41
.40
.34
.47
.57
.61
.34
.26
.17
.22
5.
ERT. superfluws
.32
.42
.43
.4B
6.
ERT, correct
reactions
I
.32
.40
.32
.39
7.
ERT. correct
reactions
III
.32
.29
.35
.37
.32
.41
.34
.42
II
.27
.20
.25
.29
DrT , BrrOrS
.26
.33
.16
.23
Mean of correlations
.30
.38
.34
.40
8.
DrT, missed signs
9.
AST, mtor
10.
mactions
disturbances
’ In every variable
the positive
sense cornponds
yea&
to good perfomanca.
group was selected towards a younger direction. Validity correlations of the follow-up group in different exposure periods were on nearly the same order of magnitude. None of the correlations differentiated significantly in any row. When the accident coefficient for the whole period was used as the criterion, the validity of the test variables was as high as, or higher than, those for the original period. The means of the ten highest correlations (according to the basic study) were in the basic, follow-up and whole periods 0.38, 0.34 and 0.40, respectively. It is important to point out that the time lapse between the psychological testing and the follow-up period ranged from 1 to 20 years, the mean being more than 10 years. Multiple regression analysis
Stepwise multiple regression analysis was used to calculate the highest correlation between the accident coefficient and the combined result of 18 test variables. Table 6 contains the results
14
S. HKKKINEN
of the regression analyses for different exposure periods when 5, 10 and 18 test variables were used for the calculation. The multiple correlation varied from 0.71 to 0.81, which means that 50-65% of the total variance of accidents was explained by the test variables used. Five test variables already gave a rather good validity, and the correlations increased very little after the inclusion of 10 test variables. The predictive power of the tests was the highest for the total period. The test variables included in the regression models of different exposure periods were approximately the same in each case. In the analysis of five variables four of them were the same in all three or two analyses. In the analysis of ten variables four of the same variables were included in all analyses and six in two analyses. The similarity of the regression models for different exposure periods means that no big changes had occurred in the ability and personality factors affecting safe or accident behavior in traffic during 20 years. Factor analysis Factor analysis was performed with 26 variables, 24 test variables, and Accident and Merit Rating variables. In Table 7 factor loadings for both the basic and follow-up groups are presented. The basic study group consisted of 100 drivers with an exposure time of about eight years. The analysis was made manually by means of the centroid method and a graphical rotation. The follow-up study group consisted of 66 drivers with an average exposure time of 16.6 years. The analysis was made by computer with the principal axes method and varimax rotation. The rotated factor loadings of six factors were both partly similar and partly different from each other. Factors of Intelligence (I, I), Attention (response orientation, II, 2) Simple Reaction Time (IV, 4) and Stability of Behavior (VI, 3) were quite similar. The composition of other factors differed more from each other. In the original analysis factor III was named Coordination and factor V Involuntary Control of Motor Function. In the new analysis factor 5 could be called Suggestibility and factor 6 Speed (or hastiness) of Performance. They were not very clear, however. In the original analysis the Accident variable was divided into several factors (II, V and VI). In the follow-up study the Attention factor was broader and included higher loadings than in the original study. The factor loading of Accidents was therefore very high (0.76) in the new second factor and low in all other factors. The Merit Rating variable was divided in the later analysis into two factors only, instead of the three in the original analysis. Differences between analyses may have been caused by the partial differences in the groups, changes in the accident variable and the different method used. Nevertheless, the general picture of the analyses was rather similar. Table
6. Multiple
correlations
between
the accident
Exposure Number test
of
coefficient
and the test variables
period
Basic
Follow-up
-otalX
variables R
R
Percentage explained
R
Percentage explained
Percentage explained
5
.?l
.51
.:1
.50
.?5
.56
10
.7a
.55
.76
.sa
.30
.6a
18
.75
.56
.77
.60
.ai
.65
‘Variables 5
test
contained variables:
in 9,
regression
16,
21,
10
test
variables:
_"_
18
test
variables:
_“_
(see
names
in
Tables
71
models 3
and
for
the
total
period:
a; l
10,
14,
22. _*_
26
and
!9; f
20,
12,
11.
5
28, and
7, 2C
5.
Traffic
accidents
and professional Table
.i;
7. Rotated
factor
.4‘
.32
.43
.4c
.
-.cz
.c:
.G1
.2:
.LY
.oc
-3c
.5z
.Ci
.3L
.3f
.cs
.iz
.5;
1:
.i;
.ic
.31
.ne
.05
.O‘
.sc
.3i
.5E
.c:
.oc
.‘a%
.5c
.34
.3c
.15
.4?
.3E
-.OE
.3”
.I5
.23
.SE
.11
.07
.33
.07
.CL
.4S
.55
.2e
.I6
.2E
.4e
.29
.?F
.;L-
-.;i
15. ERT, c~mit reactions III
.3:
characteristics:
-.&z
3;
.Zi
driver
7: -.Z’
.15
-.O’
-.G’
a follow-up
15
study
matrix
.67
.cn
.7E
1”
.5E
:i
.4>
.35
.47
.63
. ci
.S5
.E4
.,,
-.w i:
.li
.CE
.54
.??
.2;
.il
.6C
15
.c3
.37
c:
.31
.Ii
.43
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.;
.I.
.4E
.I’
.‘5
.‘t
.6>
-.C'
.zs
.7S
-.;;
.27
.E9
.61
-.iZ
.ic
.51
.Ot?
.OB
.a5
ia
.39
.66
.38
.67
-.OQ
Lt
. .;
-.Cj
.t7
.6C
.2c
.52
.I4
.LE
.;i
-.L.
.i
.u
.Y
.23
.41
.4:
.10
se
.23
.5E
.2t
.:r
.74
.42
.54
.oi,
.34
.29
.3n
-.15
.45
.18
-.25
.43
.I3
-.I6
.?5
-.34
.c7
.lE
-.a
32
1% - .c:
.lO
.21
.09
-.I4
.43
.li
.2e
.I7
.53
.22
.il’
17. 457.
rasactior tim
.oo
-.27
.15
.P1
-.OR
.12
.28
-.,4
-.I,
.I3
.CE
IE. PST.
speed
.lE
-11
.I1
.2E
.19
-18
.1B
.23
.lI
-.I2
19. AST.
coordinatxm
.2E
.21
-.04
.I3
-.ZO
.42
35
.lO
.13
.50
3:
.53 .28
-.li
.4E
.5i
.45
.29
18
.‘1
-.05
.33
.I?
.18
.42
.os
.27
.53
.I0
20. AST. mtor dlstvmances
1
.35
.2C
-.01
.2c
.35
.OO
37
.37
.46
.04
08
21. AST, nutor aistumancas
II
.07
.2E
.30
.3c
.?3
-.04
37
.Ol
.6?
.09
.02
-
.18
-.O9
-.OE
.14
.61
.08
45
-.27
-.I4
-.13
.23
-.25
-.47
.43
.14
-.07
.07
.06
.41
-.06
20
-.I0
-.06
-.34
.I?
-.I3
-.lE
.20
.10
-.03
-.10
.23
17
.45
.31
-.10
.OO
.49
.I‘
-.:t
.o:
.27
.CS
.21
-.23
.OS
.37
.2E
.1e
-.I0
-.05
.lC
-.Cl
.PS
-.07
.19
.13
.21
.06
.1E
.14
.4'
.26
.,l
.17
.3S
-.i5
3;
.08
.34
24.
plira Tent,
25
6cdy sway. suggestitil:ty
26. Rating
t-r
o* Bshavior
As mentioned earlier, the driver group studied consisted of 37 bus drivers and 29 streetcar drivers. Both in the basic and follow-up studies the results were first treated separately for both groups. Because of the small size of the groups and the similarity of the results only the combined results have been presented in this report. Lkcriminant
analysis
The whole driver group was divided into two groups according to the accident coefficient of the total period, safe drivers (N = 32) and accident drivers (N = 34). The discriminant analysis was made using 18 test variables, the same as in multiple regression analysis. A computer program selected 7 from 18 variables which formed the discriminant function. These variables, F values, F values of additional information, coefficients of discriminant function and correlation coefficients with the discriminant function are presented in Table 8. The discriminant function primarily included the same variables found to be the most valid according to the correlation matrix, regression analysis and factor analysis. Response Orientation or Attention and Stability of Behavior described the feature of discrimination. Mechanical Comprehension and DrT Reaction Time (speed) had negative signs that showed that intelligence and reaction speed had combined negatively in the discriminant function. The correlations of these variables with the discriminant function were low, however.
S. H~KKINEN
16 Table
Test
8. Results
of discriminant F
variable
1.
Ol-T.
correct
reactions
2.
AST,
motor
disturbances
3.
Body
Sway,
suggestibility
4.
OrT,
choice
rsaction
5.
OI-T,
simpie
steering
6.
ERT,
superfluous
7.
Mechanical
I
time
reactions
Comprehension
analysis
F additional
Coefficient of discriminant function
Correlation
19.60
1.11
.71
.73
15.41
0.67
.45
.iO
12.20
0.47
.37
.33
9.82
0.38
0.24
0.30
.32
.54
7.07
0.25
.30
.55
6.41
0.13
-.26
-.32
.15
.17
The result of the discriminant analysis was checked with a classification procedure belonging to the usual computer program of the discriminant analysis (Table 9). This transfer matrix showed that the proportional number of drivers who remained in their original group or that of diagonal observations was 86.4%. This result reveals the high discriminant power of the seven test variables. Only 9 out of 66 drivers were classified erroneously by the discriminant function. Results of fictional selection procedures
The use of a fictional selection procedure gives a concrete picture of the prediction power based on the test battery or the accident rates of the basic exposure period. The whole group of drivers (66) was divided into two equal parts (A and B) on the basis of the accident figures in the basic period. The worse half was divided into B, and B2 (17 and 16). Both the absolute accident figures and percentages for each exposure periods are presented in Table 10. There were small differences in the exposure times of the sub-group but the accident figures were balanced into equal exposures. The total number of accidents subtained by the 66 drivers was 1607 during the whole (average) exposure period of 16.2 years. Had the drivers been selected for the second (follow-up) period on the basis of accident figures of the basic period and had the average accident rate for the selected drivers been the same as in the better half (A), accidents would have numbered 351, or 39.0%, fewer than they did in reality during the follow-up period. If only about one-fourth (B2 = 16) of the worst drivers had been replaced by the average of others (A + B, = 50), 230 accidents would have occurred, or 25.5% fewer than in reality. In general, the figures in Table 10 reveal the constancy of accident behavior in each group. The accident percentages of groups A and B, level off from the basic to the follow-up period by about 5%, but the worst group, BZ, is the most stable, the change of percentages being only 1%. Table
9. Classification
according
to discriminant Computed
Original
Percantage
grauo
of
diagonal
function
group
1
2
1
27
5
2
4
30
observations
-
86.4
Trallk
Table
IO.
Results of fictional selection procedures Accident
Accidents basic
of
of
Basic
Follcw-up
N
I
II
I
l
II
I
II
I
l
II
A
33
177
275
452
25.1
30.5
28.1
B
33
529
626
1155
74.9
69.5
71.9
8,
17
214
233
447
xl.3
25.9
27.0
B2
16
315
393
708
44.6
43.6
44.1
66
706
901
1607
100
100
100
A . B
If B were replacedby A: If
Whole
half
drivers
Total
Group
half
drivers
Worse
Percentage
+igums
in
period
Bettsr
17
accidents and professional driver characteristics: a follow-up study
B2 ware
replaced
by A
351 or 39.0 f fewer accidents
l
8,:
230 or
25.5
Z fewer
accidents
In Table 11 a similar calculation was made on the basis of the sum of the five best test variables according to the basic study. The combined variable is the sum of the normal scores of variables l-5 in Table 5. Had this combined variable been used for the sekction of drivers for the follow-up period and the worse half of the driver group been replaced by the average of the better half, accidents would have numbered 409, or 45.4% fewer than did occur during the follow-up period. Therefore the predictive power of the combined test variable seems to be better than that of the information on accident figures for the basic eight-year period. The test variable would measure “potential” accident behavior in the future better than the accident figures gained in the early stage of driver experience. The correlations between the combined test variable and the accident coefficient for the basic, follow-up and total periods are 0.62,0.60 and 0.66, respectively, which are a little higher than the correlations of the accident coefficients between the basic and the follow-up periods. Calculations were also made in which the combined test variable was used for the selection of drivers before the beginning of the total period. If a half-and-half system (CID) were used as earlier, 609 accidents, or 37.9% fewer accidents would have occurred during the total exposure period. If the average of only the worst drivers (4 = 16) had been replaced by the average of the others, 152,213 and 365 fewer accidents (21.5,23.6 and 22.7%) would have occurred during the basic, follow-up and total periods, respectively. The preceding calculations made for the fictional selection procedures reveal the practical value of the knowledge of accident figures and of the test battery used. DISCUSSION
The follow-up study shows that the accident behavior of professional city drivers is highly constant over a period of driving of more than 25 years. There are only a few studies in which the same driver group has been followed under controlled circumstances over several years. Usually the exposure period has been short and the environmental risk @oorly controlled. In the study of Dvorak and Linke (1976) the reliability of accident criterion was 0.67 for 239 locomotive engineers in the German Federal Railway for a period of 18 years. Bach, Bickel and Biehl (1975) found the correlation of 0.76 between accident rates of two four-year periods (N = 35). The driver group in our study was small, and it is possible to claim that “pure chance” arranged this constant group and a permanent situation across the years. A cross-validation study with 160 drivers supported earlier findings, however. After these studies an abbreviated AAP Vd.
II. No. 1-B
18
S. HAKKINEN Table
Il. Results of fictional selection procedures Accident
GrWp
Sun of five teat
variables
Better
half
If
C
l
0 were
Whole
I
I
33
253
246
Cl 33
453
0,
17
D2
c
I
II
499
35.6
27.3
31.1
655
1108
64.2
72.7
66.9
167
275
442
23.7
30.5
27.5
16
266
360
666
40.5
42.2
41.4
0
66
706
901
1607
100
100
100
replaced
200
409
609
26.3
45.4,
37.9
21.5
23.6
22.7
by C:
fewer If
O2 were
by C + 0,:
* II
x + II
of
drivel-3
Total
Follar-up
I
N
of
drivel¶ uon?.a half
Basic
Percentaga
figures
accidents
replaced 152
273
365 fever
accidents
battery of tests was used for the selection of professional drivers for several years and new cross-validation studies were performed. The accident criterion for only 2-3 years had a reliability of 0.20440. Therefore, validity correlations were low, but they had a trend similar to that shown in this report. The aim of this article is not to overemphasize the role of personal factors in tragic safety. Generally, it is not possible to use and control complicated psychological tests for large groups, nor is there any way of knowing the test validity for different socio cultural populations, as pointed out, for example by Haight [1!972], Harano, McBride and Peck [1973] and Peck, McBride and Coppin [ 19711.However, with well-planned and controlled studies it is possible to detect relevant human factors which in general accident statistics and larger studies, are overshadowed by many changing and uncontrolled factors.
REFERENCES Bach H., Bickel H. and Biehl B.. Validierung van Testverfahren zur Fahrer-Auslese Verkehrssicherheit 21.21-38, 1975. Cresswell W. L. and Froggatt P., The Causation of Bus Driuer Accidents. Oxford University
am Uofailkriterium.
2. f.
Press, London, 1963. Dvorak H. and Linke J., Haufigkeit and Fahrlassigkeit von Unfiillen als Kriterien zur Testvahdierung. 2. /. Verkehnsicherheit 22, 59-63. 1976. Gulhksen H., Theory of Mental Tests. Wiley, New York, 1950. Hai@ F. A., Recent publications. Accid. Anal. Preu. 4, 353355. 1972. Harano R. M., McBride R. S. and Peck R. C., The Prediction of Accident Liability through Biographical Data and Psychometric Tests. Department of Motor Vehicles, State of California, Final Report 39, 1973. H&men S., Age and road accidents. Nordisk Psykologi 6,77-92, 1954. (Swedish). H&kinen S., Tm$ic Accidenrs and L%ver Characteristics. A Statistical and Psychological Study. Finland’s Institute of Technology, Scientific Researches No. 13, Helsinki, 1958. H&kinen S., Functional classification of human factors in accidents. Excerpta Medica fntemational Congress Serirs 62, 1669-1671,
1964.
Klein D., Accident proneness revisited. Contempomry Psychology IS, 549-550, 1973. Peck R., McBride R. S. and Coppin R. S., The distribution and prediction of driver accident frequencies. Prev. 2,243-299. 1971. Shaw L. and Sichel H., Accident Proneness. Perpmon Press, Oxford, 1971.
Accid.
Anal.
Accid Anal & Pm Vol c, Pcrgamon Press Ltd.. 1979
Pnntcd fin Citeal Bruin
TRAFFIC ACCIDENTS AND PROFESSIONAL DRIVER CHARACTERISTICS: A FOLLOW-UP STUDY SAULIHAKKINEN Helsinki University of
Technology,
Otaiaari
4 A, SF-02150
Espoo
15, Finland
Abstract-This is a follow-up study of the driver group reported on in 1958. The accident behavior of 66 professional drivers was followed over a period of IO-27 years. The constancy of the accident coefficients and the prediction power of the test variables were studied with correlations, factor analyses and discriminant analyses. The correlation between the accident coefficient (accidents per man per year) of the basic eight-year period and the follow-up period of nine years (average) was 0.56, corresponding to a reliability of 0.72 for the total exposure time. Correlations between the test variables and accident coefficients for the follow-up period were almost the same size as in the basic period, even though the follow-up period ranged from I to 20 years from the time of testing. Multiple correlations between the accident coefficient and I8 test variables for the basic, follow-up and combined periods were 0.75.0.77 and 0.81. respectively. These and other analyses showed that the accident behavior of professional city drivers is very constant, and this behavior can be predicted with specially planned psychological tests.
INTRODUCTION
Accident proneness, accident liability, accident repeaters, and personal factors in accidents are concepts which have an ambiguous sound in the literature of traffic safety. The reason for this ambiguity is the low reliability of accident figures and many nonsignificant validity correlations when predictor variables have been used. As pointed out many times, the stochastic nature and the rare occurrence of accidents, the variability of circumstances and a continuous selection of drivers make exact studies very difficult. In addition poorly controlled studies and fixed attitudes have minimized the interest in individual differences, as well as the difficult applicability of the selection or screening methods. One epoch of this discussion was the work of Shaw and Sichel [I9711 and the evaluations made of it [Haight, 1972; Klein, 19731. One of the relatively rare studies in which the consistency of individual differences in accident rates has been shown was made in Helsinki in 1958 [Hakkinen, 19581.The reliability of the accidents of bus and streetcar drivers was examined by different methods. When the reliability was found high enough, psychological tests were carried out with 100 drivers. The highest correlations between the accident coefficient and individual test variables were 0.40 and 0.43, and the multiple correlation of five test variables was 0.59, and of ten test variables 0.64. A part of the driver group considered in the basic study continued working in the same company. In the present follow-up study the exposure time (the exact time a man was working as a driver in this company) and the accident figures for the drivers were collected from the whole period of driving for the company. The total exposure time varied from 10.5 to 26.5 years with the mean of 16.6 years. A total of 66 of the original 100 drivers belonged to this follow-up group. A brief summary of the basic study is presented before the results of the follow-up period. SUMMARY
OF
THE
BASIC
STUDY
Statistical phase
In the statistical phase of the study information was gathered on approximately 4400 traffic accidents incurred by about 1000 bus and streetcar drivers employed by the Municipal Transport Company of Helsinki in 1947-54. An accident was defined as any traffic casualty incurred by a driver of a vehicle in motion, of which the management of the traffic establishment had knowledge. Every recorded accident was included without any limitation due to the amount of damage or the guilt of the driver. The mutual relationships of different accident categories were studied. The homogeneity of environmental factors was studied through the calculation of an index for each driver. His exposure time on each route was multiplied by the accident coefficient of
8
S.
HAKKINEN
the route (accidents per driver per year calculated from the whole material). The sum of these products was compared with the actual accident figures of each driver: Number .of accidents Length of time on the route X Act. coeff. of the route The ratio indicates the relative number of accidents per year for each driver after the elimination of the differences between routes. These rates were correlated with the original accident rates of all the drivers. The correlations were of a magnitude of 0.95. This correlation means that drivers had changed routes so many times that the real risk was nearly the same for all, and differences in accident rates were not affected by such environmental factors as routes. The reliability of the accident rates was investigated by the calculation of the correlations between the accidents incurred during two consecutive time periods, by analysis of the distributions of accidents and comparison of the group averages between consecutive time periods. These three methods yielded nearly identical results, and confirmed the assumption that constant personal factors exert a considerable influence upon accident rates. The reliability of accident rates increases with exposure time approximately in accordance with the SpearmanBrown formula (Gulliksen, 1950). Therefore lengthening the exposure time increases the reliability of accident rates, as for instance lengthening a psychological test increases its reliability. The correlations between the accidents in two consecutive years were on the order of 0.25435, and between two consecutive four-year periods on the order of 0.60470 (Table 1). When the exposure time was sufficiently long, eight years for instance, the reliability of accident rates was sufficient to serve as a criterion in experimental studies. In regard to the type of accidents, the total number of accidents proved more reliable than the variables formed on the basis of the various sub-divisions made according to type, size or responsibility. Collisions have, however, at least to some extent, a nature of their own, a finding which appeared ‘in both the statistical and the experimental phases of the study. Table I. Correlations
Length
between accidents in two successive time periods, and the reliabilities for the sum of these periods [Hlkkinen 1958. p. 30. 38, 391 Correlation
of
exposurr
between
year-s
time,
ir,ztcar
::-;,,eri
aus
drivers
calculated r
rEl
,3a
I-
$36
=r.1
.53
IN = 3221
.64
.45
.62
(N = 1411
.35
.52
.:7
4
IN = lcll)
4/4
a
years
l-4/5-4
.67
.dl
.5a
. 73
.3a
.a1
1*3+j+i/ 2.4+6*8
:3 ,N = 44)
Reliability 2r
coefficients
caiculated
:N = 521
from
Spearman-St-own
formula:
Traffic accidents and professional driver characteristics:
a follow-up study
9
Personal factors, as defined in terms of accident rates, may appropriately be split into constant factors, the factors which change with time (such as age, driving experience and the time of employment by the transport firm concerned), and the variable and incidental factors [Htikkinen, 19641.The possibility of revealing the constant factors is decisively influenced by the degree of homogeneity of the groups studied in respect to the changing factors mentioned. If the group is composed of drivers differing in age and length of employment, for example, the effect of the constant factors is overshadowed by that of those factors displaying strong changes. These changes may have opposite effects during the period of exposure, and thus the accident rates seem to have no reliability. Only if the material is well controlled in these respects can the effect of the constant factors be clearly demonstrated.
Experimental
phase
In the statistical phase of the study, individual accident rates were established as reliable enough for use as a criterion in an experimental study. Such a study was carried out with 100 drivers, almost one-half of whom were streetcar drivers and the rest bus drivers. The period of exposure for most of the drivers was about eight years and the reliability of the accident rates was, for both of the groups, more than 0.80. The groups were volunteers, but they were selected so that the means and standard deviations of their accident rates did not differ significantly from those of ail the experienced drivers employed at that time in the company. The psychological testing was performed from five to seven years after the beginning of the exposure time. Fourteen tests were used. A detailed description of the tests and references were given in the original report [Hikkinen, 19581.The tests covered the following areas: 1. Intelligence and mechanical aptitude. Paper and pencil tests with emphasis on reasoning and space perception: The Square Test, The Path-tracing Test and Mechanical Comprehension. 2. Simple motor speed and coordination. Reaction time and two-band coordination: Tapping and Fork. 3. Choice reaction and driving apparatus tests. These consisted of: The Clock Test, which tests for factors such as attention span, anticipation and correct timing. The Driving Apparatus Test (DrT), which is a choice reaction test requiring the subject to respond to four different kinds of stimuli with specified hand and foot movements while keeping a stylus, which is moved by means of a steering wheel, on a winding “highway”. This task as a whole required constant concentration and coordination despite disturbances and increasing difficulties. The subject’s driving experience does not influence his performance on the test. The Expectancy Reaction Test (ERT), which was designed to test whether the speed of motor performance is relatively higher than the speed of perception (i.e. whether a person acts before he really knows what sort of action is required). The test is a visual disjunctive reaction test in which the subject must respond to stimuli of a specified kind with a simple hand movement; the situation is made more difficult by means of distractions included in the test or external to it. 4. Psychomotor personality function. A psychomotor test was regarded as a personality test if the principal aim of the experiment was to draw conclusions concerning the characterologicai attributes of the subject on the basis of motor performances, muscle movements and muscle tension. They consisted of: The Ambiguous Situation Test (AST), in which the graphic record of movement made by the subject in response to certain clear, difficult or ambiguous stimuli, is studied for Lhe way in which the subject organizes his activities for hastiness, indecisiveness, lack of movement control, etc. and also for evidence of neurotic traits which are thought to exert an impairing and paralyzing influence on his performance in stress situations. Myokinetic Psychodiagnosis or Mira Test, in which the subject must retrace-certain simple patterns by drawing with a pencil without being able to see what he is drawing. The rationale behind this test is that certain personality traits are reputed to be associated with certain types of deviation from the original pattern. The Body Sway Test, which tests for suggestibility, and through it, for lability and neuroticism. 5. Questionnaires and interview variables.
IO
S. HAKKINEN
The Personality Inventory, which was derived from the inventory of Murray and that of Eysenck and tests for factors such as neuroticism, emotionality, calmness, self-assertiveness, and aggression. The Traffic Questionnaire, which was designed to test the subject’s attitudes towards traffic rules and regulations and towards accidents. Other interview variables were, for instance, biographical data and ratings on clear and frank vs vague, uncertain and concealed answers, and calmness vs nervousness. The test results were analyzed in a variety of ways: the reliability of the test variables, comparisons between the safe and accident groups, intercorrelations between the test variables themselves and the accident criterion, and a factor analysis of these correlations. Some of the results are presented together with the follow-up study in Tables 5 and 7. Both driver groups were divided into two equal parts on the basis of the accident coefficient. The better half was called a safe group and the worse half an accident group. The results of all 300 test variables were first compared between these groups. They may be summarized as follows: There were no significant differences in intelligence and mechanical aptitude tests between the safe and the accident groups. Reaction time was investigated by means of a number of different tests in simple, disjunctive and choice reaction situations. The differences between the groups were small, and none were significant. The intraindividual variability of reaction times did not prove valid for the accident criterion either. Simple motor speed, as measured, for example, by the Tapping Test, was often somewhat greater for the safe than for the accident groups, while the decline in speed during the test was stronger for the accident groups. None of the variables yielded significant differences however. In eye-hand coordination the accident groups, as a rule, did worse than the safe groups. Significant differences between the averages were found, especially within the streetcar driver groups, for three tests involving coordination. As the work of the streetcar +ivers. does not involve continuous coordination, i.e. steering, the result shows that a general psychomotor factor is concerned. The correlations ranged from 0.10 to 0.35. Two types of choice reaction tests were used. In the Clock Test the stimulus field was in sight throughout the experiment, whereas in two other tests (the Driving Apparatus Test and the Expectancy Reaction Test) the stimuli appeared suddenly. In all three tests the speed was paced and the subject could not alter it. In the Clock Test, which requires correct “timing” and estimation of speed, hardly any significant differences were found. In the Driving Apparatus Test and in the Expectancy Reaction Test several variables were discovered which significantly distinguished the accident groups from the safe ones. The number of correct responses in the Driving Apparatus Test was one of the most valid individual variables registered in the test battery (r = 0.42). Different kinds of error variables also revealed significant differences between the groups. The highest correlations between the accident coefficient and these variables were 0.30-0.42. Three so-called psychomotor personality tests were included in the battery of tests. In the Ambiguous Situation Test the motor disturbances appearing in hand performance were more numerous in the accident than in the safe groups. Susceptibility to disturbances grew stronger when the difficulty of the situation increased. The most significant results were in the differences between the numbers of motor disturbances during so-called “wrong” and “correct” reactions. The highest correlations with the accident criterion were 0.30-0.43. For several variables of the Myokinetic Psychodiagnostic Test the performances of the accident groups deviated from the safe groups in a direction considered to be typical of unstable individuals. The results were not very constant for the variables corresponding to each other or for all of the sub-groups, but there were a few highly significant differences between the groups. In the Body Sway Test swaying under suggestion was almost significantly greater in the accident than in the safe groups, a fact which furnishes additional substantiation for the results of previous tests suggestive of lability. None of the 13 variables of the Personality Inventory including a total of 93 questions yielded significant differences between the groups.
Traffic
accidents
and professional
driver
characteristics:
a follow-up
study
II
The attitudes of the drivers towards traffic regulations and traffic accidents were examined by means of two series of questions. The only significant difference was that the accident groups ascribed traffic accidents to driver fatigue, strictness of schedule and length of shifts more frequently than did the safe drivers. No significant differences between the groups were found for such biographical data as the number of children or other family conditions, obtained from interviews or drawn from other sources. On the other hand, the rating made by the interviewer during the interview on the subjects’s behavior (calmness vs nervousness) distinguished the safe groups significantly from the accident groups. The interviewer did not know the accident history of the drivers. The results were generally similar for the bus and streetcar driver groups. Either no differences were discovered or the accident drivers differed from the safe ones similarly in both groups. This demonstrated a very important point, namely that the characteristics associated with accidents were similar for the bus and streetcar driver groups although the actual driving operations they performed were very different. Therefore, it was possible to combine the two groups into one to gain a general picture of the accident behavior of professional drivers. The factor analysis of 28 variables yielded six factors (Table 7) which may be given the following names: Intelligence. Attention, Coordination, Simple Reaction Time, Involuntary Control of Motor Functions, and Stability of Behavior. Of the criterion variables, the total number of accidents and the general appraisal in merit rating were included in the factor analysis. These two correlated to the extent of 0.60. The accident variable was the most strongly saturated on the Attention factor, which was primarily determined by the correct responses on the Driving Apparatus and the Expectancy Reaction Tests. Merit rating had its highest loading in the Stability of Behavior, which was characterized by certain variables of the Ambiguous Situation Test and the Mira Test, as well as the rating of behavior. Both criterion variables had their next highest loading in the Involuntary Control of Motor Functions. The variables descriptive of poor control were indicative of hastiness, susceptibility to disturbances and motor restlessness. The loadings of the criterion variables in Coordination were relatively low, and in Intelligence as well as in Simple Reaction .Tixne they were close to zero. Following the basic study, cross-validation studies were carried out with three groups comprising 160 drivers (100 streetcar drivers, 30 mail bus drivers and 30 truck drivers). The validity correlations for an abbreviated test battery were significant in every case, and they were of the same magnitude as in the basic study (Hikkinen, 1958, p. 168-177). When different criteria such as accidents, merit ratings and observations of driving were combined into one, the validity correlations increased as in the basic study. FOLLOW-UP
STUDY
Sixty-six of the same drivers continued working from 2.5 years to 18.5 years in the company after the basic eight-year period. Exposure times and accident coefficients of the basic, follow-up and total periods are presented in Table 2. The time span for the whole study was from 1947 to 1973. The psychological testing took place in the years 1952-54. The number of Table
2. Exposure
time and accident
coefficient
of the follow-up
group (N = 66)
Exposure
time
Aooidont
coefficient
Roan
SD
Rem
SD
Basic
7.31
1.06
1.50
0.91
Follow-up
9.32
4.11
1.55
1.29
16.62
4.27
1.52
0.99
Expowre period
Total
Total
period:
Range
of
accidents
Range
of
accident
coefficient
2 -
73
0.16
-
4.16
S. HIKKINEN
12
accidents during the total period ranged from 2 to 73 and the accident coefficient (the number of accidents per year of exposure) ranged from 0.16 to 4.16. The correlation between the exposure time and the accident coefficient for the follow-up period was -0.15, which is insignificant. The correlation between the accident coefficient of the basic eight-year period and the follow-up period was 0.56, corresponding to the reliability of 0.72 for the total exposure time. Therefore the reliability of accidents was on the same order of magnitude (0.80) as in the basic period. The accident behavior of professional city drivers seems to be highly constant over a period of driving of IO-26 years. As shown in the basic study, the differences in accident coefficients were not caused by environmental differences, e.g. by route differences. The same is true for the follow-up period during which each driver changed routes several times. A general conclusion can be drawn on the reliability coefficient for the whole period (0.72). It can be stated that no large changes were possible in the relations between the accident coefficient and test variables because the criterion variable was stable over the entire period. Therefore, many detailed analyses have been omitted in this report because of the similarity to the original results. Selectiveness of the follow-up group
A part of the original group of 100 drivers did not continue their job after the basic period. The differences in age and accident coefficient of these groups are compared in Table 3. The resigned group was older, and it had fewer accidents during the basic period. Both differences were significant at the level of 0.05. The accident history had not caused the job change, but the subjects had moved otherwise to another vocation or retired as seen from the personnel records. In the follow-up group the correlations between age and accident coefficient was -0.26 for the basic period, 0.00 for the follow-up period and -0.10 for the total period. In the earlier stage of age and experience, accidents declined a little, but later the constant nature of the accident history continued, as revealed by the reliability coefficients. The follow-up group was divided into two equal parts according to age, and the accident coefficient was calculated for the basic, follow-up and total periods (Table 4). The accident coefficient of the young sub-group declined and that of the old sub-group grew from the basic to the follow-up period. The changes were not significant, but the direction of the changes revealed a general tendency. The young group entering middle age improved their driving habits and the old group over 50 years of age had some difficulties in traffic (Cresswell and Froggatt, 1963; Hiikkinen, 1954). The significance of the age factor was slight, however, when compared with the significance of stable individual characteristics. Validity of psychological tests based on basic and follow-up accident criterion
As a starting point, the ten highest correlations between the accident coefficient and the test variables for the original and for the follow-up group in different exposure periods are given in Table 5. In the basic period, correlations for the follow-up group were somewhat higher than for the basic group. The differences were not significant, but they showed a tendency similar to the one found in the original study, where validity correlations for the young group was higher than for the old group [Hikkinen, 1958, p. 1671. As presented earlier, the make-up of the follow-up Table
airth
3. .4ge and accident
date
Accioent
coefficients
of the follow-up
and resigned
Follow-up grcup
Resigned gmup
N - 66
N-34
Mean
SD
mean
so
7912.23
5.57
1909.74
5.4i
1.50
0.31
0.98
groups
coefficient
(Basic period1
“J.?B
t - 2.35 p = 0.05 t = 2.42 3 = Cl.05
Traffic accidents and professional driver characteristics:
13
a follow-up study
Table 4. Accident coefficient of the young and old sub-groups Young
group
N = 33
EXpOSUrS
period
Old
group
N -
33
mean
SD
Meen
so
Basic
1.67
0.91
1.33
0.89
Follow-up
1.46
1.12
1.65
1 .46
Total
1.53
0.88
1.46
1.10
Birth
date,
mean
Age in the of follow-up
1916.8
beginning period
Table 5. Highest correlations
1907.7
36 years
47 years
between the accident coefficient and the test variables. The mean exposure time appears in parentheses
_
Basic
Basic (7.23
AST, mtor
2.
DrT, correct
Follow-UP study
N - 100
Test veri&leX
1.
study
disturbewes
I
reactions
3.
DrT, simple
4.
Rating of behavior
steering
N = 66 Basic
yeanl
(7.31
years1
Fol lau-up
Total
(9.32
(16.62
years)
.43
.49
.43
.%I
.42
.49
.41
.40
.34
.47
.57
.61
.34
.26
.17
.22
5.
ERT. superfluws
.32
.42
.43
.4B
6.
ERT, correct
reactions
I
.32
.40
.32
.39
7.
ERT. correct
reactions
III
.32
.29
.35
.37
.32
.41
.34
.42
II
.27
.20
.25
.29
DrT , BrrOrS
.26
.33
.16
.23
Mean of correlations
.30
.38
.34
.40
8.
DrT, missed signs
9.
AST, mtor
10.
mactions
disturbances
’ In every variable
the positive
sense cornponds
yea&
to good perfomanca.
group was selected towards a younger direction. Validity correlations of the follow-up group in different exposure periods were on nearly the same order of magnitude. None of the correlations differentiated significantly in any row. When the accident coefficient for the whole period was used as the criterion, the validity of the test variables was as high as, or higher than, those for the original period. The means of the ten highest correlations (according to the basic study) were in the basic, follow-up and whole periods 0.38, 0.34 and 0.40, respectively. It is important to point out that the time lapse between the psychological testing and the follow-up period ranged from 1 to 20 years, the mean being more than 10 years. Multiple regression analysis
Stepwise multiple regression analysis was used to calculate the highest correlation between the accident coefficient and the combined result of 18 test variables. Table 6 contains the results
14
S. HKKKINEN
of the regression analyses for different exposure periods when 5, 10 and 18 test variables were used for the calculation. The multiple correlation varied from 0.71 to 0.81, which means that 50-65% of the total variance of accidents was explained by the test variables used. Five test variables already gave a rather good validity, and the correlations increased very little after the inclusion of 10 test variables. The predictive power of the tests was the highest for the total period. The test variables included in the regression models of different exposure periods were approximately the same in each case. In the analysis of five variables four of them were the same in all three or two analyses. In the analysis of ten variables four of the same variables were included in all analyses and six in two analyses. The similarity of the regression models for different exposure periods means that no big changes had occurred in the ability and personality factors affecting safe or accident behavior in traffic during 20 years. Factor analysis Factor analysis was performed with 26 variables, 24 test variables, and Accident and Merit Rating variables. In Table 7 factor loadings for both the basic and follow-up groups are presented. The basic study group consisted of 100 drivers with an exposure time of about eight years. The analysis was made manually by means of the centroid method and a graphical rotation. The follow-up study group consisted of 66 drivers with an average exposure time of 16.6 years. The analysis was made by computer with the principal axes method and varimax rotation. The rotated factor loadings of six factors were both partly similar and partly different from each other. Factors of Intelligence (I, I), Attention (response orientation, II, 2) Simple Reaction Time (IV, 4) and Stability of Behavior (VI, 3) were quite similar. The composition of other factors differed more from each other. In the original analysis factor III was named Coordination and factor V Involuntary Control of Motor Function. In the new analysis factor 5 could be called Suggestibility and factor 6 Speed (or hastiness) of Performance. They were not very clear, however. In the original analysis the Accident variable was divided into several factors (II, V and VI). In the follow-up study the Attention factor was broader and included higher loadings than in the original study. The factor loading of Accidents was therefore very high (0.76) in the new second factor and low in all other factors. The Merit Rating variable was divided in the later analysis into two factors only, instead of the three in the original analysis. Differences between analyses may have been caused by the partial differences in the groups, changes in the accident variable and the different method used. Nevertheless, the general picture of the analyses was rather similar. Table
6. Multiple
correlations
between
the accident
Exposure Number test
of
coefficient
and the test variables
period
Basic
Follow-up
-otalX
variables R
R
Percentage explained
R
Percentage explained
Percentage explained
5
.?l
.51
.:1
.50
.?5
.56
10
.7a
.55
.76
.sa
.30
.6a
18
.75
.56
.77
.60
.ai
.65
‘Variables 5
test
contained variables:
in 9,
regression
16,
21,
10
test
variables:
_"_
18
test
variables:
_“_
(see
names
in
Tables
71
models 3
and
for
the
total
period:
a; l
10,
14,
22. _*_
26
and
!9; f
20,
12,
11.
5
28, and
7, 2C
5.
Traffic
accidents
and professional Table
.i;
7. Rotated
factor
.4‘
.32
.43
.4c
.
-.cz
.c:
.G1
.2:
.LY
.oc
-3c
.5z
.Ci
.3L
.3f
.cs
.iz
.5;
1:
.i;
.ic
.31
.ne
.05
.O‘
.sc
.3i
.5E
.c:
.oc
.‘a%
.5c
.34
.3c
.15
.4?
.3E
-.OE
.3”
.I5
.23
.SE
.11
.07
.33
.07
.CL
.4S
.55
.2e
.I6
.2E
.4e
.29
.?F
.;L-
-.;i
15. ERT, c~mit reactions III
.3:
characteristics:
-.&z
3;
.Zi
driver
7: -.Z’
.15
-.O’
-.G’
a follow-up
15
study
matrix
.67
.cn
.7E
1”
.5E
:i
.4>
.35
.47
.63
. ci
.S5
.E4
.,,
-.w i:
.li
.CE
.54
.??
.2;
.il
.6C
15
.c3
.37
c:
.31
.Ii
.43
.:i
.;
.I.
.4E
.I’
.‘5
.‘t
.6>
-.C'
.zs
.7S
-.;;
.27
.E9
.61
-.iZ
.ic
.51
.Ot?
.OB
.a5
ia
.39
.66
.38
.67
-.OQ
Lt
. .;
-.Cj
.t7
.6C
.2c
.52
.I4
.LE
.;i
-.L.
.i
.u
.Y
.23
.41
.4:
.10
se
.23
.5E
.2t
.:r
.74
.42
.54
.oi,
.34
.29
.3n
-.15
.45
.18
-.25
.43
.I3
-.I6
.?5
-.34
.c7
.lE
-.a
32
1% - .c:
.lO
.21
.09
-.I4
.43
.li
.2e
.I7
.53
.22
.il’
17. 457.
rasactior tim
.oo
-.27
.15
.P1
-.OR
.12
.28
-.,4
-.I,
.I3
.CE
IE. PST.
speed
.lE
-11
.I1
.2E
.19
-18
.1B
.23
.lI
-.I2
19. AST.
coordinatxm
.2E
.21
-.04
.I3
-.ZO
.42
35
.lO
.13
.50
3:
.53 .28
-.li
.4E
.5i
.45
.29
18
.‘1
-.05
.33
.I?
.18
.42
.os
.27
.53
.I0
20. AST. mtor dlstvmances
1
.35
.2C
-.01
.2c
.35
.OO
37
.37
.46
.04
08
21. AST, nutor aistumancas
II
.07
.2E
.30
.3c
.?3
-.04
37
.Ol
.6?
.09
.02
-
.18
-.O9
-.OE
.14
.61
.08
45
-.27
-.I4
-.13
.23
-.25
-.47
.43
.14
-.07
.07
.06
.41
-.06
20
-.I0
-.06
-.34
.I?
-.I3
-.lE
.20
.10
-.03
-.10
.23
17
.45
.31
-.10
.OO
.49
.I‘
-.:t
.o:
.27
.CS
.21
-.23
.OS
.37
.2E
.1e
-.I0
-.05
.lC
-.Cl
.PS
-.07
.19
.13
.21
.06
.1E
.14
.4'
.26
.,l
.17
.3S
-.i5
3;
.08
.34
24.
plira Tent,
25
6cdy sway. suggestitil:ty
26. Rating
t-r
o* Bshavior
As mentioned earlier, the driver group studied consisted of 37 bus drivers and 29 streetcar drivers. Both in the basic and follow-up studies the results were first treated separately for both groups. Because of the small size of the groups and the similarity of the results only the combined results have been presented in this report. Lkcriminant
analysis
The whole driver group was divided into two groups according to the accident coefficient of the total period, safe drivers (N = 32) and accident drivers (N = 34). The discriminant analysis was made using 18 test variables, the same as in multiple regression analysis. A computer program selected 7 from 18 variables which formed the discriminant function. These variables, F values, F values of additional information, coefficients of discriminant function and correlation coefficients with the discriminant function are presented in Table 8. The discriminant function primarily included the same variables found to be the most valid according to the correlation matrix, regression analysis and factor analysis. Response Orientation or Attention and Stability of Behavior described the feature of discrimination. Mechanical Comprehension and DrT Reaction Time (speed) had negative signs that showed that intelligence and reaction speed had combined negatively in the discriminant function. The correlations of these variables with the discriminant function were low, however.
S. H~KKINEN
16 Table
Test
8. Results
of discriminant F
variable
1.
Ol-T.
correct
reactions
2.
AST,
motor
disturbances
3.
Body
Sway,
suggestibility
4.
OrT,
choice
rsaction
5.
OI-T,
simpie
steering
6.
ERT,
superfluous
7.
Mechanical
I
time
reactions
Comprehension
analysis
F additional
Coefficient of discriminant function
Correlation
19.60
1.11
.71
.73
15.41
0.67
.45
.iO
12.20
0.47
.37
.33
9.82
0.38
0.24
0.30
.32
.54
7.07
0.25
.30
.55
6.41
0.13
-.26
-.32
.15
.17
The result of the discriminant analysis was checked with a classification procedure belonging to the usual computer program of the discriminant analysis (Table 9). This transfer matrix showed that the proportional number of drivers who remained in their original group or that of diagonal observations was 86.4%. This result reveals the high discriminant power of the seven test variables. Only 9 out of 66 drivers were classified erroneously by the discriminant function. Results of fictional selection procedures
The use of a fictional selection procedure gives a concrete picture of the prediction power based on the test battery or the accident rates of the basic exposure period. The whole group of drivers (66) was divided into two equal parts (A and B) on the basis of the accident figures in the basic period. The worse half was divided into B, and B2 (17 and 16). Both the absolute accident figures and percentages for each exposure periods are presented in Table 10. There were small differences in the exposure times of the sub-group but the accident figures were balanced into equal exposures. The total number of accidents subtained by the 66 drivers was 1607 during the whole (average) exposure period of 16.2 years. Had the drivers been selected for the second (follow-up) period on the basis of accident figures of the basic period and had the average accident rate for the selected drivers been the same as in the better half (A), accidents would have numbered 351, or 39.0%, fewer than they did in reality during the follow-up period. If only about one-fourth (B2 = 16) of the worst drivers had been replaced by the average of others (A + B, = 50), 230 accidents would have occurred, or 25.5% fewer than in reality. In general, the figures in Table 10 reveal the constancy of accident behavior in each group. The accident percentages of groups A and B, level off from the basic to the follow-up period by about 5%, but the worst group, BZ, is the most stable, the change of percentages being only 1%. Table
9. Classification
according
to discriminant Computed
Original
Percantage
grauo
of
diagonal
function
group
1
2
1
27
5
2
4
30
observations
-
86.4
Trallk
Table
IO.
Results of fictional selection procedures Accident
Accidents basic
of
of
Basic
Follcw-up
N
I
II
I
l
II
I
II
I
l
II
A
33
177
275
452
25.1
30.5
28.1
B
33
529
626
1155
74.9
69.5
71.9
8,
17
214
233
447
xl.3
25.9
27.0
B2
16
315
393
708
44.6
43.6
44.1
66
706
901
1607
100
100
100
A . B
If B were replacedby A: If
Whole
half
drivers
Total
Group
half
drivers
Worse
Percentage
+igums
in
period
Bettsr
17
accidents and professional driver characteristics: a follow-up study
B2 ware
replaced
by A
351 or 39.0 f fewer accidents
l
8,:
230 or
25.5
Z fewer
accidents
In Table 11 a similar calculation was made on the basis of the sum of the five best test variables according to the basic study. The combined variable is the sum of the normal scores of variables l-5 in Table 5. Had this combined variable been used for the sekction of drivers for the follow-up period and the worse half of the driver group been replaced by the average of the better half, accidents would have numbered 409, or 45.4% fewer than did occur during the follow-up period. Therefore the predictive power of the combined test variable seems to be better than that of the information on accident figures for the basic eight-year period. The test variable would measure “potential” accident behavior in the future better than the accident figures gained in the early stage of driver experience. The correlations between the combined test variable and the accident coefficient for the basic, follow-up and total periods are 0.62,0.60 and 0.66, respectively, which are a little higher than the correlations of the accident coefficients between the basic and the follow-up periods. Calculations were also made in which the combined test variable was used for the selection of drivers before the beginning of the total period. If a half-and-half system (CID) were used as earlier, 609 accidents, or 37.9% fewer accidents would have occurred during the total exposure period. If the average of only the worst drivers (4 = 16) had been replaced by the average of the others, 152,213 and 365 fewer accidents (21.5,23.6 and 22.7%) would have occurred during the basic, follow-up and total periods, respectively. The preceding calculations made for the fictional selection procedures reveal the practical value of the knowledge of accident figures and of the test battery used. DISCUSSION
The follow-up study shows that the accident behavior of professional city drivers is highly constant over a period of driving of more than 25 years. There are only a few studies in which the same driver group has been followed under controlled circumstances over several years. Usually the exposure period has been short and the environmental risk @oorly controlled. In the study of Dvorak and Linke (1976) the reliability of accident criterion was 0.67 for 239 locomotive engineers in the German Federal Railway for a period of 18 years. Bach, Bickel and Biehl (1975) found the correlation of 0.76 between accident rates of two four-year periods (N = 35). The driver group in our study was small, and it is possible to claim that “pure chance” arranged this constant group and a permanent situation across the years. A cross-validation study with 160 drivers supported earlier findings, however. After these studies an abbreviated AAP Vd.
II. No. 1-B
18
S. HAKKINEN Table
Il. Results of fictional selection procedures Accident
GrWp
Sun of five teat
variables
Better
half
If
C
l
0 were
Whole
I
I
33
253
246
Cl 33
453
0,
17
D2
c
I
II
499
35.6
27.3
31.1
655
1108
64.2
72.7
66.9
167
275
442
23.7
30.5
27.5
16
266
360
666
40.5
42.2
41.4
0
66
706
901
1607
100
100
100
replaced
200
409
609
26.3
45.4,
37.9
21.5
23.6
22.7
by C:
fewer If
O2 were
by C + 0,:
* II
x + II
of
drivel-3
Total
Follar-up
I
N
of
drivel¶ uon?.a half
Basic
Percentaga
figures
accidents
replaced 152
273
365 fever
accidents
battery of tests was used for the selection of professional drivers for several years and new cross-validation studies were performed. The accident criterion for only 2-3 years had a reliability of 0.20440. Therefore, validity correlations were low, but they had a trend similar to that shown in this report. The aim of this article is not to overemphasize the role of personal factors in tragic safety. Generally, it is not possible to use and control complicated psychological tests for large groups, nor is there any way of knowing the test validity for different socio cultural populations, as pointed out, for example by Haight [1!972], Harano, McBride and Peck [1973] and Peck, McBride and Coppin [ 19711.However, with well-planned and controlled studies it is possible to detect relevant human factors which in general accident statistics and larger studies, are overshadowed by many changing and uncontrolled factors.
REFERENCES Bach H., Bickel H. and Biehl B.. Validierung van Testverfahren zur Fahrer-Auslese Verkehrssicherheit 21.21-38, 1975. Cresswell W. L. and Froggatt P., The Causation of Bus Driuer Accidents. Oxford University
am Uofailkriterium.
2. f.
Press, London, 1963. Dvorak H. and Linke J., Haufigkeit and Fahrlassigkeit von Unfiillen als Kriterien zur Testvahdierung. 2. /. Verkehnsicherheit 22, 59-63. 1976. Gulhksen H., Theory of Mental Tests. Wiley, New York, 1950. Hai@ F. A., Recent publications. Accid. Anal. Preu. 4, 353355. 1972. Harano R. M., McBride R. S. and Peck R. C., The Prediction of Accident Liability through Biographical Data and Psychometric Tests. Department of Motor Vehicles, State of California, Final Report 39, 1973. H&men S., Age and road accidents. Nordisk Psykologi 6,77-92, 1954. (Swedish). H&kinen S., Tm$ic Accidenrs and L%ver Characteristics. A Statistical and Psychological Study. Finland’s Institute of Technology, Scientific Researches No. 13, Helsinki, 1958. H&kinen S., Functional classification of human factors in accidents. Excerpta Medica fntemational Congress Serirs 62, 1669-1671,
1964.
Klein D., Accident proneness revisited. Contempomry Psychology IS, 549-550, 1973. Peck R., McBride R. S. and Coppin R. S., The distribution and prediction of driver accident frequencies. Prev. 2,243-299. 1971. Shaw L. and Sichel H., Accident Proneness. Perpmon Press, Oxford, 1971.
Accid.
Anal.