dmq

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ERGONONUCS

1993,

VOL

36,

NO

6, 627-644

Decision making style driving style and self reported involvement in

road traffic accidents

D.

J. FRENCH,

R.

J. WEST,J. ELANDERnd J. M. WILDING

Psychology Department, Royal Holloway and Bedford New College, University of London,

Egham, Surrey TW20 OEX, UK

Keywords

Driving; Accident involvement; Survey; Questionnaire; Decision-making; Driving

style.

In an exploratory postal survey of 711 drivers stratified by age, sex, annual

mileage, and accident involvement, decision-making style was measured using a

Decision-Making Questionnaire (DMQ) and driving style was assessed using a

Driving Style Questionnaire (DSQ). Responses to 21 items of the DMQ formed

seven independent and internally coherent dimensions according to a principal

components (PC) analysis. These were labelled: control, thoroughness,

instinctiveness, social resistance, hesitancy, perfectionism, and idealism. PC

analysis also revealed that responses to 15 items of the DSQ formed six

independent dimensions of driving style. These were labelled: speed, calmness,

social resistance, focus, planning, and deviance. Multiple regression analysis

indicated that drivers of 60 years and under who scored lower on thoroughness

were at greater risk of a traffic accident and that this relationship was mediated by

faster driving. This relationship was independent of age, sex, annual mileage, and

all other factors measured. In the drivers over 60 years, lower thoroughness,

greater hesitancy, and faster driving were independently associated with higher

accident rates independent of all other factors measured. The results provide

preliminary support for the view that people import aspects of their general

decision-making style into the driving situation, and that in so doing they put

themselves at differential risk of having a road traffic accident.

1. Introduction

Previous research has in general failed to reveal an association between psychomotor

ability and road traffic accident rates (Goldstein

1961).

Factors which have emerged

as predictors of accident involvement (taking account of annual mileage) include age,

experience, ability to detect hazards quickly and tendency towards risk taking

(Brown and Groeger 1988, Jonah 1986, Mayhew

et al

1981, Quimby

et al

1986). It

may be that differential accident involvement has more to do with the way that

people make judgements and decisions than merely ability to control the car, e.g., the

decision to overtake, change lanes, accept a gap of a particular size when parking, etc.

Thus it seems plausible that decision-making would be a useful focus for research

efforts aimed at understanding differential accident involvement.

There are two main ways of approaching the study of decision-making. One is to

examine the beliefs and values that enter into the decision process (e.g., Edwards

1954, Fishbein and Ajzen 1975). This has been the subject of much research in

psychology. The other is to examine the style of decision-making, i.e., the way that

individuals habitually approach decision problems and use information. Little

research has been directed at this latter issue. The present research programme was

designed to investigate possible relationships between decision-making style and

road traffic accident liability. A major feature of this approach has been to collect

information about general aspects of decision-making and relate these to accident

()()14-0139/93 1O ()()

1993 Taylor

Francis Ltd.

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D French

et al.

liability by looking at the way that they are reflected in driving style e.g., choice of

speed).

Style of decision-making involves those aspects of the decision process in which

individuals may be presumed to adopt a common mode of operation across a wide

range of decision domains. Thus for the concept to apply there must be cross

situational stability. Examples of decision-making style may be: how far individuals

are prepared to examine the pros and cons of various options before making up their

minds; the level of risk that they will accept in return for an optimum outcome; and

the relative importance of emotions in making a decision which could be reached

analytically.

There are several existing questionnaire measures of decision-making style. One of

these Buck and Daniels 1984) was developed from Harren s 1979) Model of Career

Decision-Making. Individuals are characterized by scores on one of three scales:

rational, intuitive, or dependent. Rational decision-makers seek relevant information,

look carefully at future consequences, and act deliberately and logically. Those who are

intuitive in their decision-making show little anticipation of future consequences or

systematic information-seeking. Dependent decision makers do not take

responsibility for their decisions, but take the path of least resistance, having a high

need for social approval. Arroba 1977) devised a classification of decision-making

which was applied subsequently to career decision-making by Hesketh 1982).

Arroba s taxonomy was derived by interviewing subjects regarding recent decisions

that they had made; six styles of decision-making emerged. These were emotional,

intuitive, rational, hesitant, compliant, and no-thought. The six styles were found to

fall along an active-passive continuum, with rational and hesitant being the most

active and compliant the least active. Hesketh found that one year after careers

counselling, subjects who had reported a rational decision-making style were most

likely to have achieved a match between their aspirations and their current situation,

whereas emotional and compliant individuals were least likely to have done so.

Johnson 1978) has proposed a more general theory of decision-making style, but

this too has been investigated and reported only in the context of careers counselling.

It proposes two independent aspects of decision-making style; information gathering

and information analysis. Information may be gathered spontaneously or

systematically and analysed internally or externally. A questionnaire, the Johnson

Decision-Making Inventory JDMI-Johnson

et al

1983), has been designed to

assess these dimensions.

Gordon

et al

1986) studied the relationship between Johnson s dimensions and

Harren s styles, which were assessed using the Assessment of Career Decision

Making Scale ACDMS-Buck and Daniels 1984). A factor analysis of the scale

scores, three from the ACDMS and four from the JDMI, showed that the first factor

was identified by strong positive loadings for systematic John son) and rational

Harren) and an equally high negative loading for intuitive Harren). The second

factor was characterized by positive loadings for external and spontaneous Johnson)

and dependent Harren). The third factor was Johnson s internal.

The link between Johnson s and Harren s inventories suggests that, by self-report

at least, there is an identifiable trait of decision-making style; conceptual similarities

between these and Arroba s 1977) taxonomy support this conclusion. Had Arroba s

styles been included in Gordon

et al s

investigation, one might have expected further

factors to emerge, indicating that neither the JDMI nor the ACDMS are identifying

the full range of decision-making styles.

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629

All of the above attempts to characterize decisions and decision makers have

potential contributions to make to a comprehensive account of individual

differences in decision-making style. However, there is no comprehensive decision

making questionnaire available.

This paper reports the development of a questionnaire measuring general

decision-making style and its relationship with driving behaviour, also measured by

questionnaire, and involvement in road traffic accidents. The ultimate aim was to

trace a path from certain aspects of decision-making style to differential likelihood of

accident involvement.

2. Methods

2 1 Materials

In order to develop a questionnaire on decision-making style, a number of ways in

which the decision process might differ were generated. Some of these corresponded

to dimensions used in questionnaires already in existence. Thus Johnson s

internal/external distinction and the compliant and dependent dimensions were

represented by items about preference for consultation and advice and susceptibility

to social pressure. The emotional and logical versus intuitive categories were

reflected in questions about the role of feelings in decision-making.

Questions were also added asking about locus of control Rotter 1966). In

addition, examination of normative theories of decision-making Simon 1957, Janis

and Mann 1977, Edwards 1954) led to consideration of depth of search through

consequences of courses of action, breadth of search through different options,

degree of planning ahead, use of principled versus pragmatic solutions, use of

satisficing versus optimizing decision rules, risk acceptance, degree of certainty about

a decision, and level of commitment to it.

Several versions of a questionnaire containing items relating to these dimensions

were tested and items deleted or modified according to whether subjects appeared to

be able and willing to answer them consistently and informatively.

This resulted in a 30-item Decision-Making Questionnaire DMQ). DMQ items

were phrased as questions asking about frequency of a given type of behaviour and

subjects were instructed to tick one of six boxes that indicated that they behaved in

this way: never or very infrequently, infrequently, quite infrequently, quite

frequently, frequently, very frequently or always.

A questionnaire about driving style was also developed. The choice of items for

inclusion was based on behaviours that had previously been shown, or were

suspected, lo be related to accident involvement or risky driving behaviour. These

were speed Wasielewski 1984), headway distance to the car in front-Evans and

Wasielewski 1983), seat belt use Evans et al 1982), gap acceptance size of gap in the

flow of traffic before attempting to pull out-Bottom and Ashworth 1978), and traffic

light violations Koneci et al 1976). In addition, the questionnaire included items

about behaviours thought to be directly related to decision-making style. For

example, specific questions about feeling in control when driving, some of which

were based on Montag and Comrey s 1987) scale of driving internality and

externality which proved to have a reliable factor structure, were included. Questions

were also asked about reactions to advice when driving, route planning, and risk

taking on the road. Responses were on the same six-point scale of frequency as the

decision-making questionnaire.

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D. French et al.

The DMQ and driving style questionnaires were put together in a package which

also included questions about biographical details, miles driven annually and

accident involvement during the previous year. Data on accident involvement for up

to three years prior to this was available from a questionnaire previously completed

by the same subjects see below).

2.2. Subjects and procedures

The questionnaire package was sent to 980 drivers in all parts of the UK. The sample

was a subset of 30 000 drivers who had previously been randomly selected from those

licensed at the Driver and Vehicle Licensing Agency DVLA) Swansea to take part in

a questionnaire survey conducted by National Opinion Polls for the Transport and

Road Research Laboratory. In the survey, they gave details of their driving habits

and accident records for the past three years, as well as personal details, and at the

end indicated whether they would be willing to help with further research. The data

gathered during this exercise provided information necessary for stratification ofthe

sample selected for this study by age, sex, annual mileage and accident involvement.

Thus our sample was not representative of the population at large, but it enabled us

to take account of the relationship of exposure, age, and sex with accident rates.

Table 1 shows the stratification of the sample.

Table 1.

tratification of the sample.

ge

8-24

25-590+Low

o accid.

0

0

5

2: 1 accid.

00

5

No accid.

0

0

5

2: 1 accid.

00

5

Lowo accid.00

4

2:1 accid.

005

No accid.

005 2: 1 accid.

0

06

ales-

ow mileage

=

1-10765 miles p.a.

high mileage> 10765 miles p.a.emales-Iow mileage

=

1-4848 miles p.a.

igh mileage>4848 miles p.a.

Completed questionnaires were returned by 711 drivers, 73 of those who were

sent one. There was a tendency for a slightly higher response rate among older

subjects chi squared

714 with 2 degrees of freedom,

p

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6

(3) assessment of the internal coherence and derivation of subscales for the

Driving Style Questionnaire (DSQ);

(4) investigation ofrelationships between DSQ scores and age and sex;

(5) investigation of relationship between decision-making and driving style and

accident rates;

(6) modelling of the role of decision-making style and driving style in the

causation of accidents using multiple regression.

Some of the variables used in the analyses did not conform to a normal distribution

therefore differences and correlations were analysed using both parametric and non

parametric methods, with near identical results. For the purposes of presentation

parametric statistics arereported throughout. In tests of significance, two-tailed tests

were used unless otherwise indicated.

3. sults

3 1 Internal coherence and derivation of subscale scoresfor the DMQ

A principal components analysis of the DMQ yielded seven components with

eigenvalues greater than one. Together they accounted for 543 of the variance.

These seven independent dimensions were interpreted by examining the contents of

the variables loading highly upon them. Table 2 shows the item loadings on each of

the components after varimax rotation. A criterion of 04 as used as the minimum

loading for an item to be incorporated in a dimension. Nine of the 30 items did not

meet this criterion for any dimension and were excluded from further analysis. The

Table 2. Items loading on the dimensions of decision-making style.

Factor

I. Thoroughness

(179 of variance)

2. Control

(95 of variance)

3. Hesitancy

(79 of variance)

4. Social resistance

(65 of variance)

5. Perfectionism

(58 of variance)

6. Idealism

(52 of variance)

7. Instinctiveness

(50 of variance)

*Item abbreviated.

Loadings

079

-070

065

064

076

075

072

-058

-045

070

057

055

070

-057

055

070

069

080

-069

067

061

Items

Do you work out all the pros and cons?*

Do you decide without considering all the implications?*

Do you plan well ahead?

Is your decision-making deliberate and logical?*

Do you remain calm?*

Do you enjoy making decisions?

Do you feel in control of things?

Do you avoid making decisions if you can?*

Do you find it difficult to think c1early?*

Do you favour first one option then another?*

Do you change your mind about things?

Do you take the safe option if there is one?

Do you avoid taking advice over decisions?

Do you like to consult with others?

Do you make up your own mind about things?*

Do you carry on looking for something better?*

Do you settle for an option that will just about do?*

Are practicalities more important than principles?*

Are your decisions governed by your ideals?*

Do you rely on gut feeling when making decisions?

Do you stick by your decisions come what may?

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FIG 1a CONTROL

SUBSCALE SCORE

30

I

SEM

8

26

French et al.

FIG 1b THOROUGHNESS

SUBSCALE SCORE

5

I SEM

3

21

24

22

//

/-..j

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FIG 1e PERFECTIONISM


FIG 11IDEALISM

633

SUBSC ALE SCORE

15~------

I S.EN

13

11

9

~

SUBSC ALE SCORE

15 ~,-----~-----------~

I S.EM

13

11

9

- /: >

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D.

J.

French

et al.

elationships of decision-making dimensions with age and sex.

Correlation

Males scores

emales scores

n=343

n=366

value for

n=709

ean

D

ean

D

ex difference 020***

77168216108

015***

3413

2216

49*** -014***12

14

1-315

091

008

515

415062

-014***9

19

9

19020

017***6

187

17

076

009**

2

17

617

2 79**

*p

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FIG 2a SPEED


FIG 2b CALMNESS

635

SUBSCALE SCORE

15

I SEM

13

SUBSCALE SCORE

20 I - - - - -- - - - - -- - - - - --~

I

SE.M.

18

11

16

9

+-,

+----+

,

,

,

,

+----+..,

,+

14

12

~

/

/

-+---+- _-I

v --,+--

10 ~I-~--~-~ __ __L __ _'_ __ _'__ _ __1

5

2 3 4

AGE CATEGORY

- MALES -+ FEMALES

FIG 20 PLANNING

3 4 5

AGE CATEGORY

- MALES

-+.

FEMALES

FIG 2d FOCUS

6

SUBSCALE SCORE

15

I S.E.M

13

11

SUBSCALE SCORE

20,--------------------,

I SEM.

18

16

9

-+----+

/,

/

/

+-_---1

14

12

~-+

*---+-- //

-

+---- //

2 3 4 5

AGE CATEGORY

- MALES -+. FEMALES

10

3 4

AGE CATEGORY

- MALES -+ FEMALES

6

3 3 Internal coherence and derivation of subscale scoresfor the DSQ

A principal components analysis of the driving style questions revealed six

components accounting for 394 of the variance. The six dimensions were

interpreted as speed (made up of items about driving fast and exceeding the speed

limit), calmness (items about staying calm in dangerous situations and when there is

little time to think), planning (consulting a map and planning places to stop and rest

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FIG 2e SOCIAL RESISTANCE

D J French

et al.

FIG 21 DEVIANCE

SUBSCALE SCORE

15

r-------------------,

I S.E.M.

13

11

9

-~--- .-

- -

..... , --

-

,

,

---

SUBSCALE SCORE

10

r-------------------~

I S.EM

8

6

4

~- --

r- __ _..I

__ --

r-- _ _..J......_

-- -

2 3 4 5

AGE CATEGORY

- MALES -+ FEMALES

6

I

o~ -~-~-~-~~-~-~-

3 4 5

AGE CATEGORY

- MALES

-+

FEMALES

Figure 2. Driving Style Questionnaire DSQ) subscale scores broken down by age group and

sex. Age group 1= 17-19; 2=20-29; 3=30-39; 4=40-49; 5=50-59; 6=60 and over.

before setting out), focus driving cautiously and ignoring distractions), social

resistance disliking being given advice about driving), and deviance jumping the

lights and overtaking on the inside). Table 4 shows the dimensions, the percentage of

variance that they accounted for and the item loadings. As with the DMQ, subscale

scores were calculated for driving style dime.,,:sionsby reversing the coding of ratings

with negative loadings and then adding up the items with loadings greater than 04.

Also, as with the DMQ, separate principal components analyses were carried out on

two randomly-selected subsamples each comprising half of the full sample. The

resulting loadings were similar in both subsamples and both were similar to the

results of the analysis on the full sample, indicating a stable structure.

3 4 Relationships between DSQ scores and age and sex

The relationship between each driving style dimension and age and sex was tested

using Pearson s

R

correlations to investigate changes with age and

t tests

to look at

the sex differences. In the case of deviance and planning scores, we also examined

relationships in which these variables had been recoded into dichotomies to avoid

the problem of undue influence of extreme scores. The results were nearly identical to

those using the untransformed variables so, for the sake of presentational

consistency, we report the simple Pearson correlations here. The mean-scores for

each age group of males and females on each dimension were examined in order to

establish the nature of the relationships. Figure 2 shows the results graphically. Table

5 shows the correlations with age, and the sex differences in the driving style

dimensions.

Speed showed a steady decrease with age in both sexes and females scored lower

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J.

French

et al.

measure. The annualized accident rate for the three years prior to our study (the total

number of accidents divided by the reporting period in years), as determined by the

NOP survey which preceded ours (see section 2), was correlated with the rate during

the following year as assessed by our postal questionnaire. This yielded an

R

of

O

305

(p

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Decision-making and RTAs

639

Fig 3a Drivers aged 60 and under

-.12 p

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D French et al.

Table 8. Correlations of age, sex, mileage, and DMQ subscale scores with speed in 60s and

under and over 60s.

60 yrs

Thoroughness

Hesitancy

Resistance

Perfectionism

Idealism

Instinctiveness

Age

Sex

Mileage

p

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Decision making and RT s

641

thoroughness appeared to be mediated by speed.

the over 60s, speed,

thoroughness, and hesitancy all played an independent role, and speed was predicted

by instinctiveness.

Part of the purpose of this study was to obtain a preliminary assessment of the

concept of decision-making style. We found that respondents to a self-report

questionnaire about their decision-making style gave answers which revealed quite a

large number of different dimensions. This contrasts with the theories of Harren

1979), Arroba 1977) and Johnson 1978). It is possible that there may be more than

the seven which emerged from our questionnaire, but on our data there are unlikely

to be fewer. The difference between our results and those of the studies emerging

from the previous theories is probably due to the fact that the DMQ canvassed a

much more diverse set of possible behaviours than did the previous questionnaires.

One of the major dimensions which emerged from the DMQ corresponded to

important aspects of the previous theories: the thoroughness dimension is similar to

the rational styles of Harren and Arroba and the systematic style of Johnson.

However, there can be little doubt that this is only one of many aspects of decision

making.

These data represent only the first step of a process of development and

validation of both the concept of decision-making style and its measurement. It is

one thing for self-reports of decision-making behaviour to be explicable in terms of a

set of dimensions such as we have proposed. It is another to show that the behaviour

itself can be thus explained.

According to our drivers self-reported behaviour they did carry their global

decision-making style into the driving situation. This offers the possibility that

important aspects of driving behaviour can be understood in terms of more generally

applicable traits that drivers may have. At a theoretical level it provides a way of

linking theories of driver behaviour with more general theories of cognition and

motivation. At a practical level it offers the possibility that aspects of driver

behaviour can be indexed in situations, from the respondent s point of view,

unrelated to driving. This may turn out to be useful if assessment of driver

characteristics becomes used in real-life settings which have implications for

individual drivers.

It is only possible to speculate at this stage what might underlie the relationships

between thoroughness and preferred driving speed in drivers of 60 and under. One

obvious possibility is that low thoroughness is a reflection of a more global trait of

impatience. It is not difficult to see how impatience might lead people to drive faster.

One aspect of the Type A behaviour pattern involves a feeling of being under

continual time pressure and this may too be related to impatience.

this regard it is

interesting that one study has examined the relationship between Type A behaviour

and accident liability and found a positive relationship Perry 1986). To the extent

that extroversion and sensation-seeking also involve impatience, this factor may also

explain association between these variables and accident liability Pestonjee and

Singh 1980). Further research along these lines will be needed to dissect out the key

variable or variables here.

The direct association of hesitancy and thoroughness with accident rates in the

over 60s must be mediated by some aspects of driving style which we have not

measured or not measured adequately). It may be that for drivers of this age, ability

to process information rapidly is impaired Rabbitt 1991) and that if they do not

allow for this by being more deliberate in their decision-making, or if it results in

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them beginning manoeuvres and changing their mind this could raise their accident

risk. As regards the relationship between instinctiveness and speed in the older

drivers, it may be that a greater feeling ofthe infallibility of one s intuitive judgement

could cause drivers to fail to appreciate the risks they run by driving at higher speed.

Our observation of a link between self-reported driving speed and accident rates

is consistent with the findings of other studies Engel and Thomsen 1988, Wilson and

Greensmith 1983). Accident rates are a very imprecise measure of accident liability

as demonstrated by the low correlation between accident rates over two successive

periods. fact the correlation between speed and accident rates was not much less

than the correlation between accident rates measured over two periods. Thus the

importance of speed as a contributory factor to accident liability cannot be

overstated; faster drivers are relatively unsafe drivers. Our self-reported dimension

of speed has been shown in another study to correlate quite well with actual driving

speed.

the study concerned West et al 1993), the self-reported speed dimension

of the DSQ correlated 055 with the judgements of drivers preferred speed made by

two independent in-car observers during a mixed motorway and urban test route.

that study observed speed also correlated positively with accident rates. Thus, the

relationship between speed and accident liability is consistent and is not an artifact

of our self-report methodology.

The most plausible explanation for the relationship between driving speed and

accident liability is that a direct causal link exists between the two. Minor

misjudgements of distance or timing and unexpected hazards such as patches of ice

on the road are turned into accidents because of excess speed. However, there are

other possibilities which cannot be ruled out. It may be, for example, that faster

drivers engage in particular driving habits which put them at risk. For example, they

may pull out into smaller gaps than other drivers or attend less to the driving task.

Further research is needed to unravel the various possibilities. This may involve

obtaining further data about aspects of driving that are associated with speed, finding

out whether there are certain kinds of accidents to which faster drivers are

particularly susceptible, and assessing whether interventions directed at individual

drivers to reduce their speed reduces their accident rates.

Although deviant driving behaviour correlated significantly with accident rates,

in the multiple regression analysis it was not shown to play an independent role.

Current research indicates that a substantial number of accidents do occur as a direct

result of deviant driving Reason

et al

1991). However, in our sample they were

relatively uncommon. This may have been due to deviant drivers being less likely to

volunteer for the study. It is also possible that the deviant drivers were unwilling to

report their accidents. Finally, it is possible that there was under-reporting of deviant

driving behaviour. All these factors would act to attenuate the relationship between

self-reported deviant driving and accident rates. The possibility remains, however,

that in the totality of accident statistics, excess speed is a more important factor than

dangerous manoeuvres and that to the extent that traits of fast driving and deviant

driving are separable, fast driving may play a greater role.

Questionnaire methods such as have been used in this study can only be expected

to provide a broad indication of relationships between variables of interest. They

depend on respondents being able to form impressions of their own behaviour and

communicate these using a fixed response format. Thus error of measurement is

likely to limit severely the size of associations. Most of the correlations reported in

this study were low, but reached high levels of statistical significance by virtue ofthe

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large sample size. Thus, while the pattern of associations point the way towards

potentially important relationships and ultimately to a theory of accident causation,

for the practical prediction of accident rates, it will be necessary to develop and refine

the measures used, perhaps supplementing self-report questionnaires with other

forms of behavioural assessment. We have already mentioned the use of direct

observation of dl-iver behaviour. We are also examining ways of using computerized

tasks and presentation of real and hypothetical decisions as a means of assessing

decision-making style.

There is the danger when questionnaire responses are correlated with other

questionnaire responses, that at least part of the associations found reflect

consistency in response biases rather than underlying psychological dimensions of

interest. It is difficult to envisage how response biases could lie behind the particular

pattern of associations we found. The relatively large number of independent

dimensions of decision-making and driving style, and the relationships between

particular dimensions and accident rates would require a much more elaborate

conception of response biases than has been proposed in the literature.

In conclusion, this study has provided preliminary evidence on a new

questionnaire assessing decision-making style indicating that at least seven

independent dimensions can be isolated. One of these dimensions, which we have

labelled thoroughness, correlated significantly with accident rates. In drivers of 60

and under, this relationship appeared to be mediated by a single aspect of driving

style, preferred driving speed. The results suggest several further lines of

investigation which would help to provide a clearer understanding of why some

drivers have more accidents than others.

Acknowledgement

The work described in this paper was carried out under a contract placed with Royal

Holloway and Bedford New College by the Transport and Road Research

Laboratory, Crowthorne, Berkshire and the paper is published by permission of the

Director. The views expressed in this paper are not necessarily those of the

Department of Transport.

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Addison-Wesley, Reading, MA .

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Received 12 October 1990.

Final revison accepted 8 November 1991.

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