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Accident proneness: A conceptual analysis
ACCIDENT PRONENESS: A CONCEPTUAL
ANALYSIS
FR,G~; P. MCKENN;\ .LfRC Applied
Psychology
Unit.
Ii Chaucer
(Recricrd
Road, Cambridge
3 Murch
CB1 2EF.
England
1981)
Abstract-The concept of accident proncnsss has had a long and controversial history. An attempt is made both to demonstrate the nature of this controversy and to investigate the reasons for its occurrence. Two factors are identified. One is the conceptual confusion surrounding the meaning of the concept. This is accounted for b) the fact that accident proneness is defined by exclusion. The second factor is the repctitivc use of statistical techniques which have been shown to be equivocal. An alternatitc approach to individual differences in accident involvement is advocated. This approach cuts through the conceptual confusion and is less susceptible to the criticisms which have been levelled against the traditional statistical techniques.
PRONENESS:
AN
ANALYSIS
It
is generally estimated that about 90% of accidents can be attributed to human error. This human component in accident involvement has however been notoriously difficult to study. The concept of accident proneness while being in existence for over 60 years is still controversial. Why should this be so? Greenwood and Woods [I9191 were responsible for the early work which created the concept, which then grew in popularity through the twenties [Newbold, 19261 reaching its peak in the late thirties [Farmer and Chambers, 19391. Accident proneness was questioned in the fifties [Arbous and Kerrich, 19511 and rejected in the sixties [Haddon, Suchman and Klein, 19641. Since then it has made somewhat of a comeback [Shaw and Sichel, 1971; Rodstein, 1974; Milosevic and Vhcinc, 1975; Boyle, 19801. Needless to say these swings have been associated with argument, debate and plain confusion. No attempt will be made to review the data over which these controversies are based. This has been done elsewhere [Hakkinen. 1958; Cresswell and Froggatt, 1963; Shaw and Sichel, 19711. The data have not been controversial. Their interpretation has. Since the revival of accident proneness has not been associated with a reconceptualization of its nature the question occurs whether this is another part of the cycle which will be followed by critical comment and rejection. In order to determine this, an attempt will be made to review the concepts which have been associated with or taken to constitute the concept of accident proneness. The aim will be to understand why the controversy has arisen and whether the study of individual differences in accident liability is viable and necessarily dependent on the concept of accident proneness. THE ACCIDENT
DISTRIBUTION
The concept of accident proneness originated in the work of Greenwood and Woods [19191. Their approach was to examine and compare the distribution of accidents with several hypothetical distributions which were based on varying assumptions about the cause of accidents. They used an analogy which was then current in problems of applied mathematical probability. Suppose that a series of pigeon holes are bombarded with a number of balls. What is the likely distribution of balls in pigeon holes, that is, how many balls are likely to land in each pigeon hole? This will depend on the size of the pigeon holes. If it is assumed that the pigeon holes are of equal size (that every individual has an equal chance of having an accident) then they showed the resulting distribution to be Poisson. If on the other hand, the pigeon holes vary in size (there is an unequal initial liability to accidents) then a negative binomial distribution may be derived. Thus the obtained accident distribution was compared with two hypothetical distributions, one which assumed accidents were distributed by chance, the other assumed that there was an unequal initial liability to accident involvement. These were assessed by determining how well each fit the data. This approach has been used extensively since its introduction and is now one of the standard techniques for assessing individual differences in accident liability [Newbold, 1926;
F. P Iicl<~\\a
hh
Hakkinen. 1958: Cresswell and Froggatt, 1963; Milosesic and ‘I’ucinc. 1975: Boyle. 19801.Given that the negative binomial has provided a consistently better fit than the Poisson should the accident proneness proposition be accepted? Considering the controversial status of the hypothesis this has obviously not happened. Why not? The problem has been, and still is, that the interpretation of the negative binomial fit is not unequivocal. Several alternative explanations have been offered which do not include the assumption of unequal initial liabiiity. (t) Interpreting the negative binomial fit as evidence for accident proneness is dependent on the control of non personal factors such as exposure to risk and biases in accident reporting. Thus the same distribution could occur because some people are exposed to more risk. This means that the negative binomial fit may be explained as a failure to control exposure to risk [e.g. Cobb. 19391or to inadequate control where this control has been attempted. Even in studies where considerable efforts have been made to control exposure, for example Hakkinen I19581. the differential exposure hypothesis has been raised as an alternative explanation [Smeed, 19601.It seems that in practice this alternative explanation can always be raised. This may be the case in principle as well as practice. This argument would run as follows. Given that the chance distribution has been rejected then the resulting fit may be interpreted as due to an unknown personal factor or an unknown non personal factor. Thus even if it were possible to have perfect control over the known variables of exposure to risk etc. it could still be argued that an unknown non personal variable was producing the result. Whether this is more or less parsimonious than an unknown personal factor is a matter of debate. (2) A second reason for doubting the negative binomial fit as a test of the accident proneness concept is that several authors have pointed out that the negative binomial may be derived from assumptions which do_not involve differential initial liability to accident involvement [Arbous and Kerrich, 1951: Feller, 1966; Irwin, 1964; Kemp, 1973; M’Kendrick. 19261.It has been demonstrated that, with the assumption of equal initial liability, the negative binomial may be derived if the occurrence of an accident alters the probability of having subsequent accidents. Since even the originator of the negative binomial’ test has accepted this line of argument then this seriously weakens the power of the test [Greenwood, l950]. Another approach to the accident proneness concept using the accident distribution has been made by Cresswell and Froggatt[ 19631.They attempted to refute the concept by producing two models which did not assume differential initial liability. These models were developed with the view that people vary over time in their efficiency and are subject to “spells” where their performance is much poorer. Fundamental to their models is that people are more likely to incur an accident during a “spell”. There are perhaps two reasons why this approach has fared no better than the negative binomial. First, these models fit the data no better than the negative binomial and second, Irwin [1964] has pointed out that they can be reinterpreted as being consistent with accident proneness. In summary, then, it can be seen that despite the continuing popularity of appeals to the accident distribution these are inconclusive sources of evidence. Both the negative binomial and the models offered by Cresswell and Froggatt f19631 can be interpreted by a mode1 which either implicates accident proneness or by a model which does not imphcate accident proneness. Add to this the problem of control over non personai factors and it becomes clear that this approach is not decisive. THE
RELIABILITY
OF ACCIDENT
INVOLVE~~ENT
The other major approach to accident proneness also developed by Greenwood and Woods f19191 has been to examine the reliabiIity of accident involvement. If accident proneness is a viable concept, it is argued that those involved in accidents at one period of time should also be involved at a subsequent period of time [Newbold, 1926; Hakkinen, 1958; Milosevic and Vucinc, 1975; Boyle, 19801.Thus the correlation coefficient between the two periods has been used as a test of accident proneness. Those who doubt the accident proneness concept have pointed to the generally low correlation coefficients [Cresswell and Froggatt, 1963: Goldstein, 19611and those who accept the accident proneness concept point to the generally significant correlation coefficients [Johnson, 1946; Shaw and Sichel, 19711. Is the correlation coefficient a critical test of the accident proneness concept? While it has
;\ccident
proneness:
a conceptual
analysis
6’
been accepted by many it has not received universal acclaim. Arbous and Kerrich [ 1951] and Sichel [1971]. for example, point to the difficulty in interpreting a correlation coeficient from a bivariate negative binomial distribution. The same numerical correlation coming from different distributions may have a very different characteristics. For example, in dealing with a bivariate negative binomial distribution it would be common to have very few people with large numbers of accidents in both periods. iMost would have zero or very few accidents in both periods. This can result in a high correlation if these few extreme people are included and a virtually zero correlation if they are excluded. A more general problem has already been mentioned in the previous section. If. for example. people vary in their exposure to risk then this alone could produce a significant correlation. Those issues raised in relation to the control of non personal factors have the same force here and will not be reiterated. It seems therefore that the correlation coefficient is not decisive. Even if it is accepted that a significant correlation is not a sufficient condition for accident proneness many would regard it as a necessary condition. On this argument while a significant correlation would not provide unambiguous evidence for accident proneness a non significant correlation would provide unambiguous evidence against. Thus there are many both for and against the concept who argue that the correlation is necessary (even if it is not sufficient) for a study of accident proneness. One argument which has come from this line of thought may best be demonstrated by quoting McBride. Peck and Coppin [1965]: “Based on the estimated reliability ceiling (r = 0.29) for accidents over a three year interval, it is impossible that any predictive battery or model can ever account for more than nine percent (0.29)’ of the variability in accidents over a three year period”. In other words, the reliability sets the upper limit for correlations with any psychological test. This argument has come from many sources and is generally accepted in the literature [Arbous and Kerrich. 1951; Goldstein, 1961; Shaw and Sichel, 19711.I would like to argue that this argument is false, or more accurately it is not necessarily true. That is, I would like to argue that it is possible to have a psychological test which correlates higher with accidents than accidents correlate with themselves. Later I would like to give a concrete example where this could be true. THE CONCEPT
OF ACCIDENT
PRONENESS
It
is out of the work on accident distributions and the reliability of accident involvement that the concept of accident proneness has emerged. Here an attempt will be made to examine some of the concepts which have been associated with, or taken to constitute, accident proneness. Most accidents are caused by a few people
MacIver]l961], for example, states that “accident proneness carries the implication that many accidents occur because of a particular kind of mental abnormality, and that many accidents are concentrated in a minority of the population with this abnormality”. This type of view may have developed from Cobb [1939] who pointed out that 4% of his sample were responsible for 36% of the accidents. He does refer to an accident prone group as “small in number but mighty in deed”. It is not clear to what extent this view has been seriously put forward, though it has been seriously criticised both by those who favour accident proneness [Shaw and Sichel, 19711 and those who oppose it [Forbes, 19391. Mintz and Blum [1949] went to some lengths to point out that this argument is fallacious. Even in distributions based on chance it is possible to find that a few people are responsible for many accidents. This is so because, it is expected by chance that a few people will have several accidents. In addition many people will have no accidents or few accidents. Put together this can easily lead to a situation where few people are responsible for many accidents. This situation provides no evidence for any form of accident proneness. Accident proneness as a unitary trait
This type of view has been particularly prevalent among those who are critical of the concept. Suchman[l960] in rejecting the concept states that “we do not believe that the complex behavioural phenomenon of accidents can be adequately explained in terms of a single
hR
F. P. !.fcK~zu\
personality type .“. Interestingly, there are those [e.g. Hakkinen. 1918, p. 211 who retain a belief in accident proneness while rejecting the unitary trait theory. The conceptual confusion surrounding the term accident proneness can be demonstrated by considering the following quotations. Haddon. Suchman and Klein [1964, p. 4441 state: “In fact. rejecting the concept of accident proneness, with its implication of a global personality trait, forces one to search for many different psychological factors and their significance in given environmental circumstances”. It is clear that the above authors consider accident proneness as a single trait. They also consider accident proneness and “different psychological factors” as mutually exclusive and reject the former while retaining the latter. This distinction between a single trait and multiple psychological factors should be borne in mind when considering a dispute between Shaw [1971] and McFarland [ 19621. Shaw quotes McFarland who after doubting the usefulness of the term accident proneness adds “It would be more profitable in accident research to concentrate on the specific causes of repeated accidents and to try to identify those specific personality characteristics that are associated with repeated accidents for which the individual is primarily responsible”. Shaw [1971, p. 1881 regards this as self-contradictory and, indeed is correct, if it is assumed that any person centred association with accidents is equivalent to accident proneness. McFarland [19621, however, does not use the term in this way. The dispute arises because of a conceptual confusion over the term accident proneness where some authors consider the term to denote a single trait while others will include in the definition multiple psychological factors. Accident proneness as a general characteristic Here the proposition under question is whether accident involvement generalizes across different environments. Newbold [1926]. for example, suggested that accident proneness may well be a general characteristic because she found that accidents in a factory correlated with accidents at home. Similarly, Guilford [1973] found a significant correlation between accidents in a simulated kitchen and road accidents and likewise suggested that accident proneness may be a general phenomenon. The most extreme statement on this issue has been made by Wong and Hobbs [ 19491 who concluded that “accident tendency was a lifelong characteristic and that it appears to invade all aspects of life”. This view is at the core of Tillman and Hobbs [1949] oft-quoted line “a man drives as he lives”. Given the paucity of data on this issue it is perhaps not too surprising that it has been controversial with many critics [Adelstein, 1952; Arbous and Kerrich, 1951; Thorndike, 19511. There have been those who while rejecting the generality notion have retained the concept of accident proneness [Hakkinen, 1958; Shaw and Sichel, 19711. Accident proneness as an innate and unmodijiable characteristic Several authors have proposed that accident proneness refers to an innate characteristic. Hale and Hale [1972] consider accident proneness to mean “that some people are more liable to accidents than others due to innate personal characteristics”. Irwin [1964] states that “it would be most surprising if individuals did not vary innately in their tendency to accident when exposed to the same risk”. And Shaw [1971, p. 901 refers to accident proneness as “innate differences between people’s propensity for accidents. . .“. Given that there is literally no evidence on this issue it would indeed be most surprising if this were not controversial. A related but conceptually distinct issue concerns whether accident proneness refers to a modifiable characteristic or not. Adelstein [I9521 has objected to the concept because it “has resulted in a tendency to neglect the factors underlying accidents, factors which are not fixed as accident proneness is assumed to be, and are amenable to improvement”. Cresswell and Froggatt [1963] wax lyrical on this issue: “few could cavil with the widespread acceptance of accident proneness as an immutable load to which, the unfortunate possessor is chained as inexorably as Ixion to his wheel. . .“. These same authors also suggest that accident proneness is “hung like the albatross around each person’s neck”. It seems inappropriate to consider Zeus’ condemnation or the Ancient Mariner’s problems but once again the conceptual confusion among different authors over the meaning of accident proneness is strikingly clear.
Accident proneness:
a conceptual
analysis
69
Accident proneness as an explanatory concept Accident proneness is used to describe the pattern of accident involvement and then used as a causal explanation of the same pattern it describes. Several authors have criticised this view because they note the circularity in its use [Cameron, 1975; Cresswell and Froggatt, 1963; Peck and Coppin. 19711. GENERAL
COMMENTS
By now it should be clear that one of the major reasons
for the controversial status of accident proneness is the conceptual confusion surrounding the concept. Authors have varied in both their implicit and explicit definitions. The statements reviewed here concerning accident proneness are largely independent of each other. That is, the validity of each can be assessed independently of the others. Different authors under the guise of the term accident proneness have been accepting and rejecting different concepts. Thus one of the reasons for the failure of accident proneness has been the lack of unanimity over its meaning. Another is due to the repetitive use of statistical techniques which are known to be equivocal. To this day accident proneness is still tackled using the same techniques that Greenwood and Woods [1919] devised, the same interpretations offered, the same alternatives possible, the same arguments result. Is a study of individual differences in accident liability
viable? The first move should be to discard the term accident proneness since it has been shown to have no consistent meaning. A new term such as “differential accident involvement” should be used. Is this a trivial semantic modification? It appears not. The advantage of such a term is that it denotes the study of individual differences without the historical confusions. It has the added advantage that it does not prejudge the issue in the way that accident proneness does. It is an area of study not a set theory. The central issue from this approach is to consider whether it is possible to predict or distinguish on the basis of psychological tests those who are involved in accidents from those who are not. There is a historical precedent for this approach which is almost as old as the concept of accident proneness itself. Many studies have been done on factors such as reaction time, visual acuity etc. Unfortunately this approach has always been overshadowed by the statistical approach perhaps because no outstanding results were reported. When more complex tasks have been used more encouraging results have been reported. For example, Goodenough [1976] reviewed several studies which showed that field dependent people were more involved in accidents. Kahneman, Ben-Ishai and Lotan [1973] have found significant results with an attention switching task and several studies have reported that those going through more life events are more involved in accidents [Selzer and Vinokur, 1974; Alkov and Borowsky,. 19801. This latter finding is important because it is possible that here is a concrete example of what was referred to earlier where a psychological test could correlate higher with accidents than accidents correlate with themselves. The importance of this finding is that it would question the long and generally held belief that it is impossible for a psychological test to correlate higher with accidents than accidents correlate with themselves. It has been assumed that if accident involvement is not a stable phenomenon then it cannot be studied. This is not necessarily true. In other words it would still be possible to study differential accident involvement even if those who were involved in accidents at one point in time were not involved at another. This could be done and in the case of life events has been done by designing tests which measure the temporary states of the individual. The important point to note is the traditional assumption that accident involvement is necessarily a stable phenomenon. The approach advocated here makes no such assumption. This is a factor to be tested not assumed. Likewise, no assumptions about the shape of the distribution need be made. Factors such as whether the hypothesized differences are due to innate or learned factors, whether accident involvement is general or specific are factors to be investigated not assumed. In general the study of differential accident involvement has the advantage that it makes fewer assumptions and is less open to the criticisms which have plagued the concept of accident proneness. A theoretical understanding of differential accident involvement would lead to a knowledge of the psychological processes underlying human error. This would encourage training where appropriate,
selection
when necessary
and redesign if possible. This latter point
‘0
F. P. .LICKENVA
is included because an understanding of the perceptual, attentional and performance limitations of man may point to sources in the environment, rather than in man, which could be changed. Q%ereas the study of accident proneness focussed only on the problem of selection. a study of differential accident involvement would not. To understand this it is necessary to compare the information to be gained by a study of accident proneness which is a concept based on statistical modelling, and differential accident involvement which is a concept based on psychological testing. Consider the logic of the statistical approach. The concept of accident proneness is arrived at through a process of exclusion. An attempt is made to control a!! factors relating to risk exposure, accident reporting etc. If a result then occurs it is attributed to something else-this something else is called accident proneness. Accident proneness is thus defined not by what it is, but what it is not. This has resulted in different authors, often it would seem unknowingly, bringing their own individual implicit and explicit definitions. It is now clear how the conceptual confusion can so easily arise. Other problems have already been dealt with: alternative explanations have been offered, the practical and theoretical problems over control of these non persona! factors have been discussed. Even if a!! these factors were ignored and the statistical approach were completely successful then the result would be that we would still know literally nothing about the psychological antecedents of accident involvement. The alternative approach being advocated here, if successful, both demonstrates differential liability and provides some information on the antecedents of this differential liability. REFERENCES Adelstein A. M., Accident proneness: a criticism of the concept based upon an analysis of shunters’ accidents. 1. Roy. Statist. Sot. 115. 354-410. 1952. Alkov R. A. and Borowsky M. S., A questionnaire study of psychological background factors in U.S. Navy aircraft accidents. Aria?. Space & Enriron. Med. 51. 860-863. 1980. Arbous A. G. and Kerrich J. E., Accident statistics and the concept of accident proneness. Biometrics 7, 340-432, 1951. Boyle A. J., ‘Found experiments’ in accident research: Report of a study of accident rates and implications for future research. 1. Occup. Psychol. 53, 53-64, 1980. Cameron C.. Accident proneness. Accid. Anal. & Preu. 7.49-53. 1975. Cobb P. W., Automobile driver tests administered to 3663 persons in Connecticut, 1936-1937 and the relation of the test scores to accidents sustained, Report to the Highway Research Board, Washington, D.C.. unpublished, 1939. Cresswell W. L. and Froggatt P., The Causation of Bus Driver Accidents: An Epidemiologicaf Study. O.xford University Press, London, 1963. Farmer E. and Chambers E. G., A study of accident proneness amongst motor drivers. Industrial Health Research Board, London, Rep. No. 84, 1939. Feller W., An Introduction lo Probability Theory and its AppIicafions, Vol. II. Wiley, New York, 1966. Forbes T. W.. The normal automobile driver as a traffic problem. J. Gen. Psycho/. 20, 471-474, 1939. Goldstein L. C., Research on human variables in safe motor vehicle operation: A correlation summary of predictor variables and criterion measures, the Driver Behaviour Research Project, George Washington University. 1961. Goodenough D. R.. A review of individual differences in field dependence as a factor in auto safety. Hum. Factors 18. 53-62, 1976. Greenwood M., Accident proneness. Biometrika 37, 24-29, 1950. Greenwood M. and Woods H. M., A report on the incidence of industrial accidents upon individuals with special reference to multiple accidents, 1919. Reproduced in W. Haddon, E. A. Suchman and D. Klein (Eds.), Accident Research. Harper & Row, New York, 1964. Guilford J. S.. Prediction of accidents in a standardized home environment. J. Appl. Psychol. 57. 36313. 1973. Haddon W., Suchman E. A. and Klein D. (Eds.). Accident Research. Harper & Row, New York, 1964. Hakkinen, S. Traffic Accidents and Driver Characteristics: A Statistical and Psychological Study. Finland’s Institute of Technology, Scientific Researches, No. 13, Helsinki, 1958. Hale A. R. and Hale M., A Review of the Industrial Accidenf Literature. Her Majesty’s Stationary Office. London, 1972. Irwin J. 0.. The personal factor in accidents-a review article. 1. Roy. Statist. Sot. 127, 438-451, 1964. Johnson H. M., The detection and treatment of accident-prone drivers. Psycho/. Bull. 43,489-532, 1946. Kahneman D., Ben-Ishai R. and Lotan M., Relation of a test of attention to road accidents. 1. Appl. Psycho/. 58, 113-l IS, 1973. Kemp C. D., An elementary ambiguity in accident theory. Accid. Anal. & Prec. 5, 371-373, 1973. MacIver J.. Safety and human behaviour. In Behavioural Approaches to Accident Research. Association for the Aid of Crippled Children. New York, 1961. IMcBride R. S., Peck R. C. and Coppin R. S., 1965, cited by Shaw, L. & Sichel, H. S. Accident Research. International Series of Monographs in Experimental Psychology, Vol. I I, Pergamon Press, Oxford, 1971. McFarland R. A., The epidemiology of motor vehicle accidents. J. Am. Med. Ass. 180, 289-300, l%2. Milosevic S. and Vucinc S., Statistical study of tram drivers’ accidents. Accid. Anal. & Prer. 7. l-7, IY75. rMintz A. and Blum M. L., A re-examination of the accident-proneness concept. 1. Appl. Psychol. 73, 195-21 I, 1949. M’Kendrick A. G., Applications of mathematics to medical problems. Proc. Edin. Math. Sot. 4.4. 98-130, 1926. Newbold E. M., A contribution to the study of the human factor in the causation of accidents, 1926. Reproduced in W. Haddon. E. A. Suchman d D. Klein, (Eds.). Accident Research. Harper & Row, New York. 1964.
.-\ccident proneness:
a conceptual
analysis
71
Peck R. C. and Coppin R. S.. A position paper on accident proneness and driver-oriented safety models. In L. Shaw & H. S. Sichel. Accidmr Proneness. International Series of Monographs in Experimental Psychology. Vol. II, Pergamon Press. Oxford. 1971. Rodstein \I.. Accident proneness. J. ;\m. Med. .I\ss. 229. 1194. 1974. Seizer XI. L. and Vinokur A.. Life events, subjective stress and traffic accidents. r\m. I. Psychiut. 13. 903-906. 1971. Shaw L.. In L. Shaw & H. S. Sichel, .4ccident Proneness. International Series of Monographs in Experimental Psychology. Vol. II. Pergamon Press. Oxford. 1971. Shaw L. and Sichel H. S.. Accident Proneness. International Series of Monographs in Experimental Psychology. Vol. I I, Pergamon Press, Oxford. 1971. Sichel H. S.. New statistical techniques for the evaluation of the concept of accident proneness. In L. Shaw L H. S. Sichel, .Accidmr Proneness. International Series of Monographs in Experimental Psychology, Vol. Ii. Pergamon Press, Oxford, 1971 ._. .
Smeed R. 1.. Proneness of drivers to road accidents. Nnfure. London 186. 273-275. 1960. Suchman E. A.. A conceptual analysis of the accident phenomenon. Social Problems 8. 11[-2.(J, 1960. Thorndike R. L.. The Human Factors in Accidents with Special Reference to Aircraft Accidents, Project 11-30-001. Rep. I, U.S. Air Force. School of Aviation Medicine. Randolph Field, Texas, 1951. Tillman K’. A. and Hobbs G. E.. The accident-prone automobile driver. Am. 1. Psychiat. 106. 331-333. 1949, Wong u’. A. and Hobbs G. E.. Personal factors in industrial accidents: A study of accident proneness in an industrial group. Indust. Med. Surg. 18. 291-291. 1949.
ANALYSIS
FR,G~; P. MCKENN;\ .LfRC Applied
Psychology
Unit.
Ii Chaucer
(Recricrd
Road, Cambridge
3 Murch
CB1 2EF.
England
1981)
Abstract-The concept of accident proncnsss has had a long and controversial history. An attempt is made both to demonstrate the nature of this controversy and to investigate the reasons for its occurrence. Two factors are identified. One is the conceptual confusion surrounding the meaning of the concept. This is accounted for b) the fact that accident proneness is defined by exclusion. The second factor is the repctitivc use of statistical techniques which have been shown to be equivocal. An alternatitc approach to individual differences in accident involvement is advocated. This approach cuts through the conceptual confusion and is less susceptible to the criticisms which have been levelled against the traditional statistical techniques.
PRONENESS:
AN
ANALYSIS
It
is generally estimated that about 90% of accidents can be attributed to human error. This human component in accident involvement has however been notoriously difficult to study. The concept of accident proneness while being in existence for over 60 years is still controversial. Why should this be so? Greenwood and Woods [I9191 were responsible for the early work which created the concept, which then grew in popularity through the twenties [Newbold, 19261 reaching its peak in the late thirties [Farmer and Chambers, 19391. Accident proneness was questioned in the fifties [Arbous and Kerrich, 19511 and rejected in the sixties [Haddon, Suchman and Klein, 19641. Since then it has made somewhat of a comeback [Shaw and Sichel, 1971; Rodstein, 1974; Milosevic and Vhcinc, 1975; Boyle, 19801. Needless to say these swings have been associated with argument, debate and plain confusion. No attempt will be made to review the data over which these controversies are based. This has been done elsewhere [Hakkinen. 1958; Cresswell and Froggatt, 1963; Shaw and Sichel, 19711. The data have not been controversial. Their interpretation has. Since the revival of accident proneness has not been associated with a reconceptualization of its nature the question occurs whether this is another part of the cycle which will be followed by critical comment and rejection. In order to determine this, an attempt will be made to review the concepts which have been associated with or taken to constitute the concept of accident proneness. The aim will be to understand why the controversy has arisen and whether the study of individual differences in accident liability is viable and necessarily dependent on the concept of accident proneness. THE ACCIDENT
DISTRIBUTION
The concept of accident proneness originated in the work of Greenwood and Woods [19191. Their approach was to examine and compare the distribution of accidents with several hypothetical distributions which were based on varying assumptions about the cause of accidents. They used an analogy which was then current in problems of applied mathematical probability. Suppose that a series of pigeon holes are bombarded with a number of balls. What is the likely distribution of balls in pigeon holes, that is, how many balls are likely to land in each pigeon hole? This will depend on the size of the pigeon holes. If it is assumed that the pigeon holes are of equal size (that every individual has an equal chance of having an accident) then they showed the resulting distribution to be Poisson. If on the other hand, the pigeon holes vary in size (there is an unequal initial liability to accidents) then a negative binomial distribution may be derived. Thus the obtained accident distribution was compared with two hypothetical distributions, one which assumed accidents were distributed by chance, the other assumed that there was an unequal initial liability to accident involvement. These were assessed by determining how well each fit the data. This approach has been used extensively since its introduction and is now one of the standard techniques for assessing individual differences in accident liability [Newbold, 1926;
F. P Iicl<~\\a
hh
Hakkinen. 1958: Cresswell and Froggatt, 1963; Milosesic and ‘I’ucinc. 1975: Boyle. 19801.Given that the negative binomial has provided a consistently better fit than the Poisson should the accident proneness proposition be accepted? Considering the controversial status of the hypothesis this has obviously not happened. Why not? The problem has been, and still is, that the interpretation of the negative binomial fit is not unequivocal. Several alternative explanations have been offered which do not include the assumption of unequal initial liabiiity. (t) Interpreting the negative binomial fit as evidence for accident proneness is dependent on the control of non personal factors such as exposure to risk and biases in accident reporting. Thus the same distribution could occur because some people are exposed to more risk. This means that the negative binomial fit may be explained as a failure to control exposure to risk [e.g. Cobb. 19391or to inadequate control where this control has been attempted. Even in studies where considerable efforts have been made to control exposure, for example Hakkinen I19581. the differential exposure hypothesis has been raised as an alternative explanation [Smeed, 19601.It seems that in practice this alternative explanation can always be raised. This may be the case in principle as well as practice. This argument would run as follows. Given that the chance distribution has been rejected then the resulting fit may be interpreted as due to an unknown personal factor or an unknown non personal factor. Thus even if it were possible to have perfect control over the known variables of exposure to risk etc. it could still be argued that an unknown non personal variable was producing the result. Whether this is more or less parsimonious than an unknown personal factor is a matter of debate. (2) A second reason for doubting the negative binomial fit as a test of the accident proneness concept is that several authors have pointed out that the negative binomial may be derived from assumptions which do_not involve differential initial liability to accident involvement [Arbous and Kerrich, 1951: Feller, 1966; Irwin, 1964; Kemp, 1973; M’Kendrick. 19261.It has been demonstrated that, with the assumption of equal initial liability, the negative binomial may be derived if the occurrence of an accident alters the probability of having subsequent accidents. Since even the originator of the negative binomial’ test has accepted this line of argument then this seriously weakens the power of the test [Greenwood, l950]. Another approach to the accident proneness concept using the accident distribution has been made by Cresswell and Froggatt[ 19631.They attempted to refute the concept by producing two models which did not assume differential initial liability. These models were developed with the view that people vary over time in their efficiency and are subject to “spells” where their performance is much poorer. Fundamental to their models is that people are more likely to incur an accident during a “spell”. There are perhaps two reasons why this approach has fared no better than the negative binomial. First, these models fit the data no better than the negative binomial and second, Irwin [1964] has pointed out that they can be reinterpreted as being consistent with accident proneness. In summary, then, it can be seen that despite the continuing popularity of appeals to the accident distribution these are inconclusive sources of evidence. Both the negative binomial and the models offered by Cresswell and Froggatt f19631 can be interpreted by a mode1 which either implicates accident proneness or by a model which does not imphcate accident proneness. Add to this the problem of control over non personai factors and it becomes clear that this approach is not decisive. THE
RELIABILITY
OF ACCIDENT
INVOLVE~~ENT
The other major approach to accident proneness also developed by Greenwood and Woods f19191 has been to examine the reliabiIity of accident involvement. If accident proneness is a viable concept, it is argued that those involved in accidents at one period of time should also be involved at a subsequent period of time [Newbold, 1926; Hakkinen, 1958; Milosevic and Vucinc, 1975; Boyle, 19801.Thus the correlation coefficient between the two periods has been used as a test of accident proneness. Those who doubt the accident proneness concept have pointed to the generally low correlation coefficients [Cresswell and Froggatt, 1963: Goldstein, 19611and those who accept the accident proneness concept point to the generally significant correlation coefficients [Johnson, 1946; Shaw and Sichel, 19711. Is the correlation coefficient a critical test of the accident proneness concept? While it has
;\ccident
proneness:
a conceptual
analysis
6’
been accepted by many it has not received universal acclaim. Arbous and Kerrich [ 1951] and Sichel [1971]. for example, point to the difficulty in interpreting a correlation coeficient from a bivariate negative binomial distribution. The same numerical correlation coming from different distributions may have a very different characteristics. For example, in dealing with a bivariate negative binomial distribution it would be common to have very few people with large numbers of accidents in both periods. iMost would have zero or very few accidents in both periods. This can result in a high correlation if these few extreme people are included and a virtually zero correlation if they are excluded. A more general problem has already been mentioned in the previous section. If. for example. people vary in their exposure to risk then this alone could produce a significant correlation. Those issues raised in relation to the control of non personal factors have the same force here and will not be reiterated. It seems therefore that the correlation coefficient is not decisive. Even if it is accepted that a significant correlation is not a sufficient condition for accident proneness many would regard it as a necessary condition. On this argument while a significant correlation would not provide unambiguous evidence for accident proneness a non significant correlation would provide unambiguous evidence against. Thus there are many both for and against the concept who argue that the correlation is necessary (even if it is not sufficient) for a study of accident proneness. One argument which has come from this line of thought may best be demonstrated by quoting McBride. Peck and Coppin [1965]: “Based on the estimated reliability ceiling (r = 0.29) for accidents over a three year interval, it is impossible that any predictive battery or model can ever account for more than nine percent (0.29)’ of the variability in accidents over a three year period”. In other words, the reliability sets the upper limit for correlations with any psychological test. This argument has come from many sources and is generally accepted in the literature [Arbous and Kerrich. 1951; Goldstein, 1961; Shaw and Sichel, 19711.I would like to argue that this argument is false, or more accurately it is not necessarily true. That is, I would like to argue that it is possible to have a psychological test which correlates higher with accidents than accidents correlate with themselves. Later I would like to give a concrete example where this could be true. THE CONCEPT
OF ACCIDENT
PRONENESS
It
is out of the work on accident distributions and the reliability of accident involvement that the concept of accident proneness has emerged. Here an attempt will be made to examine some of the concepts which have been associated with, or taken to constitute, accident proneness. Most accidents are caused by a few people
MacIver]l961], for example, states that “accident proneness carries the implication that many accidents occur because of a particular kind of mental abnormality, and that many accidents are concentrated in a minority of the population with this abnormality”. This type of view may have developed from Cobb [1939] who pointed out that 4% of his sample were responsible for 36% of the accidents. He does refer to an accident prone group as “small in number but mighty in deed”. It is not clear to what extent this view has been seriously put forward, though it has been seriously criticised both by those who favour accident proneness [Shaw and Sichel, 19711 and those who oppose it [Forbes, 19391. Mintz and Blum [1949] went to some lengths to point out that this argument is fallacious. Even in distributions based on chance it is possible to find that a few people are responsible for many accidents. This is so because, it is expected by chance that a few people will have several accidents. In addition many people will have no accidents or few accidents. Put together this can easily lead to a situation where few people are responsible for many accidents. This situation provides no evidence for any form of accident proneness. Accident proneness as a unitary trait
This type of view has been particularly prevalent among those who are critical of the concept. Suchman[l960] in rejecting the concept states that “we do not believe that the complex behavioural phenomenon of accidents can be adequately explained in terms of a single
hR
F. P. !.fcK~zu\
personality type .“. Interestingly, there are those [e.g. Hakkinen. 1918, p. 211 who retain a belief in accident proneness while rejecting the unitary trait theory. The conceptual confusion surrounding the term accident proneness can be demonstrated by considering the following quotations. Haddon. Suchman and Klein [1964, p. 4441 state: “In fact. rejecting the concept of accident proneness, with its implication of a global personality trait, forces one to search for many different psychological factors and their significance in given environmental circumstances”. It is clear that the above authors consider accident proneness as a single trait. They also consider accident proneness and “different psychological factors” as mutually exclusive and reject the former while retaining the latter. This distinction between a single trait and multiple psychological factors should be borne in mind when considering a dispute between Shaw [1971] and McFarland [ 19621. Shaw quotes McFarland who after doubting the usefulness of the term accident proneness adds “It would be more profitable in accident research to concentrate on the specific causes of repeated accidents and to try to identify those specific personality characteristics that are associated with repeated accidents for which the individual is primarily responsible”. Shaw [1971, p. 1881 regards this as self-contradictory and, indeed is correct, if it is assumed that any person centred association with accidents is equivalent to accident proneness. McFarland [19621, however, does not use the term in this way. The dispute arises because of a conceptual confusion over the term accident proneness where some authors consider the term to denote a single trait while others will include in the definition multiple psychological factors. Accident proneness as a general characteristic Here the proposition under question is whether accident involvement generalizes across different environments. Newbold [1926]. for example, suggested that accident proneness may well be a general characteristic because she found that accidents in a factory correlated with accidents at home. Similarly, Guilford [1973] found a significant correlation between accidents in a simulated kitchen and road accidents and likewise suggested that accident proneness may be a general phenomenon. The most extreme statement on this issue has been made by Wong and Hobbs [ 19491 who concluded that “accident tendency was a lifelong characteristic and that it appears to invade all aspects of life”. This view is at the core of Tillman and Hobbs [1949] oft-quoted line “a man drives as he lives”. Given the paucity of data on this issue it is perhaps not too surprising that it has been controversial with many critics [Adelstein, 1952; Arbous and Kerrich, 1951; Thorndike, 19511. There have been those who while rejecting the generality notion have retained the concept of accident proneness [Hakkinen, 1958; Shaw and Sichel, 19711. Accident proneness as an innate and unmodijiable characteristic Several authors have proposed that accident proneness refers to an innate characteristic. Hale and Hale [1972] consider accident proneness to mean “that some people are more liable to accidents than others due to innate personal characteristics”. Irwin [1964] states that “it would be most surprising if individuals did not vary innately in their tendency to accident when exposed to the same risk”. And Shaw [1971, p. 901 refers to accident proneness as “innate differences between people’s propensity for accidents. . .“. Given that there is literally no evidence on this issue it would indeed be most surprising if this were not controversial. A related but conceptually distinct issue concerns whether accident proneness refers to a modifiable characteristic or not. Adelstein [I9521 has objected to the concept because it “has resulted in a tendency to neglect the factors underlying accidents, factors which are not fixed as accident proneness is assumed to be, and are amenable to improvement”. Cresswell and Froggatt [1963] wax lyrical on this issue: “few could cavil with the widespread acceptance of accident proneness as an immutable load to which, the unfortunate possessor is chained as inexorably as Ixion to his wheel. . .“. These same authors also suggest that accident proneness is “hung like the albatross around each person’s neck”. It seems inappropriate to consider Zeus’ condemnation or the Ancient Mariner’s problems but once again the conceptual confusion among different authors over the meaning of accident proneness is strikingly clear.
Accident proneness:
a conceptual
analysis
69
Accident proneness as an explanatory concept Accident proneness is used to describe the pattern of accident involvement and then used as a causal explanation of the same pattern it describes. Several authors have criticised this view because they note the circularity in its use [Cameron, 1975; Cresswell and Froggatt, 1963; Peck and Coppin. 19711. GENERAL
COMMENTS
By now it should be clear that one of the major reasons
for the controversial status of accident proneness is the conceptual confusion surrounding the concept. Authors have varied in both their implicit and explicit definitions. The statements reviewed here concerning accident proneness are largely independent of each other. That is, the validity of each can be assessed independently of the others. Different authors under the guise of the term accident proneness have been accepting and rejecting different concepts. Thus one of the reasons for the failure of accident proneness has been the lack of unanimity over its meaning. Another is due to the repetitive use of statistical techniques which are known to be equivocal. To this day accident proneness is still tackled using the same techniques that Greenwood and Woods [1919] devised, the same interpretations offered, the same alternatives possible, the same arguments result. Is a study of individual differences in accident liability
viable? The first move should be to discard the term accident proneness since it has been shown to have no consistent meaning. A new term such as “differential accident involvement” should be used. Is this a trivial semantic modification? It appears not. The advantage of such a term is that it denotes the study of individual differences without the historical confusions. It has the added advantage that it does not prejudge the issue in the way that accident proneness does. It is an area of study not a set theory. The central issue from this approach is to consider whether it is possible to predict or distinguish on the basis of psychological tests those who are involved in accidents from those who are not. There is a historical precedent for this approach which is almost as old as the concept of accident proneness itself. Many studies have been done on factors such as reaction time, visual acuity etc. Unfortunately this approach has always been overshadowed by the statistical approach perhaps because no outstanding results were reported. When more complex tasks have been used more encouraging results have been reported. For example, Goodenough [1976] reviewed several studies which showed that field dependent people were more involved in accidents. Kahneman, Ben-Ishai and Lotan [1973] have found significant results with an attention switching task and several studies have reported that those going through more life events are more involved in accidents [Selzer and Vinokur, 1974; Alkov and Borowsky,. 19801. This latter finding is important because it is possible that here is a concrete example of what was referred to earlier where a psychological test could correlate higher with accidents than accidents correlate with themselves. The importance of this finding is that it would question the long and generally held belief that it is impossible for a psychological test to correlate higher with accidents than accidents correlate with themselves. It has been assumed that if accident involvement is not a stable phenomenon then it cannot be studied. This is not necessarily true. In other words it would still be possible to study differential accident involvement even if those who were involved in accidents at one point in time were not involved at another. This could be done and in the case of life events has been done by designing tests which measure the temporary states of the individual. The important point to note is the traditional assumption that accident involvement is necessarily a stable phenomenon. The approach advocated here makes no such assumption. This is a factor to be tested not assumed. Likewise, no assumptions about the shape of the distribution need be made. Factors such as whether the hypothesized differences are due to innate or learned factors, whether accident involvement is general or specific are factors to be investigated not assumed. In general the study of differential accident involvement has the advantage that it makes fewer assumptions and is less open to the criticisms which have plagued the concept of accident proneness. A theoretical understanding of differential accident involvement would lead to a knowledge of the psychological processes underlying human error. This would encourage training where appropriate,
selection
when necessary
and redesign if possible. This latter point
‘0
F. P. .LICKENVA
is included because an understanding of the perceptual, attentional and performance limitations of man may point to sources in the environment, rather than in man, which could be changed. Q%ereas the study of accident proneness focussed only on the problem of selection. a study of differential accident involvement would not. To understand this it is necessary to compare the information to be gained by a study of accident proneness which is a concept based on statistical modelling, and differential accident involvement which is a concept based on psychological testing. Consider the logic of the statistical approach. The concept of accident proneness is arrived at through a process of exclusion. An attempt is made to control a!! factors relating to risk exposure, accident reporting etc. If a result then occurs it is attributed to something else-this something else is called accident proneness. Accident proneness is thus defined not by what it is, but what it is not. This has resulted in different authors, often it would seem unknowingly, bringing their own individual implicit and explicit definitions. It is now clear how the conceptual confusion can so easily arise. Other problems have already been dealt with: alternative explanations have been offered, the practical and theoretical problems over control of these non persona! factors have been discussed. Even if a!! these factors were ignored and the statistical approach were completely successful then the result would be that we would still know literally nothing about the psychological antecedents of accident involvement. The alternative approach being advocated here, if successful, both demonstrates differential liability and provides some information on the antecedents of this differential liability. REFERENCES Adelstein A. M., Accident proneness: a criticism of the concept based upon an analysis of shunters’ accidents. 1. Roy. Statist. Sot. 115. 354-410. 1952. Alkov R. A. and Borowsky M. S., A questionnaire study of psychological background factors in U.S. Navy aircraft accidents. Aria?. Space & Enriron. Med. 51. 860-863. 1980. Arbous A. G. and Kerrich J. E., Accident statistics and the concept of accident proneness. Biometrics 7, 340-432, 1951. Boyle A. J., ‘Found experiments’ in accident research: Report of a study of accident rates and implications for future research. 1. Occup. Psychol. 53, 53-64, 1980. Cameron C.. Accident proneness. Accid. Anal. & Preu. 7.49-53. 1975. Cobb P. W., Automobile driver tests administered to 3663 persons in Connecticut, 1936-1937 and the relation of the test scores to accidents sustained, Report to the Highway Research Board, Washington, D.C.. unpublished, 1939. Cresswell W. L. and Froggatt P., The Causation of Bus Driver Accidents: An Epidemiologicaf Study. O.xford University Press, London, 1963. Farmer E. and Chambers E. G., A study of accident proneness amongst motor drivers. Industrial Health Research Board, London, Rep. No. 84, 1939. Feller W., An Introduction lo Probability Theory and its AppIicafions, Vol. II. Wiley, New York, 1966. Forbes T. W.. The normal automobile driver as a traffic problem. J. Gen. Psycho/. 20, 471-474, 1939. Goldstein L. C., Research on human variables in safe motor vehicle operation: A correlation summary of predictor variables and criterion measures, the Driver Behaviour Research Project, George Washington University. 1961. Goodenough D. R.. A review of individual differences in field dependence as a factor in auto safety. Hum. Factors 18. 53-62, 1976. Greenwood M., Accident proneness. Biometrika 37, 24-29, 1950. Greenwood M. and Woods H. M., A report on the incidence of industrial accidents upon individuals with special reference to multiple accidents, 1919. Reproduced in W. Haddon, E. A. Suchman and D. Klein (Eds.), Accident Research. Harper & Row, New York, 1964. Guilford J. S.. Prediction of accidents in a standardized home environment. J. Appl. Psychol. 57. 36313. 1973. Haddon W., Suchman E. A. and Klein D. (Eds.). Accident Research. Harper & Row, New York, 1964. Hakkinen, S. Traffic Accidents and Driver Characteristics: A Statistical and Psychological Study. Finland’s Institute of Technology, Scientific Researches, No. 13, Helsinki, 1958. Hale A. R. and Hale M., A Review of the Industrial Accidenf Literature. Her Majesty’s Stationary Office. London, 1972. Irwin J. 0.. The personal factor in accidents-a review article. 1. Roy. Statist. Sot. 127, 438-451, 1964. Johnson H. M., The detection and treatment of accident-prone drivers. Psycho/. Bull. 43,489-532, 1946. Kahneman D., Ben-Ishai R. and Lotan M., Relation of a test of attention to road accidents. 1. Appl. Psycho/. 58, 113-l IS, 1973. Kemp C. D., An elementary ambiguity in accident theory. Accid. Anal. & Prec. 5, 371-373, 1973. MacIver J.. Safety and human behaviour. In Behavioural Approaches to Accident Research. Association for the Aid of Crippled Children. New York, 1961. IMcBride R. S., Peck R. C. and Coppin R. S., 1965, cited by Shaw, L. & Sichel, H. S. Accident Research. International Series of Monographs in Experimental Psychology, Vol. I I, Pergamon Press, Oxford, 1971. McFarland R. A., The epidemiology of motor vehicle accidents. J. Am. Med. Ass. 180, 289-300, l%2. Milosevic S. and Vucinc S., Statistical study of tram drivers’ accidents. Accid. Anal. & Prer. 7. l-7, IY75. rMintz A. and Blum M. L., A re-examination of the accident-proneness concept. 1. Appl. Psychol. 73, 195-21 I, 1949. M’Kendrick A. G., Applications of mathematics to medical problems. Proc. Edin. Math. Sot. 4.4. 98-130, 1926. Newbold E. M., A contribution to the study of the human factor in the causation of accidents, 1926. Reproduced in W. Haddon. E. A. Suchman d D. Klein, (Eds.). Accident Research. Harper & Row, New York. 1964.
.-\ccident proneness:
a conceptual
analysis
71
Peck R. C. and Coppin R. S.. A position paper on accident proneness and driver-oriented safety models. In L. Shaw & H. S. Sichel. Accidmr Proneness. International Series of Monographs in Experimental Psychology. Vol. II, Pergamon Press. Oxford. 1971. Rodstein \I.. Accident proneness. J. ;\m. Med. .I\ss. 229. 1194. 1974. Seizer XI. L. and Vinokur A.. Life events, subjective stress and traffic accidents. r\m. I. Psychiut. 13. 903-906. 1971. Shaw L.. In L. Shaw & H. S. Sichel, .4ccident Proneness. International Series of Monographs in Experimental Psychology. Vol. II. Pergamon Press. Oxford. 1971. Shaw L. and Sichel H. S.. Accident Proneness. International Series of Monographs in Experimental Psychology. Vol. I I, Pergamon Press, Oxford. 1971. Sichel H. S.. New statistical techniques for the evaluation of the concept of accident proneness. In L. Shaw L H. S. Sichel, .Accidmr Proneness. International Series of Monographs in Experimental Psychology, Vol. Ii. Pergamon Press, Oxford, 1971 ._. .
Smeed R. 1.. Proneness of drivers to road accidents. Nnfure. London 186. 273-275. 1960. Suchman E. A.. A conceptual analysis of the accident phenomenon. Social Problems 8. 11[-2.(J, 1960. Thorndike R. L.. The Human Factors in Accidents with Special Reference to Aircraft Accidents, Project 11-30-001. Rep. I, U.S. Air Force. School of Aviation Medicine. Randolph Field, Texas, 1951. Tillman K’. A. and Hobbs G. E.. The accident-prone automobile driver. Am. 1. Psychiat. 106. 331-333. 1949, Wong u’. A. and Hobbs G. E.. Personal factors in industrial accidents: A study of accident proneness in an industrial group. Indust. Med. Surg. 18. 291-291. 1949.