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Beliefs and Naive Causal Explanations of Accidents and Prevention
Dongo Rémi KOUABENAN
( University of Grenoble II, Laboratory of Social Psychology, UFR SHS, BP. 47, 38040 Grenoble Cedex 9, France)
Abstract: This paper examines the way laypeople, who are unknowledgeable about safety matters but directly affected by the risks of their environment,
explain the causes of accidents, and also the possible impact of their systems of values and beliefs on the effectiveness of safety measures and campaigns. The
usefulness of an understanding of naive causal explanations (ones given by laypeople) is stressed. Knowledge of the causal explanations of accidents is not only
a prerequisite for accident prevention, but is also important for experts as well as nonexperts, i.e., workers or people facing risks. It is shown that various factors
cause bias in accident explanations, including beliefs about one's ability to cope with risks, hierarchical position in the organization, accident severity, level of
involvement in the accident situation, cultural beliefs, and so on. Such biases are shown to influence safety diagnoses and to be important factors in designing
effective preventive actions and in drafting relevant preventive messages.
Keywords: explanations; accidents; prevention
1 Introduction
Research on accidents and risks has demonstrated the utility of taking into account the values and beliefs of subjects who are not
knowledgeable in matters of risk-taking and accident explanations[1-4]. This is particularly true today when the organizational culture
and the culture of workers influence each other, and when both are having a greater impact on safety culture than in the past.
Moreover, it has been shown in some cases that technical and organizational safety measures are implemented with only a relative
degree of success: safety devices and regulations are not always observed, few people feel concerned by safety campaigns, workers
do not always use the self-protective equipment provided, and -- as workers sometimes say -- accident prevention does not seem to
be a major preoccupation of executives or managers. In an earlier study[2], I hypothesized that such a lack of concern towards
accident prevention and the somewhat moderate effectiveness of technical and organizational preventive measures could be rooted
both in different interpretations (or "views") of the same situation and in conflicting communication about risks and possible means
of prevention. This situation is caused by divergent and sometimes biased beliefs and perceptions regarding the causes of risks and
accidents. Studying naive or spontaneous accident explanations appears to be a good exploration path for enriching accident analysis
and enhancing individual commitment to preventive initiatives[2,4].
The hypothesis that beliefs and behaviors play a part in accident events and in risk management has aroused more interest lately
among specialists, especially those involved in programs to reduce risks and risky behaviors. In this area, knowledge gained from
psychology research -- particularly in cognitive occupational psychology and social psychology -- could make some significant
contributions. Representations and beliefs, whether individual or collective, seem to be an important factor in determining a person's
relationship to risk, and also his/her willingness to get involved in combatting risks and accidents.
Individuals' spontaneous explanations for accidents -- I called "naive explanations"[2] -- as well as their perceptions of risks, can
shed light on their behavioral choices and their differing reactions in the face of risks. An understanding of naive explanations can
also help account for why many standard prevention campaigns, which promote safety in general but are short on specifics, are
ineffective, and why the messages included in such campaigns are also ineffective: it is because they disregard the beliefs and
expectations of the individuals targeted for these campaigns.
2 Principles and Foundations of Naive Explanations
My recent studies[2,4,5] have demonstrated that spontaneous explanations given by individuals who are not safety specialists, but
who must nevertheless face risks, can be very important for understanding not only their risk-related attitudes and behaviors, but also
their reactions to prevention campaigns and procedures. These explanations help in developing more effective preventive measures.
This paper will begin by outlining the basic foundation of these so-called naive explanations, which are in large part influenced
by individuals' representations and beliefs. A more in-depth development of this topic can be found in several of our recent
articles[4-8].
My theory of naive explanations of accidents[2] states that causal explanations given spontaneously by operators or others
directly confronted with accidents and risks can supply vital information that is helpful in understanding the causes of accidents and
providing guidelines for risk- and accident-prevention strategies. Even if it is not yet a common practice to ask operators to explain
accidents that happen to them or their co-workers, it has become clear that operators who face on-the-job risks very often have their
own ideas about the causes of the accidents, incidents, and the even errors they notice or in which they are involved in some way.
Causal inferences -- whether implicit or explicit -- are generally made whenever an individual is faced with a troublesome, unusual,
or uncommon event, and they are present during all phases of accident analysis and risk management. Causal explanations allow
people to feel that their environment is stable and controllable. Conversely, having no explanation for an event is puzzling and
creates a state of psychological imbalance which, although transient, is hard to endure. Accidents generate a state of frustration that
impinges upon operators' need for safety and comfort. For this reason, the necessity of explaining and preventing accidents is an
important concern for both safety specialists and operators exposed to risks. Finding causes for accidents helps to maintain a sense of
control and to better cope with risky situations.
Based on Heider's approach[9] to the naive analysis of actions, the concept of naive causal explanations of accidents is used here
to refer to off-hand explanations of accidents made by ordinary individuals rather than by accident specialists[2]. In reality, this kind
of explanation, although subjective, is far from naive and deserves as much consideration in the drafting of prevention strategies as
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explanations furnished by safety experts. The term "naive" refers to the fact that spontaneous explanations essentially spring from
beliefs and representations, without explicit reference to a known methodology finding explanations, such as those used by scientists
or "experts".
Studies involving accident victims have shown that explanations can have a therapeutic function (Bordieri & Kilburg, 1991;
Bulman & Wortman, 1977, etc.). In particular, research has shown that certain types of internal explanations allow victims to more
quickly recover a sense of control. Knowing that one is partially responsible for what happens, and that one can or could have done
something to avoid it, seems to help victims face situations positively. Likewise, Furstenberg (1988) showed that simply talking
about an accident where one was a victim, recounting it and finding causes for it, allows victims to overcome anxiety and trauma
stemming from the event, and to recover a certain sense of control. Being able to pinpoint the source of the accident, and in
particular, being able to attribute it to one's own actions or to controllable elements, allows victims to glimpse possibilities of
prevention or corrective action. Blaming oneself is beneficial in cases where the accident is attributed to one's actions rather than
personality traits (less easily changed), since ascribing it to the latter could cause maladjustment [10,11]. In short, identifying accident
causes is one way that victims are able to get the situation back in hand, thereby reducing anxiety and stress, restoring order, and
regaining control.
Another idea supported here is that explaining accidents is a prerequisite to preventing them. Indeed, all preventive actions rely
(or should rely) on some view of accident causality. Explanations precede and guide preventive actions. They allow us to define
corrective actions or appropriate risk management procedures, and to plan preventive measures that are specific and relevant. I also
contend that accident explanations are not the exclusive concern of experts; rather, they matter to any person involved in risky
situations. Individuals faced with risks very often have ideas about the causes of accidents of which they are victims or which happen
in their surroundings. Unfortunately, preventive measures are all too often based on causal analyses performed by experts, who
neglect the representations and beliefs of those who must implement the measures. Yet it has been shown not only that experts and
laypeople think differently about accidents (they may disagree on causes and appropriate measures), but also that both groups are
subject to biases in their accident explanations[12]. In my mind every explanation is meaningful and useful. Taking naive explanations
into account allows us, among other things, to enrich and/or complete analyses conducted by experts. Such explanations are an aid in
designing preventive measures that will be viewed as relevant because they are based on the logic of the individuals in charge of
implementing them. We know that people are inclined to act in accordance with the causal inferences they construct[13]. Furthermore,
as Slovic et al. [12] noted, ""subjective judgements, whether by experts or laymen, are a major component in any risk assessment. If
such judgements are faulty, risk management efforts are likely to be misdirected".
3 Heuristic Model of Naive Explanations and Presentation of Research Results
My work in this area has utilized various methodologies, including interviews, questionnaires, analysis of attributions found in
accident reports or files, and experiments in which participants are asked to analyze various accident scenarios. These studies have
revealed that whatever their position in an organization, even non-specialists possess a certain "expertise" regarding risks and
accidents -- one that is based on their own experience. Such expertise does not contradict technical expertise; on the contrary, it can
be a useful complement for enhancing our understanding of accident causes and adherence to safety measures. As previously
mentioned, causal explanations are sometimes biased by various psychological processes, whether motivational (self-protection,
upholding self-esteem, need to present oneself positively), cognitive (incomplete or selective processing of accident information,
tendency to confirm one's own hypotheses or causal beliefs), or normative (need to conform to social norms and expectations,
socializing influences, etc.). These biases, which are defensive or illusory by nature, also depend on the victim's personal
characteristics (hierarchical position, age, type of injury, gender), the person analyzing the accident (hierarchical position, value and
belief systems, level of accident involvement, gender, age, perceptions of risk and of one's own coping capacities), the relationship
between these two individuals (co-worker, hierarchical superior, subordinate, interpersonal rapport), the seriousness of the accident's
consequences, and so forth.
We find, for example, that individuals who occupy a high position in the organizational hierarchy explain an accident differently
from those at lower levels: high-ranking individuals tend to attribute accidents to factors that involve the causal responsibility of the
lower ranks (inattention, non-adherence to safety procedures, lack of experience, etc.), whereas lower-level employees tend to
attribute accidents to organizational factors (time pressure, lack of materials or poor condition of supplies and equipment, lack of
protective gear), to management (lack of training programs and insensitivity to safety problems, focus on productivity, etc.), or to bad
luck[2,3]. Likewise, accident victims and witnesses explain the same accidents differently: victims attribute them more to external
factors beyond their control or causal role, whereas witnesses more often mention factors related to the victim's causal role [14]. A
more detailed description of this approach and the results it produces can be found in my various publications on this issue [2,3,6,7].
As a general rule, the explanations offered by persons involved in the accident in any way are primarily defensive, in the sense
that the accident is attributed to external factors such as the actions of others or bad luck; the explanations are internal or attributed to
the victim or to the accident's protagonists when the person explaining the accident is not directly involved or is emotionally
detached from the protagonists[2,3]. The seriousness of an accident seems to be a factor that accentuates defensive biases, especially
when the accident situation is one that involves the explaining person (situational relevance). When an accident is benign,
explanations are less defensive and less clear-cut. By contrast, when the accident is serious, there is a sharp distinction between the
various external and internal factors, and several different types of defensive reactions are found. The social, moral, economic, and
legal implications of the consequences of an accident most definitely play a role here. However, it would be erroneous to believe that
these biases are found only among non-specialists. Biases have been found in explanations given by both experts and laypeople [12].
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How can studying and understanding naive explanations and their underlying processes help us to improve safety expertise and
to prevent accidents? The following sections offer insight on this matter.
ACCIDENT
CHARACTERISTICS OF THE VICTIM
(beliefs, values, hierarchical
position, personality, seriousness
of injuries, amount of information,
skills, etc.)
BEHAVIOR IN RELATION
TO SAFETY
ATTRIBUTIONS
CHARACTERISTICS OF THE
ACCIDENT (type, economic
repercussions, seriousness)
CIRCUMSTANCES
(past & present industrial
relations climate, physical
state of the premises, financial
situation of the company, etc.)
CHARACTERISTICS OF THE
ATTRIBUTOR (degree of
involvement, witness, author,
victim, beliefs, personality,
hierarchical position, etc.)
RELATIONSHIP BETWEEN THE
VICTIM AND THE ATTRIBUTOR
(co-worker, friend, hierachical
superior, subordinate,
good/poor rapport)
gives rise to
may determine
Fig.1 Henuristic model of naive causal explanation of accidents
Figure 1. A heuristic model of naive causal explanation of accidents
4 Naive Explanations and Safety Diagnosis
The naive explanations that people give for accidents influence not only their attitudes, but also their behaviors and actions with
regard to safety. Such explanations help us understand why in certain situations, obvious or basic precautions are not taken, or why
individuals engage in objectively risky behaviors. If it is true that people tend to behave in accordance with their causal inferences [13],
then erroneous inferences may lead to maladaptive behaviors and risk-taking, and to uncommitted attitudes towards preventive
measures. In the same vein, defensive explanations ascribing accidents to others, to fate, or to external factors can have an
appreciable effect on an individual's relationship to risk and on his/her adherence to protective measures and personal involvement in
safety-related actions. Defensive explanations can also have an impact on supervisors' reactions to safety issues, on the general social
climate and safety-related atmosphere within the organization, and on the effectiveness of the company's diagnostic and preventive
actions. In addition, defensive explanations may have the unfortunate consequence of causing operators to incorrectly assess actual
workplace risks, or even to neglect important safety measures. As such, they can lead to resigned or irresponsible attitudes on the part
of both managers and subordinates.
It seems indeed that total reliance on internal explanations can cause external factors (working conditions, time constraints,
defective equipment, etc.) to be overshadowed -- factors which need to be considered if accident analysis is to be a systemic process.
An overemphasis on internal factors often causes managers to take disciplinary action or institute training interventions typically
directed only at operators. Such managerial measures are unlikely to be effective unless all factors are taken into account. On the
other side, when accidents are attributed entirely to external factors, this can cause individuals to minimize their own role in accident
occurrence and prevention. Expecting solutions from others or simply waiting for things to work out in the course of events,
operators can retreat into passivity or even total resignation, thereby increasing their exposure to risks and accidents. Similarly,
fatalistic explanations imply a lack of control over the accident situation, making the accident impossible to prevent. Such beliefs
lead to weak, uncommitted, or even non-existent involvement in preventive actions. The consequence will be greater exposure to
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danger and more risk-taking. A study involving different groups of highway drivers[1] showed that fatalistic beliefs, as well as the
superstitious behaviors sometimes associated with them, influence risk perception and lead to risk-taking and to the neglect of safety
measures. Fatalists generally tend to attribute car accidents to factors out of their control and to minimize the role of factors involving
personal initiative. Believing that an accident is caused by someone else or by circumstances beyond one's control implies that any
personal efforts toward accident prevention are useless; this in turn leads to an abdication of responsibility[2,7]. Seen from this angle,
naive defensive explanations can detract from safety or reliability. By leading to passivity and indifference, they tend to increase
objective risk and the probability of an accident.
Naive explanations, especially defensive ones, can cause conflicts between different people concerned with the accident
situation -- not only with respect to its causes, but also regarding the appropriateness of potential preventive measures. In their
concern for self-protection, people might be tempted to challenge or justify an identified cause if they perceive it as involving their
own role or responsibility, or as implicating someone close to them. Naive defensive explanations can thus impede sound
identification of accident causes and jeopardize the quality of preventive measures. This can worsen the work atmosphere and detract
from communication about risk, which is detrimental to safety. However, by analyzing these types of explanations and any possible
biases associated with them, the quality of safety expertise can be improved.
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Naive explanations
Erroneous inferences
Maladaptive
Indifference or
behaviors: risk-
poor adherence to
taking
preventive
measures
Clarify accident causes
Internal explanations 
External or fatalistic
explanations
concealment of external factors
Illusion of fairness
Accidents only happen to those
Partial/biased diagnosis
Passivity, negligence
who deserve it  passivity,
indifference
Risk-taking or increased objective risk
Accident
Fig.2 Contribution of naive explanations to safety diagnosis (Recap)
6 Naive Explanations and Prevention
Another important application of knowledge gained from studying naive causal explanations concerns accident and risk
prevention. A good prevention campaign cannot be designed without a certain knowledge of accident causalities and without taking
into account the psychological and sociological characteristics of the population targeted for these campaigns. Dejoy [15] pointed out
that preventive actions are based more on causal inferences than on actual causes. Note also that defensive attributions lead people to
believe that safety campaigns are mainly addressed to others and not to themselves, that accident prevention is for other people.
Fatalism and defensive explanations may therefore lead to inaction, resigned attitudes, and even to thoughtless risk-taking. For this
reason, explanation biases may be an obstacle to prevention. Conversely, "correct" inferences can lead to better-adjusted behaviors
and a greater commitment to preventive actions.
The effectiveness of preventive measures rests on the cooperation of the operators in charge of implementing them. We know
that operators and ordinary individuals do not always perceive safety issues in the same way as the experts who develop preventive
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measures[2,6,7]. Ordinary individuals (non-specialists) are more likely to adhere to such measures when they agree with the causal
analyses on which the measures are based, that is, if their own causal notions coincide with those of the experts who developed the
measures. This suggests that these measures should draw from people's representations and causal beliefs. Otherwise, they may be
viewed as irrelevant and lead to lower levels of adherence. As I have often mentioned in previous articles[6,7], what matters is not so
much that causal inferences be very accurate, nor that safety measures be truly effective; what really counts is that the person who
must implement them be convinced of their accuracy and effectiveness.
Safety training is another area that can be improved by knowledge of naive causal explanations. Educational goals for training
all persons involved in risk analysis should include enhancing awareness of biases found in accident explanations, in addition to
providing the means to overcome these biases and a greater feeling of personal control via the validation of internal explanations. By
showing trainees the contradictions between their own causal analyses and analyses coming from other sources, one can promote
critical thinking about causes and help individuals progress to a better grasp of the diversity of causal factors involved in accidents.
The best training will consist of a slow and patient process of modifying attitudes and beliefs. The training should also ensure that
each participant feels personally involved in risks and preventive actions.
Effectiveness of preventive
Operator
Perception of validity of causal
measures
adherence
analysis/preventive measures
Organizational diagnosis and
Safety training: change of
identification of ergonomic
Naive explanations and
improvements
prevention
attitudes and beliefs
Taking biases into
Enhancement of the power
account, diversity of
of control
factors involved
Commitment and involvement in
preventive actions
Information and communication
on risk: conflicts, relevance of
message, etc.
Fig.3 Naive Explanations and Prevention
When analyzing on-the-job accidents, having mixed groups of workers participate in accident analysis is in itself a good training
exercise. By comparing analyses coming from various sources during training, workers not only learn about possible biases and the
importance of avoiding them, but also gain important perspective on accident causality. In a second phase of training, awareness of
biases can be reinforced by presenting objective data from previous expert analyses done for accidents that occurred in the context of
a similar activity, organization, or industrial sector[5]. By exposing non-specialist individuals to accident analyses in areas that
concern them, training can not only enhance their feeling of control, but also promote their understanding of safety measures and
their resulting adherence to them. Employees will be more motivated to apply measures that they understand better and that they
view as relevant because they are in line with their own analyses of accident causality. We have also shown that the participation of
operators in safety diagnoses can contribute positively to the design of ergonomic changes that conform more to standards and are
better accepted[16].
Finally, taking naive explanations into account can help improve information and communication channels surrounding accident
analysis and prevention. By presenting other people's perceptions of risks and accident causes, different members of the organization
learn more about what they can expect from others and what others expect of them. Knowledge of biases helps eliminate ambiguities
and misunderstandings, increase the credibility and representativeness of information, dissipate fears, and appease conflicts. When all
concerned individuals -- including managers -- collaborate in accident analysis in a dispassionate atmosphere, this improves
knowledge of workplace risks and enhances trust. Lastly, to be effective, prevention-campaign material should be adapted to the
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beliefs and culture of the population to whom it is addressed [8]. Knowledge of naive explanations provides excellent ideas for
crafting well-targeted, effective communications, with messages based on the reasoning processes of the target population.
7 Conclusions
This paper has shed light on how people's beliefs affect accident explanations and analysis, as well as how those beliefs
contribute to safety planning and implementation of accident prevention campaigns. It is shown how explanations provided
spontaneously by the people who actually have to cope with risks can help us understand their attitudes and behaviors in the face of
risks. In particular, defensive explanations can prevent individuals from properly assessing their own role in accident occurrences and
can cause them to be indifferent to safety measures and thus to needlessly expose themselves to risk. Likewise, when managers give
this type of explanation, they may be led to absolve themselves of responsibility and expect everything to come from operators.
Knowledge gained in this area points out the need to pay close attention to the sources of data during both data collection and
analysis. Care should also be taken to gather data from a variety of sources and to treat it with a critical eye. Naive explanations help
us understand why people may be uninterested in prevention campaigns, which are too often based on the viewpoints of safety
experts alone and have little to do with the causal beliefs of the people at whom the campaigns are directed. The gap between these
two sets of beliefs can explain the perceived lack of relevance by workers, who sometimes have trouble understanding the validity of
safety measures designed by experts. But the fact is, workers will be more likely to apply safety measures if they understand the basis
for them. Both safety communications and preventive measures can be made more effective by examining the content of naive
explanations.
Finally, this body of research indicates the importance of taking the naive causal beliefs of the target population into account
when planning safety campaigns and communications, and the need to design very specific, targeted campaigns rather than general
ones, that is, campaigns that are adapted to the culture and context of each group or organization. Unlike standard approaches, it is
important for each intervention to first analyze the causal attributions made by the people involved, and to do so within that specific
socio-organizational context. In addition, safety planning should consider operators' perceptions of safety measures and any
alternative measures they might propose, before developing a prevention program that will optimally integrate the beliefs and
statements obtained from the preliminary analysis. This process can be time-consuming, but it is highly worthwhile, for the resulting
campaigns will challenge and mobilize people and thus have a greater chance of being fruitful.
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