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Safety climate, attitudes and risk perception in Norsk Hydro
Safety Science 34 (2000) 47±59
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Safety climate, attitudes and risk perception in Norsk Hydro T. Rundmo * Norwegian University of Science and Technology, Department of Psychology, 7055 Trondheim, Norway
Abstract The aims of this paper are to test mental images of risk and to present some results of a survey of safety climate, employee attitudes, risk perception and behaviour among employees within the industrial company Norsk Hydro. Two mental images were tested. They are both based on the assumption that it is possible to make a distinction between cognitive and aective processes involved in risk perception. The ®rst model was the `rationalistic' approach, which assumes that the aective component of risk perception is in¯uenced by cognitive judgements. The justi®cation for the second model is found in Zajonc's [Zajonc, R.B., 1980. Feeling and thinking. Preferences need no inferences. American Psychologist 35 (2), 151±175] conclusion that emotions are precognitive. In this model, entitled the `mental imagery' approach, emotion is seen as the driving force aecting cognition of risk and safety. Employees at 13 plants have answered a self-completion questionnaire. The plants belonged to the agricultural, aluminium, magnesium and petrochemical divisions within Norsk Hydro. A total of 731 respondents replied to the questionnaire. The mental imagery approach was somewhat better ®tted to the data than a rationalistic approach. Safety climate and employee attitudes towards safety and accident prevention contributed signi®cantly to the variance in employee occupational risk behaviour. Worry and the extent to which the employee felt safe/ unsafe was the most important predictor for the cognitive judgement of risk. Acceptability of rule violations seemed to be the most important predictor of behaviour, probably because acceptability also aected how often the respondents took chances and broke safety rules. # 2000 Elsevier Science Ltd. All rights reserved. Keywords: Mental images; Risk perception; Safety climate; Employee attitudes; Norsk Hydro
* Fax: +47-73-59-1656. E-mail address: [email protected]. 0925-7535/00/$ - see front matter # 2000 Elsevier Science Ltd. All rights reserved. PII: S0925-7535(00)00006-0
48
T. Rundmo / Safety Science 34 (2000) 47±59
1. Introduction 1.1. Mental images of risk It is interesting to study employee risk perception primarily because it may aect risk behaviour and also the probability of accidents and health injuries. However, there are a very few who suer a serious accident during their lifetime. Theories of accident causation are aimed at explaining why accidents take place. Perhaps even more interesting is to explain and understand why most of the time we so successfully manage to avoid accidents and health injuries. It may be that people at large perceive risk well enough to avoid accidents. Consequently, a strategy in accident prevention could be to build upon and expand the success criteria instead of ®nding out what went `wrong' when an accident has taken place. Risk perception is composed of a subjective assessment of the probability of experiencing an accident or a health injury caused by exposure to a risk source as well as emotions related to the source. Accordingly, SjoÈberg (1993) has suggested that an individual's experience of risk can be separated into one cognitive component and one emotional or aective component. An employee may believe that the probability of an accident during his or her working hours is high or low when thinking about personal risk as well as for employees in general. Employees may also be asked to which extent they agree or disagree with the statement that `the probability to experience an accident or a health injury is present at my work place'. In addition, they may also be asked to which extent they feel unsafe and worried when thinking about the source. It may be argued that when asking employees to assess the probability of an accident or health-injury, we ask for an assessment which is mainly based on cognition and rational judgements of risk perception and when asking them about their worry and whether they feel safe or unsafe we measure their emotional component. Then it is also relevant to question the cause±eect relation between cognition and emotion. Probability judgements and other `beliefs' about a risk source may cause worry and insecurity. Consequently, worry and insecurity are post-cognitive. However, respondents also express their emotions when reporting how strongly they believe in a statement. Consequently, post-cognitive emotion is present in the respondents' assessments, i.e. the more strongly they agree or disagree the stronger also is their emotion. Several approaches conceive emotion to be post-cognitive (Arnold, 1970; Lazarus et al., 1970; Smith and Ellworth, 1987; Ellsworth and Smith, 1988; Lazarus and Smith, 1988). According to Lazarus (1990) cognitions interpret stimuli in terms of their importance for the person. Therefore, they have to precede emotion. The cognition is not regarded as deliberate, rational, and conscious (Epstein, 1984). However, according to Zajonc (1980) emotions are primary to cognition. Accordingly, worry and insecurity may be a `mental image' which occurs as the ®rst reaction and need not depend on any cognitive judgements. The rationalistic approach conceives rational judgements of risk and beliefs about the risk as factors aecting worry and insecurity. The second approach, where
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mental images are conceived to exert in¯uence on beliefs, is what has been entitled the mental imagery approach (SjoÈberg and Biel, 1983). Studies carried out previously among oshore oil and gas workers on an oil platform also gave some support to the mental imagery approach in risk perception (Rundmo and SjoÈberg, 1996, 1998). The ®rst aim of the present paper is to test the ®t of the `rationalistic' as well as the `mental imagery' approach related to occupational risks. 1.2. Risk perception, safety climate and attitudes In risk research there has been a shift from individual psychological explanations to sociological and organisational frameworks for understanding risk perception and risk behaviour (see Pidgeon, 1995). To test models of risk perception and behaviour without including measures of safety climate, safety status and other aspects of the work environment which may aect safety seems not to be an appropriate strategy. In an occupational setting employee risk judgements have to be related to the `safety climate' and other organisational and social factors which are important for safety (Hale and Glendon, 1987). The concept of safety climate was introduced by Zohar (1980). According to Zohar the safety climate consists of the following dimensions: safety training programmes, management attitudes towards safety work, eects of safe conduct on promotion and on social status, level of risk at the place of work, priorities of work tempo versus safety and status of safety ocers and of safety committees. Brown and Holmes (1986) reduced the model to a three-factor model consisting of management concerns, management safety activities and employee risk perception. Dedobbeleer and BeÂland (1991) tested Brown and Holmes' safety climate model among workers employed on construction sites. They found strong correlations between management concerns and reduced the model to a two-factor model consist-ing of management commitment and workers' involvement. Organisational and social factors, i.e. factors not primarily directed at improving the safety level, can also aect safety. Examples of such factors are management commitment and involvement in safety work, and social support from the management, supervisors and other workers. For several years research has been carried out aimed at measuring attitudinal and other organisational and social aspects relevant to occupational safety (Lee et al., 1993; Alexander et al., 1995; Lee, 1995; Flin et al., 1996). This work includes measurement of safety climate factors, theories of accident causation, risk behaviour, safety status, risk perception and safety commitment. All these aspects are related to safety. Employee attitudes, safety commitment and organisational factors may aect acceptability of rule violations and the status of safety rules and instructions, which also may aect risk behaviour. Attitudes towards safety and the safety climate have been found to be associated with risk perception as well as risk behaviour (Rundmo, 1995, 1997). However, the cause±eects relationship between attitudes, risk perception and behaviour is not clear. Attitudes may aect risk perception, but it may also be that risk perception is a causal factor of behaviour in line with safety attitudes. The cause±eect relations
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between safety attitudes, the safety climate and risk perception may be questioned. Consequently, a second aim of the present paper is to analyse the relations between safety climate, safety attitudes and the cognitive and aective component of risk perception, and to relate these factors to risk behaviour. 2. Materials and methods 2.1. Sample A total of 13 plants participated in the study and 730 respondents replied to the questionnaire. The plants were located all over Europe and in USA and Canada and covered the aluminium, magnesium, agricultural (production of fertilisers), energy and petrochemical divisions of the company Norsk Hydro. A random sample of employees at all the plants were asked to ®ll in the questionnaire. It was distributed, ®lled in and collected at the place of work. The response rate was about 95%. The questionnaire data collection was carried out during Safety, Health and Environment revisions within the plants. A programme of risk identi®cation, understanding of risk and controlling risk is carried out regularly within all plants belonging to Norsk Hydro. 2.2. Questionnaire The respondents were asked to which extent they agreed with statements intended to measure safety climate, safety attitudes, management and employee safety commitment and involvement, safety status, as well as risk perception and behaviour. A ®ve-point evaluation scale ranging from ``fully agree'' to ``fully disagree'' was applied to measure the safety climate and employee attitudes. The subjects also rated how satis®ed they were with management and employee safety commitment and involvement and the safety status on a ®ve-point scale ranging from ``very satis®ed'' to ``very dissatis®ed''. Safety status included the following four dimensions: (1) employee in¯uence and communication with management, i.e. the way the respondent is consulted before decisions are made, and communication with management and supervisors; (2) personal protection equipment, which is availability and use of personal safety devices, as well as protection and safety devices and housekeeping; (3) rules and instructions, e.g. training and control and inspection routines; and (4) satisfaction with other people (Rundmo, 1998). The measurement of risk perception was intended to measure the cognitive as well as the emotional component. The respondents were asked to assess the probability for themselves as well as for ``an employee in general will suer an accident in the plant where you work''. The measures of aective reactions included assessment of ``worry'' as well as ``how safe'' the respondent felt when thinking ``about the risks in your work''. A seven-point bipolar scale was applied. It ranged from ``very prob-
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51
able'' to ``not at all probable'', ``very unsafe'' to ``very safe'', and ``very worried'' to ``not at all worried''. The mid-points were not labelled. Compound measures were made of the probability assessments as well as of worry and insecurity. Rundmo (1998) described in more detail the reliability and validity of the compound measures. Speci®c occupational risk behaviours were also listed and the respondents were asked to rate whether they ``very often'', ``often'', ``sometimes'', ``seldom'', or ``never'' carried out these actions in their jobs. The respondents were asked to assess the following risk behaviours: ``I take chances to get a job done'', ``I bend the rules to achieve a target'', ``I take risk to get the job done'', ``Job stress at the workplace stops me working to the rules'', ``I break rules and instructions relating to personal safety because they do not describe the safest way of working'', ``I break rules due to management pressure'', and ``I turn a blind eye when safety rules are broken''. These indicators are part of a measure of occupational risk behaviour validated by Rundmo (1998) (see also Rundmo, 1997). 2.3. Analysis Principal component analysis with iteration and varimax rotation was applied to determine the dimensions of each of the main elements (safety climate, attitudes, safety commitment, risk perception, risk behaviour) of the questionnaire. One Table 1 Safety climate, attitudes, satisfaction with safety status, risk perception and behaviour (reliability of the indices) Cronbach's alpha
No. of indicators
Safety climate Acceptability of rule violations Priorities of safety versus production Supervisor and friend commitment Management commitment Union representatives commitment
0.816 0.743 0.914 0.805 ±
3 4 4 2 1
Safety attitudes Fatalism Belief in accident prevention
0.708 0.728
5 2
Safety status Employee in¯uence and communication with management Status of personal protection measures Status of safety rules and instructions
0.748 0.627 0.788
3 3 5
Risk perception Cognitive component Emotional component
0.818 0.660
2 2
Risk behaviour
0.864
7
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analysis was carried out for each main element. Thereafter Cronbach's alphas were determined using all the respondents (n=731). Reliability analysis was also carried out separately for each plant on an identical factor structure, i.e. the one determined by the explorative analysis carried out on the entire material. The reliability of the indices was found to be reliable for all the plants. However employee assessments of the conditions varied, which means that the measurement instruments also were ®t to determine dierences between plants (see Rundmo, 1998). Dierences were found between plants, however, the same instruments could be applied to measure cultural and organisational dierences. The reliability of the indices is shown in Table 1. An important objective for the company is to reduce risk behaviour and, consequently, the probability of accidents among the employees. Path analyses were carried out applying the Structural Equation Modelling (SEM) methodology. The analyses were intended to test how well the safety climate and attitudes predicted risk perception and risk behaviour. Path analysis can be used for comparing the magnitude of direct and indirect eects between a set of variables. The higher the path coecient, the stronger is the eect that one variable has on another variable. Path coecients vary between ÿ1 and +1, being analogous to standardised partial regression coecients. Error terms in the path model are termed e. The dimensions were included as weighted z-score variables in the models as far as they signi®cantly aected risk perception and behaviour. 3. Results 3.1. Risk perception, safety climate, attitudes and safety status The results con®rmed that the respondent perceived the personal risk to be less compared to the risk for others. There was also a correlation between the probability assessment and worry and insecurity, r=0.36, P<0.001. It is also interesting to note that respondents rated the probability to be greater than their own worry and insecurity, indicating that some of them may see an accident or health injury to be probable. Despite this they do not feel especially unsafe and worried. Fig. 1 shows that there were possibilities for further improvements of the safety attitudes as well as the safety climate. The attitude related to belief in accident prevention/activity in safety promotion was `non-ideal' for the majority of the respondents. A great percentage also rated management and supervisor commitment and involvement in safety work to be non-ideal and almost 50% of the respondents did agree in attitudes, which accepted employees violating rules and taking chances in their job. An ideal attitude and an ideal safety climate is an attitude and a climate contributing to enhancing the safety, i.e. safe behaviour and lowering the frequency of accidents and near misses. A non-ideal attitude is one that contributes to the opposite. However, it may not be easy to decide on what really is an ideal attitude and an ideal safety climate contributing to safety. The criteria in the present study are partly based on expert judgements and partly on results of analyses aimed at predicting risk behaviour (e.g. Rundmo, 1997, 1998).
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Fig. 1. Employee assessments of safety climate, attitudes, satisfaction with safety status and behaviour (mean values).
Fig. 2. A mental imagery approach Ð b-matrix.
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Fig. 3. A mental imagery approach Ð g-matrix.
3.2. A `mental imagery approach' on risk perception and risk behaviour In Figs. 2 and 3 it is hypothesised that the emotional component of risk perception aects rational risk judgements and that safety attitudes and safety status also exert an in¯uence on the cognitive component. This is in accordance with the `mental imagery approach', which conceives emotion to be basic, i.e. emotion aects the rational judgements of risk as well as risk behaviour. Correlations between model and data were examined by means of the w2 test and tests of general adaptability (GFI) and modi®ed adaptability (AGFI). A non-signi®cant w2 shows that there are no signi®cant dierences between the predicted and observed co-variance matrices, i.e. that the observed data is in accordance with the theoretical model. The ®t of the model presented above was satisfactory, w2=22.71, df=21, P=0.360. The theoretical model did not deviate from the data, giving support to the `mental imagery approach'. The eects on behaviour of aect may be direct as well as indirect, through its eect on the cognitive judgements of risk. However, the direct eect on risk behaviour of the cognitive component of risk perception was totally insigni®cant. Therefore, it was excluded from the model. The strongest predictor of behaviour was acceptability of rule violations, b=0.50. Fig. 3 shows the direct as well as indirect eects on risk perception and risk behaviour obtained by a SEM analysis. The ®gure shows the `coecient of contribution' (Keeves, 1970; Marek and Iversen, 1989). When these coecients are added they form the adj. R2100%. The analyses were able to explain about 25% of the variance of rational judgements of risk. The compound measure of worry and
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insecurity was the most signi®cant predictor of cognitive or rational risk judgements. Supervisor commitment and involvement in safety work was also strongly correlated with rational judgements of risk. Fig. 3 also shows that management priority of safety versus production goals was the most signi®cant predictor of acceptability of rule violations. This means that there was a strong indirect eect on risk behaviour from management priorities of safety, also indicated in Fig. 3 by the eect of mediating variables with an eect on occupational risk behaviour. Employee fatalism related to safety and accident prevention was the second most important predictor variable of acceptability of rule violations. The same predictor also signi®cantly aected the status of safety rules and instructions. 3.3. `Rationalistic approaches' to risk perception and risk behaviour The cause±eect relation between the probability assessment and the compound measure of worry and insecurity was `turned' to test the `rationalistic approach'. The remaining part of the model was identical to the one shown in the Figs. 2 and 3. The ®t of this new model was signi®cantly less satisfactory, w2=57.01, df=21, P=0.001, compared to the model tested above (Fig. 4). Fig. 5 shows very similar eects on the criterion variables as shown in Fig. 3. In the model presented in Figs. 4 and 5 rational risk judgements in¯uenced worry and insecurity as well as behaviour. The `mental image' exerted a strong in¯uence on
Fig. 4. A rationalistic approach I Ð b-matrix.
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Fig. 5. A rationalistic approach I Ð g-matrix.
the judgement, and this predictor variable alone explained about 10% of the variance in rational judgement. However, as shown in Fig. 4, the ®t of this model was not so good compared to Fig. 2. This may be because the emotional component was expected to exert a direct eect on the status of safety rules and instructions as well as on acceptability of rule violations and indirectly on risk behaviour. A study carried out previously found no cause±eect relation between risk perception and behaviour (Rundmo, 1997). The results indicated that they were both endogenous variables aected by the same predictors. Rundmo (1998) also found that the eect of the cognitive and emotional component of risk perception may be related dierently to risk behaviour. Consequently, we also tested a model where the emotional component was a criterion variable in line with risk behaviour and where these two variables were conceived to be independent of each other (Figs. 6 and 7). The ®t of this model was not satisfactory, w2=57.77, df=21, P<0.001. 4. Discussion The results of the present study supported the `mental imagery' approach on risk perception. The emotional component of risk as well as the safety status, safety attitudes and their assessment of the safety climate seemed to form rational judgements of risk among employees. In addition, the emotional component of risk perception was found to be a strong predictor of the rational assessments. Fatalism,
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Fig. 6. A rationalistic approach II Ð b-matrix.
Fig. 7. A rationalistic approach II Ð g-matrix.
which was one of the dimensions of employee safety attitudes, seemed to be associated primarily with the cognitive component of risk perception. It is important to notice that structural equation modelling is aimed at comparing the ®t of models. The method does not ful®l strict experimental conditions necessary
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for inferring cause (e.g. James et al., 1982; Crozby, 1985). However, during the past few years SEM analysis has gained wide applicability for testing models in the social sciences. The best model is the one that explains a portion of the reality without substantial error terms. If a theoretical model is found not to deviate signi®cantly from the data, the model is said to be consistent with reality. The test then gives support to the causal relations speci®ed in the theoretical model. The results are all based on the assumption that it is possible to distinguish between cognitive and emotional aspects of risk perception and that it is possible to measure these two `components'. In psychology there has perhaps been a tendency to believe that it is necessary `to wire people up' to measure their emotions. However, it may be argued that emotions related to risk could be measured just by asking people how worried and concerned they are when thinking about potential dangers. In addition, we may ask about their rational judgements of risk by measuring their `beliefs' about the risk source as well as their probability judgements. When people assess the probability of an accident or injury there is of course also emotions involved. However, this does not change Zajonc's (1980) argument that aect is primary to cognition. Accordingly, it has to be made clear that the thesis that emotions are pre-cognitive cannot be taken literally, because emotional responses surely occur as reactions to hazards. However, such beliefs need not always be prior to emotions. They may serve the function of justifying the emotional reaction. Consequently, it is probable that they are consequences of emotional reactions rather than their causes. Studies carried out previously in an occupational setting (Rundmo, 1995, 1997), asking employees to assess how `safe' they felt, did not dier between the cognitive and emotional component of risk perception. Consequently we were unable to analyse mental models of risk separating the probability assessments from emotions related to risk sources. Risk perception was found to be an endogenous variable, in line with risk behaviour. However, risk perception was not found to be a strong predictor of behaviour (Rundmo, 1997). The results of the present study show that the cognitive and emotional components of risk perception were related dierently to risk behaviour. The `mental image' of risk seemed to be the main causal factor in the cognition of risk. However, correlations between emotion and risk behaviour were weak and rather insigni®cant. Rational judgements were found to be weakly, however signi®cantly, associated with behaviour. References Alexander, M., Cox, S., Cheyne, A., 1995. UK oshore safety culture. In: Collected Papers of The Conference ``Understanding Risk Perception'' Ð A Special 1-Day Conference on the Role of Risk Perception in Safety Management in the Workplace. Aberdeen, Scotland, 2 February. Arnold, M.B., 1970. Perennial problems in the ®eld of emotion. In: Arnold, M.B. (Ed.), Feelings and Emotions: The Loyoloa Symposium. Academic Press, New York, pp. 169±185. Brown, R.L., Holmes, H., 1986. The use of a factor analytic procedure for assessing the validity of an employee safety climate model. Accident Analysis and Prevention 18, 445±470.
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Crozby, P.C., 1985. Methods in Behavioural Research. May®eld, Palo Alto. Dedobbeleer, N., BeÂland, F., 1991. A safety climate measure for construction sites. Journal of Safety Research 22, 97±103. Ellworth, P.C., Smith, C.A., 1988. From appraisal to emotion: Dierences among unpleasant feelings. Motivation and Emotion 12, 271±302. Epstein, S., 1984. Controversial issues in emotional theory. In: Shaver, P. (Ed.), Review of Personality and Social Psychology, Emotions, Relationships, and Health Vol. 5. Sage, Beverly Hills, CA, pp. 64±88. Flin, R., Mearns, K., Gordon, R., Fleming, M., 1996. Risk perception by oshore workers in UK oil and gas platforms. Safety Science 22, 131±145. Hale, A.R, Glendon, I., 1987. Individual Behaviour in the Control of Danger. Elsevier, Amsterdam. James, L.R., Mulaik, S.A., Brett, J.M., 1982. Causal Analysis. Assumptions. Models, and Data. Sage, London. Keeves, J.P., 1970. The Home Environment and Educational Achievement. Australian National University, Canberra. Lazarus, R.S., 1990. Constructs of the mind in adaption. In: Stein, N.L., Leventhal, B., Trabasso, T. (Eds.), Psychological and Biological Approaches to Emotion. Erlbaum, Hillsdale, NJ, pp. 3±20. Lazarus, R.S., Smith, C.A., 1988. Knowledge and appraisal in the cognition±emotion relationship. Cognition and Emotion 2, 281±300. Lazarus, R.S., Averill, J.R., Opton Jr., E.M., 1970. Towards a cognitive theory of emotion. In: Arnold, M.B. (Ed.), Feelings and Emotions: The Loyoloa Symposium. Academic Press, New York, pp. 207± 232. Lee, T., 1995. The role of attitudes in the safety culture and how to change them. In: Collected Papers of The Conference ``Understanding Risk Perception'' Ð A Special 1-Day Conference on the Role of Risk Perception in Safety Management in the Workplace. Aberdeen, Scotland, 2 February. Lee, T., Macdonald, S.M., Coote, J.A., 1993. Perception of risk and attitudes to safety at a nuclear reprocessing plant. Paper presented at the Fourth Conference of The Society for Risk Analysis Ð Europe. Rome, 4±8 September. Marek, J., Iversen, E., 1989. Risikokontroll, Sikkerhet og Organisatoriske Forhold. (Risk control, safety and organisational factors). University of Bergen, Bergen (in Norwegian). Pidgeon, N., 1995. Risk perception research: implications for risk regulation and management. In: Collected Papers of the Conference ``Understanding Risk Perception'' Ð A Special 1-Day Conference on the Role of Risk Perception in Safety Management in the Workplace. Aberdeen, Scotland, 2 February. Rundmo, T., 1995. Vurdering av Ulykkesrisiko Blant Oshorepersonell. Resultatrapport. Utarbeidet for Oljedirektoratet. (Assessment of The Risk of Accidents Amongst Oshore Personnel. Main Report. Prepared for the Norwegian Petroleum Directorate). Stavanger: The Norwegian Petroleum Directorate, NPD-report, Order No. 544. (in Norwegian). Rundmo, T., 1997. Associations between risk perception and safety. Safety Science 24, 197±209. Rundmo, T., 1998. Organisational Factors, Safety Attitudes and Risk Behaviour. Main Report. Prepared for Norsk Hydro. Trondheim: Rotunde Publikasjoner. Rundmo, T., SjoÈberg, L., 1996. Risk perception by oshore personnel related to platform movements. Safety Science Vol. 24, 211±227. Rundmo, T., SjoÈberg, L., 1998. Risk perception by oshore oil personnel during bad weather conditions. Risk Analysis 18, 111±118. SjoÈberg, L., 1993. Oro och riskuppfatning. (Worry and risk perception). Paper presented at FRN/Riskkollegiets Symposium 17th September 1993, Wennergren-Center, Stockholm (in Swedish). SjoÈberg, L., Biel, A., 1983. Mood and belief-value correlations. Acta Psychologica 53, 253±270. Smith, C.A., Ellsworth, P.C., 1987. Patterns of cognitive appraisal and emotion related to taking an exam. Journal of Personality and Social Psychology 52, 475±488. Zajonc, R.B., 1980. Feeling and thinking. Preferences need no inferences. American Psychologist 35 (2), 151±175. Zohar, D., 1980. Safety climate in industrial organizations: Theoretical and applied implications. Journal of Applied Psychology 65, 96±101.
www.elsevier.com/locate/ssci
Safety climate, attitudes and risk perception in Norsk Hydro T. Rundmo * Norwegian University of Science and Technology, Department of Psychology, 7055 Trondheim, Norway
Abstract The aims of this paper are to test mental images of risk and to present some results of a survey of safety climate, employee attitudes, risk perception and behaviour among employees within the industrial company Norsk Hydro. Two mental images were tested. They are both based on the assumption that it is possible to make a distinction between cognitive and aective processes involved in risk perception. The ®rst model was the `rationalistic' approach, which assumes that the aective component of risk perception is in¯uenced by cognitive judgements. The justi®cation for the second model is found in Zajonc's [Zajonc, R.B., 1980. Feeling and thinking. Preferences need no inferences. American Psychologist 35 (2), 151±175] conclusion that emotions are precognitive. In this model, entitled the `mental imagery' approach, emotion is seen as the driving force aecting cognition of risk and safety. Employees at 13 plants have answered a self-completion questionnaire. The plants belonged to the agricultural, aluminium, magnesium and petrochemical divisions within Norsk Hydro. A total of 731 respondents replied to the questionnaire. The mental imagery approach was somewhat better ®tted to the data than a rationalistic approach. Safety climate and employee attitudes towards safety and accident prevention contributed signi®cantly to the variance in employee occupational risk behaviour. Worry and the extent to which the employee felt safe/ unsafe was the most important predictor for the cognitive judgement of risk. Acceptability of rule violations seemed to be the most important predictor of behaviour, probably because acceptability also aected how often the respondents took chances and broke safety rules. # 2000 Elsevier Science Ltd. All rights reserved. Keywords: Mental images; Risk perception; Safety climate; Employee attitudes; Norsk Hydro
* Fax: +47-73-59-1656. E-mail address: [email protected]. 0925-7535/00/$ - see front matter # 2000 Elsevier Science Ltd. All rights reserved. PII: S0925-7535(00)00006-0
48
T. Rundmo / Safety Science 34 (2000) 47±59
1. Introduction 1.1. Mental images of risk It is interesting to study employee risk perception primarily because it may aect risk behaviour and also the probability of accidents and health injuries. However, there are a very few who suer a serious accident during their lifetime. Theories of accident causation are aimed at explaining why accidents take place. Perhaps even more interesting is to explain and understand why most of the time we so successfully manage to avoid accidents and health injuries. It may be that people at large perceive risk well enough to avoid accidents. Consequently, a strategy in accident prevention could be to build upon and expand the success criteria instead of ®nding out what went `wrong' when an accident has taken place. Risk perception is composed of a subjective assessment of the probability of experiencing an accident or a health injury caused by exposure to a risk source as well as emotions related to the source. Accordingly, SjoÈberg (1993) has suggested that an individual's experience of risk can be separated into one cognitive component and one emotional or aective component. An employee may believe that the probability of an accident during his or her working hours is high or low when thinking about personal risk as well as for employees in general. Employees may also be asked to which extent they agree or disagree with the statement that `the probability to experience an accident or a health injury is present at my work place'. In addition, they may also be asked to which extent they feel unsafe and worried when thinking about the source. It may be argued that when asking employees to assess the probability of an accident or health-injury, we ask for an assessment which is mainly based on cognition and rational judgements of risk perception and when asking them about their worry and whether they feel safe or unsafe we measure their emotional component. Then it is also relevant to question the cause±eect relation between cognition and emotion. Probability judgements and other `beliefs' about a risk source may cause worry and insecurity. Consequently, worry and insecurity are post-cognitive. However, respondents also express their emotions when reporting how strongly they believe in a statement. Consequently, post-cognitive emotion is present in the respondents' assessments, i.e. the more strongly they agree or disagree the stronger also is their emotion. Several approaches conceive emotion to be post-cognitive (Arnold, 1970; Lazarus et al., 1970; Smith and Ellworth, 1987; Ellsworth and Smith, 1988; Lazarus and Smith, 1988). According to Lazarus (1990) cognitions interpret stimuli in terms of their importance for the person. Therefore, they have to precede emotion. The cognition is not regarded as deliberate, rational, and conscious (Epstein, 1984). However, according to Zajonc (1980) emotions are primary to cognition. Accordingly, worry and insecurity may be a `mental image' which occurs as the ®rst reaction and need not depend on any cognitive judgements. The rationalistic approach conceives rational judgements of risk and beliefs about the risk as factors aecting worry and insecurity. The second approach, where
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mental images are conceived to exert in¯uence on beliefs, is what has been entitled the mental imagery approach (SjoÈberg and Biel, 1983). Studies carried out previously among oshore oil and gas workers on an oil platform also gave some support to the mental imagery approach in risk perception (Rundmo and SjoÈberg, 1996, 1998). The ®rst aim of the present paper is to test the ®t of the `rationalistic' as well as the `mental imagery' approach related to occupational risks. 1.2. Risk perception, safety climate and attitudes In risk research there has been a shift from individual psychological explanations to sociological and organisational frameworks for understanding risk perception and risk behaviour (see Pidgeon, 1995). To test models of risk perception and behaviour without including measures of safety climate, safety status and other aspects of the work environment which may aect safety seems not to be an appropriate strategy. In an occupational setting employee risk judgements have to be related to the `safety climate' and other organisational and social factors which are important for safety (Hale and Glendon, 1987). The concept of safety climate was introduced by Zohar (1980). According to Zohar the safety climate consists of the following dimensions: safety training programmes, management attitudes towards safety work, eects of safe conduct on promotion and on social status, level of risk at the place of work, priorities of work tempo versus safety and status of safety ocers and of safety committees. Brown and Holmes (1986) reduced the model to a three-factor model consisting of management concerns, management safety activities and employee risk perception. Dedobbeleer and BeÂland (1991) tested Brown and Holmes' safety climate model among workers employed on construction sites. They found strong correlations between management concerns and reduced the model to a two-factor model consist-ing of management commitment and workers' involvement. Organisational and social factors, i.e. factors not primarily directed at improving the safety level, can also aect safety. Examples of such factors are management commitment and involvement in safety work, and social support from the management, supervisors and other workers. For several years research has been carried out aimed at measuring attitudinal and other organisational and social aspects relevant to occupational safety (Lee et al., 1993; Alexander et al., 1995; Lee, 1995; Flin et al., 1996). This work includes measurement of safety climate factors, theories of accident causation, risk behaviour, safety status, risk perception and safety commitment. All these aspects are related to safety. Employee attitudes, safety commitment and organisational factors may aect acceptability of rule violations and the status of safety rules and instructions, which also may aect risk behaviour. Attitudes towards safety and the safety climate have been found to be associated with risk perception as well as risk behaviour (Rundmo, 1995, 1997). However, the cause±eects relationship between attitudes, risk perception and behaviour is not clear. Attitudes may aect risk perception, but it may also be that risk perception is a causal factor of behaviour in line with safety attitudes. The cause±eect relations
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between safety attitudes, the safety climate and risk perception may be questioned. Consequently, a second aim of the present paper is to analyse the relations between safety climate, safety attitudes and the cognitive and aective component of risk perception, and to relate these factors to risk behaviour. 2. Materials and methods 2.1. Sample A total of 13 plants participated in the study and 730 respondents replied to the questionnaire. The plants were located all over Europe and in USA and Canada and covered the aluminium, magnesium, agricultural (production of fertilisers), energy and petrochemical divisions of the company Norsk Hydro. A random sample of employees at all the plants were asked to ®ll in the questionnaire. It was distributed, ®lled in and collected at the place of work. The response rate was about 95%. The questionnaire data collection was carried out during Safety, Health and Environment revisions within the plants. A programme of risk identi®cation, understanding of risk and controlling risk is carried out regularly within all plants belonging to Norsk Hydro. 2.2. Questionnaire The respondents were asked to which extent they agreed with statements intended to measure safety climate, safety attitudes, management and employee safety commitment and involvement, safety status, as well as risk perception and behaviour. A ®ve-point evaluation scale ranging from ``fully agree'' to ``fully disagree'' was applied to measure the safety climate and employee attitudes. The subjects also rated how satis®ed they were with management and employee safety commitment and involvement and the safety status on a ®ve-point scale ranging from ``very satis®ed'' to ``very dissatis®ed''. Safety status included the following four dimensions: (1) employee in¯uence and communication with management, i.e. the way the respondent is consulted before decisions are made, and communication with management and supervisors; (2) personal protection equipment, which is availability and use of personal safety devices, as well as protection and safety devices and housekeeping; (3) rules and instructions, e.g. training and control and inspection routines; and (4) satisfaction with other people (Rundmo, 1998). The measurement of risk perception was intended to measure the cognitive as well as the emotional component. The respondents were asked to assess the probability for themselves as well as for ``an employee in general will suer an accident in the plant where you work''. The measures of aective reactions included assessment of ``worry'' as well as ``how safe'' the respondent felt when thinking ``about the risks in your work''. A seven-point bipolar scale was applied. It ranged from ``very prob-
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able'' to ``not at all probable'', ``very unsafe'' to ``very safe'', and ``very worried'' to ``not at all worried''. The mid-points were not labelled. Compound measures were made of the probability assessments as well as of worry and insecurity. Rundmo (1998) described in more detail the reliability and validity of the compound measures. Speci®c occupational risk behaviours were also listed and the respondents were asked to rate whether they ``very often'', ``often'', ``sometimes'', ``seldom'', or ``never'' carried out these actions in their jobs. The respondents were asked to assess the following risk behaviours: ``I take chances to get a job done'', ``I bend the rules to achieve a target'', ``I take risk to get the job done'', ``Job stress at the workplace stops me working to the rules'', ``I break rules and instructions relating to personal safety because they do not describe the safest way of working'', ``I break rules due to management pressure'', and ``I turn a blind eye when safety rules are broken''. These indicators are part of a measure of occupational risk behaviour validated by Rundmo (1998) (see also Rundmo, 1997). 2.3. Analysis Principal component analysis with iteration and varimax rotation was applied to determine the dimensions of each of the main elements (safety climate, attitudes, safety commitment, risk perception, risk behaviour) of the questionnaire. One Table 1 Safety climate, attitudes, satisfaction with safety status, risk perception and behaviour (reliability of the indices) Cronbach's alpha
No. of indicators
Safety climate Acceptability of rule violations Priorities of safety versus production Supervisor and friend commitment Management commitment Union representatives commitment
0.816 0.743 0.914 0.805 ±
3 4 4 2 1
Safety attitudes Fatalism Belief in accident prevention
0.708 0.728
5 2
Safety status Employee in¯uence and communication with management Status of personal protection measures Status of safety rules and instructions
0.748 0.627 0.788
3 3 5
Risk perception Cognitive component Emotional component
0.818 0.660
2 2
Risk behaviour
0.864
7
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analysis was carried out for each main element. Thereafter Cronbach's alphas were determined using all the respondents (n=731). Reliability analysis was also carried out separately for each plant on an identical factor structure, i.e. the one determined by the explorative analysis carried out on the entire material. The reliability of the indices was found to be reliable for all the plants. However employee assessments of the conditions varied, which means that the measurement instruments also were ®t to determine dierences between plants (see Rundmo, 1998). Dierences were found between plants, however, the same instruments could be applied to measure cultural and organisational dierences. The reliability of the indices is shown in Table 1. An important objective for the company is to reduce risk behaviour and, consequently, the probability of accidents among the employees. Path analyses were carried out applying the Structural Equation Modelling (SEM) methodology. The analyses were intended to test how well the safety climate and attitudes predicted risk perception and risk behaviour. Path analysis can be used for comparing the magnitude of direct and indirect eects between a set of variables. The higher the path coecient, the stronger is the eect that one variable has on another variable. Path coecients vary between ÿ1 and +1, being analogous to standardised partial regression coecients. Error terms in the path model are termed e. The dimensions were included as weighted z-score variables in the models as far as they signi®cantly aected risk perception and behaviour. 3. Results 3.1. Risk perception, safety climate, attitudes and safety status The results con®rmed that the respondent perceived the personal risk to be less compared to the risk for others. There was also a correlation between the probability assessment and worry and insecurity, r=0.36, P<0.001. It is also interesting to note that respondents rated the probability to be greater than their own worry and insecurity, indicating that some of them may see an accident or health injury to be probable. Despite this they do not feel especially unsafe and worried. Fig. 1 shows that there were possibilities for further improvements of the safety attitudes as well as the safety climate. The attitude related to belief in accident prevention/activity in safety promotion was `non-ideal' for the majority of the respondents. A great percentage also rated management and supervisor commitment and involvement in safety work to be non-ideal and almost 50% of the respondents did agree in attitudes, which accepted employees violating rules and taking chances in their job. An ideal attitude and an ideal safety climate is an attitude and a climate contributing to enhancing the safety, i.e. safe behaviour and lowering the frequency of accidents and near misses. A non-ideal attitude is one that contributes to the opposite. However, it may not be easy to decide on what really is an ideal attitude and an ideal safety climate contributing to safety. The criteria in the present study are partly based on expert judgements and partly on results of analyses aimed at predicting risk behaviour (e.g. Rundmo, 1997, 1998).
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Fig. 1. Employee assessments of safety climate, attitudes, satisfaction with safety status and behaviour (mean values).
Fig. 2. A mental imagery approach Ð b-matrix.
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Fig. 3. A mental imagery approach Ð g-matrix.
3.2. A `mental imagery approach' on risk perception and risk behaviour In Figs. 2 and 3 it is hypothesised that the emotional component of risk perception aects rational risk judgements and that safety attitudes and safety status also exert an in¯uence on the cognitive component. This is in accordance with the `mental imagery approach', which conceives emotion to be basic, i.e. emotion aects the rational judgements of risk as well as risk behaviour. Correlations between model and data were examined by means of the w2 test and tests of general adaptability (GFI) and modi®ed adaptability (AGFI). A non-signi®cant w2 shows that there are no signi®cant dierences between the predicted and observed co-variance matrices, i.e. that the observed data is in accordance with the theoretical model. The ®t of the model presented above was satisfactory, w2=22.71, df=21, P=0.360. The theoretical model did not deviate from the data, giving support to the `mental imagery approach'. The eects on behaviour of aect may be direct as well as indirect, through its eect on the cognitive judgements of risk. However, the direct eect on risk behaviour of the cognitive component of risk perception was totally insigni®cant. Therefore, it was excluded from the model. The strongest predictor of behaviour was acceptability of rule violations, b=0.50. Fig. 3 shows the direct as well as indirect eects on risk perception and risk behaviour obtained by a SEM analysis. The ®gure shows the `coecient of contribution' (Keeves, 1970; Marek and Iversen, 1989). When these coecients are added they form the adj. R2100%. The analyses were able to explain about 25% of the variance of rational judgements of risk. The compound measure of worry and
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insecurity was the most signi®cant predictor of cognitive or rational risk judgements. Supervisor commitment and involvement in safety work was also strongly correlated with rational judgements of risk. Fig. 3 also shows that management priority of safety versus production goals was the most signi®cant predictor of acceptability of rule violations. This means that there was a strong indirect eect on risk behaviour from management priorities of safety, also indicated in Fig. 3 by the eect of mediating variables with an eect on occupational risk behaviour. Employee fatalism related to safety and accident prevention was the second most important predictor variable of acceptability of rule violations. The same predictor also signi®cantly aected the status of safety rules and instructions. 3.3. `Rationalistic approaches' to risk perception and risk behaviour The cause±eect relation between the probability assessment and the compound measure of worry and insecurity was `turned' to test the `rationalistic approach'. The remaining part of the model was identical to the one shown in the Figs. 2 and 3. The ®t of this new model was signi®cantly less satisfactory, w2=57.01, df=21, P=0.001, compared to the model tested above (Fig. 4). Fig. 5 shows very similar eects on the criterion variables as shown in Fig. 3. In the model presented in Figs. 4 and 5 rational risk judgements in¯uenced worry and insecurity as well as behaviour. The `mental image' exerted a strong in¯uence on
Fig. 4. A rationalistic approach I Ð b-matrix.
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Fig. 5. A rationalistic approach I Ð g-matrix.
the judgement, and this predictor variable alone explained about 10% of the variance in rational judgement. However, as shown in Fig. 4, the ®t of this model was not so good compared to Fig. 2. This may be because the emotional component was expected to exert a direct eect on the status of safety rules and instructions as well as on acceptability of rule violations and indirectly on risk behaviour. A study carried out previously found no cause±eect relation between risk perception and behaviour (Rundmo, 1997). The results indicated that they were both endogenous variables aected by the same predictors. Rundmo (1998) also found that the eect of the cognitive and emotional component of risk perception may be related dierently to risk behaviour. Consequently, we also tested a model where the emotional component was a criterion variable in line with risk behaviour and where these two variables were conceived to be independent of each other (Figs. 6 and 7). The ®t of this model was not satisfactory, w2=57.77, df=21, P<0.001. 4. Discussion The results of the present study supported the `mental imagery' approach on risk perception. The emotional component of risk as well as the safety status, safety attitudes and their assessment of the safety climate seemed to form rational judgements of risk among employees. In addition, the emotional component of risk perception was found to be a strong predictor of the rational assessments. Fatalism,
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Fig. 6. A rationalistic approach II Ð b-matrix.
Fig. 7. A rationalistic approach II Ð g-matrix.
which was one of the dimensions of employee safety attitudes, seemed to be associated primarily with the cognitive component of risk perception. It is important to notice that structural equation modelling is aimed at comparing the ®t of models. The method does not ful®l strict experimental conditions necessary
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for inferring cause (e.g. James et al., 1982; Crozby, 1985). However, during the past few years SEM analysis has gained wide applicability for testing models in the social sciences. The best model is the one that explains a portion of the reality without substantial error terms. If a theoretical model is found not to deviate signi®cantly from the data, the model is said to be consistent with reality. The test then gives support to the causal relations speci®ed in the theoretical model. The results are all based on the assumption that it is possible to distinguish between cognitive and emotional aspects of risk perception and that it is possible to measure these two `components'. In psychology there has perhaps been a tendency to believe that it is necessary `to wire people up' to measure their emotions. However, it may be argued that emotions related to risk could be measured just by asking people how worried and concerned they are when thinking about potential dangers. In addition, we may ask about their rational judgements of risk by measuring their `beliefs' about the risk source as well as their probability judgements. When people assess the probability of an accident or injury there is of course also emotions involved. However, this does not change Zajonc's (1980) argument that aect is primary to cognition. Accordingly, it has to be made clear that the thesis that emotions are pre-cognitive cannot be taken literally, because emotional responses surely occur as reactions to hazards. However, such beliefs need not always be prior to emotions. They may serve the function of justifying the emotional reaction. Consequently, it is probable that they are consequences of emotional reactions rather than their causes. Studies carried out previously in an occupational setting (Rundmo, 1995, 1997), asking employees to assess how `safe' they felt, did not dier between the cognitive and emotional component of risk perception. Consequently we were unable to analyse mental models of risk separating the probability assessments from emotions related to risk sources. Risk perception was found to be an endogenous variable, in line with risk behaviour. However, risk perception was not found to be a strong predictor of behaviour (Rundmo, 1997). The results of the present study show that the cognitive and emotional components of risk perception were related dierently to risk behaviour. The `mental image' of risk seemed to be the main causal factor in the cognition of risk. However, correlations between emotion and risk behaviour were weak and rather insigni®cant. Rational judgements were found to be weakly, however signi®cantly, associated with behaviour. References Alexander, M., Cox, S., Cheyne, A., 1995. UK oshore safety culture. In: Collected Papers of The Conference ``Understanding Risk Perception'' Ð A Special 1-Day Conference on the Role of Risk Perception in Safety Management in the Workplace. Aberdeen, Scotland, 2 February. Arnold, M.B., 1970. Perennial problems in the ®eld of emotion. In: Arnold, M.B. (Ed.), Feelings and Emotions: The Loyoloa Symposium. Academic Press, New York, pp. 169±185. Brown, R.L., Holmes, H., 1986. The use of a factor analytic procedure for assessing the validity of an employee safety climate model. Accident Analysis and Prevention 18, 445±470.
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