Does safety climate predict safety performance in Italy?

Different conceptualizations of safety climate have been proposed in the literature. One that seems particularly interesting from a measurement perspective was proposed by Neal, Griffin and Hart (2000). In their model, safety climate is defined as a specific form of organizational climate involving individual perceptions of the value of safety in the work environment which can be broken down into four facets: management values, communication, training, and safety systems. Furthermore, they propose a conceptual model in which safety climate affects safety knowledge and safety motivation, which in turn influence the two components of safety performance, namely safety compliance and safety participation. To date, however, their measure of these constructs has largely been applied and validated in English-speaking samples. Thus, the purpose of the current research was twofold: 1) to validate the Italian version of the questionnaire developed by Neal and colleagues 2) to examine the conceptual model linking safety climate to antecedents and components of safety performance. Our hypotheses were tested using a sample of 1255 employees from 14 different companies in Italy. Following Anderson and Gerbing (1981), a confirmatory factor analysis was conducted on the 32 items comprising the Neal and colleagues’ questionnaire. Results, 2 (450, N=1255)=1118, p<.001; CFI=.96; TLI=.96; RMSEA=.034(.032, .037), supported a model where safety compliance, safety participation, safety knowledge and safety motivation where posited as first order factors measured by their respective items. Safety climate was posited as a second order factor measured by management values, communication, training, and safety systems, which were, in turn, modelled as first order factors measured by their respective items. A structural equation model where safety climate influenced safety performance only indirectly via safety knowledge and motivation was first tested. This model showed an excellent fit to the data. However, a model also allowing direct effects of safety climate on both components of safety performance resulted in an even better fit, 2diff(2)=95., p<.0001. The final model explained 62% of safety compliance variance, and 52% of safety participation variance. In conclusion, the current results replicated in an Italian sample the original findings of Neal and colleagues, confirming the indirect contribution of safety climate on safety performance components, while also evidencing a direct effect of safety climate in predicting safety performance.