Multilevel Confirmatory Factor Analysis of a Safety Climate Questionnaire

In the literature there is a general agreement about safety climate as a multilevel construct (Zohar, 2010) but often scales were not validated considering this safety climate characteristics. Shannon & Norman (2009), referring to factor analysis of safety climate surveys, affirmed the importance that a proper analysis requires adjustment to incorporate the multilevel nature of the data. The aim of this study is to conduct a multilevel confirmatory factor analysis (MCFA) to evaluate the factor structure underlying a safety climate questionnaire composed of three scales: Organizational Safety Climate (OSC) scale, Supervisor Safety Climate (SSC) scale and Co-workers Safety Climate (CSC) scale. A two-level design was used, considering the individual level and the work-group level. Data collection involved 1312 blue-collars from 7 Italian manufacturing companies. According with Griffin and Neal research (2000), at the individual level a second-order factor structure with four first-order factors for OSC scale and for CSC scale was identified. At the same level for SSC scale (values-safety systems, and safety coaching-communication) a second-order factor structure only with two first-order factors emerged. At the group level the same factorial structure was confirmed only for the SSC scale (NNFI = .95; CFI = .96; SRMRw= .049 SRMRb= .032; RMSEA = .06). A model with a one factor structure at the group level fitted better the data for the OSC scale (NNFI = .91; CFI = .92; SRMRw= .042 SRMRb= .054; RMSEA = .06) and a model with four factors free to covariates seemed more plausible ((NNFI = .95; CFI = .96; SRMRw= .035 SRMRb= .056; RMSEA = .051). These MCFA results demonstrated the importance to use proper analysis to date of the factor structure of a multilevel construct as safety climate.