BACKGROUND: The method "Learning by mistakes" was developed in Italy to conduct occupational injury investigations and to collect information on the genesis of injuries. The aim is to analyze data classified with this method in order to identify patterns among the factors contributing to injury dynamics. METHODS: Data regarding 673 factors, corresponding to 354 occupational fatalities that occurred in the Piedmont region (north-west of Italy) during 2005-2014 were considered. Latent Class Analysis (LCA) was applied to find patterns among these factors. RESULTS: The eight-class model was selected. Most of the factors fell in the class "Fall from height or vehicle rollover due to incorrect practice" (40.56%) while the remaining factors where heterogeneously distributed in the other classes. CONCLUSIONS: All the classes found allow for a logical interpretation. Systematic use of LCA could aid in uncovering new, unexpected patterns of factors not otherwise detectable by analysis of the single fatal accident.
BACKGROUND: The method "Learning by mistakes" was developed in Italy to conduct occupational injury investigations and to collect information on the genesis of injuries. The aim is to analyze data classified with this method in order to identify patterns among the factors contributing to injury dynamics. METHODS: Data regarding 673 factors, corresponding to 354 occupational fatalities that occurred in the Piedmont region (north-west of Italy) during 2005-2014 were considered. Latent Class Analysis (LCA) was applied to find patterns among these factors. RESULTS: The eight-class model was selected. Most of the factors fell in the class "Fall from height or vehicle rollover due to incorrect practice" (40.56%) while the remaining factors where heterogeneously distributed in the other classes. CONCLUSIONS: All the classes found allow for a logical interpretation. Systematic use of LCA could aid in uncovering new, unexpected patterns of factors not otherwise detectable by analysis of the single fatal accident.