Safeguarding construction workers from occupational hazards, whether arising from traumatic, ergonomic, and/or exposure accidents involves training workers to recognize such hazards. Earlier research presented at the Annual Construction Safety Conference explored the need for an assessment of the process of identification and applied Signal Detection Theory (SDT) to assess the ability of a worker to detect unsafe condi-tions. This research applies Fuzzy SDT to increase the applicabil-ity of conventional SDT analysis to construction settings where the definition of a signal event and its associated response do not follow a binary or dichotomous structure. Application of the methodology is demonstrated using a pilot study involving structural steel workers. Results from the sample of 10 ironwork-ers indicated the average sensitivity in identifying hazards was above average and that workers generally adopted a conser-vative strategy. Data analysis using conventional SDT model showed a marginally increased sensitivity, but with a very high variation. This study indicates that that the fuzzy SDT model was a better fit when quantifying and analyzing the ability of con-struction workers to recognize workplace hazards.

Hazard Identification Using Fuzzy Signal Detection Theory Tariq Abdelhamid, Michigan State Univeristy Puneet Narang, Michigan State Univeristy Takis Mitropoulos, Arizona State Univeristy