Catastrophe modeling of the accident process: evaluation of an accident reduction program using the occupational...

The report details a catastrophe theory model of the accident process with empirical validation. According to the cusp model, two distinct levels of risk can be observed for a distribution of group accident rates, one at 0.0 Occupational Safety and Health Association (OSHA)-reportable accidents per 100 person-years of exposure and one at 11.5. Changes within or between the two levels are determined by two control parameters: environmental hazard (asymmetry) and operator load (bifurcation). The sample consisted of 68 work groups from 8 Milwaukee-Chicago area sheet metal mills and foundries who completed the Occupational Hazards Survey (OHS). The OHS contributed six bifurcation variables (safety management, life stress, physical stress anxiety, beliefs about accident control, and experience) and two asymmetry variables (environmental hazards and danger). All organizations received an interpretive report of their survey responses with recommendations for accident control, and had held their reports for two to nine months at the time the follow-up accident rate data were collected. There were two additional bifurcation variables: months holding report and group size. Regression analysis determined that the cusp model (R2 = .42) was more than twice as accurate as the best log-linear or linear alternative. Accidents were successfully controlled by safety managers' attention to recommendations produced by the OHS analysis. Catastrophe theory provided some novel insights regarding the linkage between predictor variables and actual behavior. Research has shown that a substantial percentage of occupational accidents are the result of human error. In an effort to explain and predict such errors in a systematic manner, an accident process model based on the cusp catastrophe is developed and tested. The model offers several unique and useful properties: (1) It proposes that changes in accident rates for work groups are the result of a nonlinear dynamic process. (2) The distribution of accident rates is bimodal, with one model near zero and the other at some higher level. (3) Changes in accident rates are predicted from four sources: (i) ambient danger and hazard levels, (ii) variables that impact upon human performance capability, (iii) initial accident rates, and (iv) the mathematical function that interrelates those variables. (4) The mathematical model has inherent properties that allow for causal inference. Environmental and human performance factors can be operationalized as sets of more specific variables. In this application. The Occupational Hazards Survey was used to gather data from mill and foundry workers pertaining to hazards and dangers, adequacy of safety management, stress, anxiety, and beliefs about accident control.(ABSTRACT TRUNCATED AT 400 WORDS)