Occupational and traffic accidents among veterinary surgeons

Citation
R. Trimpop et al., Occupational and traffic accidents among veterinary surgeons, STRESS MED, 16(4), 2000, pp. 243-257
Citations number
62
Categorie Soggetti
Psychiatry
Journal title
STRESS MEDICINE
ISSN journal
07488386 → ACNP
Volume
16
Issue
4
Year of publication
2000
Pages
243 - 257
Database
ISI
SICI code
0748-8386(200007)16:4<243:OATAAV>2.0.ZU;2-N
Abstract
A recent large-scale survey of accidents in German veterinary surgeons was performed. Veterinary work represents a relatively high-risk occupation inv olving substantial driving throughout the working week (visiting rural farm s, etc.) with high reported rates of driving accidents and of accidents res ulting from physical injury through treatment of animals. In this paper the prediction of both driving and other work-related accidents among veterina ry surgeons (N = 494) is considered; it is appropriate to consider accident rates for this group separately, as there is evidence that the main predic tors of accidents differ between veterinary surgeons and auxiliary veterina ry personnel. A series of univariate and mutltivariate analyses of the data indicate that work-related accident occurrence is best predicted by work-r elated driving distance and risk attitude, with associations also being fou nd with working hours and stress. Driving accident rate is best predicted b y risk attitudes, stress and aggression, with associations also being found with age, number of children, work-related driving distance and safety att itude. Construction of transactional models suggests models in which the ef fect of work-related driving distance on driving accident rates is mediated by risk attitude, whilst the effect of working hours on work-related accid ents is mediated by stress. A detailed discussion of the general factors wh ich predict work-related accidents and specific occupational factors which apply to veterinary workers is also included. Problems associated with the high degree of intercorrelation between individual difference and occupatio nal predictors in the interpretation and modelling of accident data are dis cussed. The implications for practice are also discussed. Copyright (C) 200 0 John Wiley & Sons, Ltd.