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Prohn, Maria J. and Herbig, Britta ORCID logoORCID: https://orcid.org/0000-0002-6772-5255 (30. March 2022): Traffic safety knowledge gain of ambulance drivers after simulator-based training. In: BMC Medical Education, Vol. 22 [PDF, 1MB]


Background Compared to other road users, ambulance drivers are at a higher accident risk while driving with warning lights and sirens. No standard exists for training or education for emergency medical service employees driving ambulances. Training programs should positively influence knowledge. However, knowledge gain can be influenced by several different factors. This study developed a knowledge test for ambulance drivers to determine influencing factors on knowledge and its gain by simulator-based training.

Methods Two parallel knowledge test forms with 20 questions each were designed in several steps and tested on up to 174 participants. Questionnaires were used to study associated and influencing factors, such as objective experience, subjective attitudes, personality, motivation and demographic data.

Results Test construction showed good overall parallelism of the two tests as well as reliability and sensitivity. There was no correlation between subjective and objective knowledge gain, but participants with higher subjective knowledge gain showed a higher variation in objective knowledge. Younger age, higher qualification, higher number of license classes, fewer traffic violations, and more traffic safety trainings were positively associated with knowledge, whereas less yearly driving mileage, more traffic safety trainings, and higher risk sensitivity positively influenced knowledge gain through the training.

Conclusion Knowledge and its gain through training are very low. Reasons for the lack of predictive power of some variables, such as motivation, personality and attitudes, are discussed. This study presents a new tool for testing knowledge on driving with warning lights and sirens. It shows the need for objective testing and for further research in this special area.

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