Abstract:
The performance of pilots in the aerospace environment is a critical factor in the success of modern air and space travel. Various methods of evaluating performances of pilots have been implemented and the search for improved means of evaluation is an ongoing process. Multiple factors influencing performance have been identified in the past. However, as the demands on the pilot’s performances varies with changing technology, so does the need to identify new risk factors, as well as ranking old and new factors in order of effect on performance. Aim The descriptive study aims to identify and rank risk factors affecting the performance of pilots as assessed by the Penalty Scoring System at a Precision World Flying Championship. Methods and materials Pilots participating at the 2008 World Precision Championship in Ried-Kircheim in Austria were requested to complete questionnaires regarding possible factors that could affect performance stress factors. Each questionnaire required the subject to answer 14 questions, relating to 17 possible factors. These questionnaires were linked to the participant’s individual score as per the official competition results. Results Out of a total number (n = 178) of pilot performances during a week period, 88 % (n=157) completed questionnaires. Only 57% (n=89) of these performances were included in the study, due to administrative difficulties preventing the accurate linking of performances to penalty scores. Out of the 17 possible risk factors, 4 factors (23 %) were identified as being significantly associated with the Penalty Scoring System. Age proved the most consistent factor, the younger pilots (youngest aged 21) performing consistently better than the older ones (oldest aged 67), even if the older pilots may have had more experience. Experience also proved reliable as a factor predicting outcome, as the performances of the moderate experienced group (having competed in 3 or less previous World championships) was associated with a lower penalty score. The mood of the pilots on the day of competing proved to be an effective way of predicting outcome, with a good mood associated with a lower penalty score. Any medical condition or medication used, were associated with a higher penalty score. The remaining factors (n=13) showed no association, although some (n=5) factors, like sleep deprivation and alcohol are known risk factors. Conclusions The study succeeds in showing an association between the Penalty Scoring System and 4 factors (Age, Experience, Mood and Medical conditions) affecting the performance of pilots. Although not the aim of this study, the conclusion can be made that the Penalty Scoring System may be a valuable tool in identifying risk factors affecting pilot’s performance.
