Predictive variables for musculoskeletal problems in professional drivers

Identificador:  imarina:5768656

Handle: https://hdl.handle.net/20.500.11797/imarina5768656

Autores:  Serrano-Fernandez, Maria-Jose; Boada-Grau, Joan; Robert-Sentis, Lluis; Vigil-Colet, Andreu

Resumen:
© 2019 Elsevier Ltd Background: Professional drivers are considered prone to health risks with a high prevalence of diverse types of pain. Several authors have analyzed how certain work characteristics can produce musculoskeletal disorders in professional drivers. Drivers usually report back pain as a stressor, but they also report pain in areas such as the neck, shoulders and knees. Physical agents (vibrations and noise), postural stress, high density of traffic, numerous and frequent tasks put professional drivers at high risk of musculoskeletal disorders, fatigue, effects on drivers’ mental health. For this reason, we have conducted a predictive study to analyze variables that may be predictors of stress in driving. Methods: In the present work we develop a predictive model for musculoskeletal disorders in professional drivers that uses the following indicators: Age, Gender, Seat Comfort, Seat Suspension, Adjustable Lumbar Support for the driver's seat, Driving Hours, Sleep Quality, Driver Stress, Irritation, Hardiness, Burnout, Safety Behaviors and Impulsivity. Participants in the study were 372 professional drivers from various transport sectors recruited via non-probabilistic sampling. For this study we used the SPSS 25.0 program. Results: The variables to predict trunk musculoskeletal problems were: Psychophysiological Disorders, Challenge, and ME Extremities. These variables account for 30.6% of the criterion variable's variance. The variables to predict musculoskeletal problems of the extremities were: Psychophysiological Disorders, ME Truck, Cognitive Irritation, Seat Suspension, Hours, Cynicism and Emotional Irritation. These variables account for 34.3% of the criterion variable's variance. The best predictor was Psychophysiological Disorders. Conclusions: This study helps to extend knowledge of musculoskeletal disorders with the aim of improving the health of professional drivers. The results highlight the importance of designing individual interventions to reduce the incidence of musculoskeletal problems in professional drivers. This would provide greater well-being and lead to a reduction in sick leave.