Predictive variables for sleep quality in professional drivers

2021 
espanolAntecedentes: Los conductores profesionales suelen padecer problemas para dormir o descansar correctamente. Esto puede deberse a diversos factores tanto personales como especificos de las condiciones laborales. En el presente trabajo nos hemos planteado desarrollar un modelo predictivo sobre la calidad del sueno en conductores profesionales utilizando los indicadores siguientes: Edad, Genero, Confort del asiento, suspension del asiento, Soporte lumbar ajustable del asiento del conductor, Horas de conduccion, Problemas musculoesqueleticos, Drivers Stress, Irritacion, Personalidad resistente, Burnout, conductas de seguridad e Impulsividad. Metodo: Los participantes han sido 369 conductores profesionales, de distintos sectores del transporte, obtenidos mediante un muestreo no probabilistico. Se han utilizado el programa SPSS 25.0. Resultados: Se determina la capacidad predictiva de algunas variables que afectan a los conductores sobre la calidad del sueno. Conclusiones: La calidad del sueno se puede predecir a traves de determinadas variables, siendo la mejor predictora Exhaustion (Burnout). Esta investigacion contribuye a un mayor conocimiento de la calidad del sueno y a la mejora de la salud de los conductores profesionales. EnglishBackground: Professional drivers often have problems sleeping or resting properly. This may be due to various factors, both personal and specific to their working conditions. In this study, we set out to develop a predictive model for the quality of sleep in professional drivers using the following indicators: Age, Gender, Seat Comfort, Seat Suspension, Adjustable Lumbar Support of the Driver’s Seat, Driving Hours, Musculoskeletal Problems, Driver Stress, Irritation, Resistant Personality, Burnout, Safety Behaviors and Impulsivity. Method: The participants were 369 professional drivers from different transport sectors, obtained through non-probabilistic sampling. The SPSS 25.0 program was used for statistical analysis. Results: The predictive capacity of certain variables that affect drivers’ sleep quality is determined. Conclusions: Sleep quality can be predicted by means of certain variables, the best predictor of which is Exhaustion (Burnout). This research contributes to the body of knowledge on sleep quality and on improving the health of professional drivers.
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