Age, gender, personality, burnout, job characteristics and job content as predictors of driver fatigue.

Objectives. Several studies have shown that one of the most common causes of collision is driver fatigue since fatigue causes drowsiness while driving and this decreases the driver's ability to maneuver the vehicle and increases the probability of their nodding off and falling asleep at the wheel. This may be due to a variety of personal reasons and specific factors connected to working conditions. In the present work we therefore intend to develop a predictive model for fatigue in professional drivers using the following indicators: age, gender, personality, burnout, characteristics and job content. Method. The participants were 516 professional drivers from different transport sectors, obtained through non-probabilistic sampling. SPSS version 25.0 was used for data analysis. Results. The predictive capacity of a number of variables that affect drivers by causing fatigue is determined. Fatigue can be predicted through certain variables, with the best predictor being exhaustion (48.8%). Conclusions. This research contributes to a greater knowledge of the factors that produce fatigue in professional drivers. It highlights the importance of designing interventions to reduce the incidence of fatigue, resulting in greater well-being for the driver and a lower incidence of collisions.

Predictive variables for sleep quality in professional drivers / Variables predictivas de la calidad del sueño en conductores profesionales

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 Lum-bar 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

Los conductores profesionales suelen padecer problemas para dormir o descansar correctamente. Esto puede deberse a diversos factores tanto personales como específicos de las condiciones laborales. En el presente trabajo nos hemos planteado desarrollar un modelo predictivo sobre la calidad del sueño en conductores profesionales utilizando los indicadores siguientes: Edad, Género, Confort del asiento, suspensión del asiento, Soporte lumbar ajustable del asiento del conductor, Horas de conducción, Problemas musculoesqueléticos, Drivers Stress, Irritación, Personalidad resistente, Burnout, conductas de seguridad e Impulsividad. MÉTODO: Los participantes han sido 369 conductores profesionales, de distintos sectores del transporte, obtenidos mediante un muestreo no probabilístico. 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 sueño. CONCLUSIONES: La calidad del sueño se puede predecir a través de determinadas variables, siendo la mejor predictora Exhaustion (Burnout). Esta investigación contribuye a un mayor conocimiento de la calidad del sueño y a la mejora de la salud de los conductores profesionales

Predictive power of selected factors over driver stress at work.

Professional drivers are considered prone to health risks. For this reason we have conducted a predictive study to analyze variables that may be predictors of stress in driving. Participating in this study were 372 drivers (93.4% men, 6.6% women) recruited through non-probabilistic sampling. The aim of the study is to develop a prediction model for job stress in professional drivers using the following indicators: personality, impulsiveness, hardy personality, job, age, seat comfort, seat suspension, lumbar support and driving hours. We found that the variables with predictive power over driving stress were: commitment over relaxed driving (ΔR2 = 0.101; ß = 0.135), danger prevention (ΔR2 = 0.139; ß = 0.342) and fatigue and anxiety (ΔR2 = 0.063; ß = -0.227); control over alertness and vigilance (ΔR2 = 0.069; ß = 0.278); agreeableness over sensation-seeking (ΔR2 = 0.047; ß = -0.268). In conclusion, driver stress can be predicted by certain variables. This study contributes to better understanding of driver stress and promotes safety at the wheel, thus helping to prevent traffic accidents.

Desarrollo, consistencia interna, fiabilidad y validez de una escala de riesgos laborales en lengua española / Development, internal consistency, reliability and validity of a scale of occupational hazards in Spanish

En el presente artículo estudiamos las propiedades psicométricas de una escala breve (RL-14) creada con el objetivo de detectar la información / formación recibida por los empleados, así como las patologías psicofisiológicas. Los participantes de la presente investigación son 1.489 empleados de diversos sectores como la formación, la construcción, el transporte, la sanidad, la industria, el comercio y la hostelería. Los resulta-dos obtenidos demuestran, después de realizar análisis factorial tanto exploratorio como confirmatorio, una estructura constituida por dos factores: "(F1) Información y Formación" y "(F2) Patologías Psicofisiológicas". Además, los dos factores obtenidos tienen una fiabilidad adecuada e igual-mente se constatan indicios de validez de los dos factores si se toman como referencia algunas variables sociodemográficas, la fatiga, el burnout y la tensión laboral. En suma, la presente escala puede resultar idónea para identificar de manera apropiada los riesgos laborales. Futuras investigaciones podrían utilizar el RL-14 como una herramienta de screening en combinación con otros instrumentos (AU)

In this article, we study the psychometric properties of a short scale (RL-14) created in order to ascertain the information / training received by employees and their psychophysiological disorders. The participants of this study were 1.489 employees in various sectors including education, construction, transport, health, industry, trade and hospitality. The results of an exploratory and confirmatory factor analysis show a structure consisting of two factors: "(F1) Information and Training" and "(F2) Psychophysiological Pathologies". In addition, the two factors obtained have adequate reliability and present evidence of the validity of the two factors if some sociodemographic variables, such as fatigue, burnout and job strain are taken as benchmarks. In short, this scale may be suitable for the proper identification of workplace hazards. Future research could use the RL-14 as a tool for screening in combination with other instruments (AU)