Antecedentes: 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. Background: 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.
Resumen: En el presente artículo estudiamos las propiedades psicométri-cas 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 resultados 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 igualmente 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. Palabras clave: Riesgos laborales, patologías psicofisiológicas, información, formación, instrumento psicométrico.Title: Development, internal consistency, reliability and validity of a scale of occupational hazards in Spanish. Abstract: 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.
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