Predictive variables for sleep quality in professional drivers

Abstract

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.

A Decision-Making Model for Professional Drivers Selection: A Hybridized Fuzzy–AROMAN–Fuller Approach

“…Nordfaern et al [18] investigated safety attitudes, behavior, anxiety, and perceived control among professional and non-professional drivers. Serrano-Fernández et al [19] addressed the most important predictive variables for sleep quality in professional drivers. Chen et al [20] conducted a driving simulator study regarding the safety of professional drivers in an aging society.…”

“…Authors Considered Problem Öz, Özkan and Lajunen [17] Professional and non-professional drivers' stress reactions and risky driving Nordfaern, Jorgensen and Rundmo [18] Safety attitudes, behavior, anxiety, and perceived control among professional and non-professional drivers Rosso, Perotto, Feola, Bruno and Caramella [14] Obesity among professional drivers Meng, Li, Cao, Li, Peng, Wang and Zhang [21] Driving fatigue among professional taxi and truck drivers Maslać, Antić, Lipovac, Pešić and Milutinović [13] Comparison of the professional and non-professional drivers considering rules violations Wu, Zhao, Rong and Zhang [16] Effectiveness of eco-driving training for male professional and non-professional drivers Chen, Sze and Bai [20] Safety of professional drivers in an ageing society Han and Zhao [22] Driver behavior and traffic accident involvement among professional urban bus drivers in China Serrano-Fernández, Tàpia-Caballero, Boada-Grau and Araya-Castillo [24] Variables that predict attitudes toward safety regulations in professional drivers Zaranka, Pečeliunas and Žuraulis [12] Factors affecting the behavior of road users Serrano-Fernández, Boada-Grau, Robert-Sentís and Vigil-Colet [19] Predictive variables for sleep quality in professional drivers Chen, Sze, Newnam and Bai [15] Difference between professional and non-professional drivers in terms of the effectiveness Llamazares, Useche, Montoro and Alonso [25] Commuting accidents of professional drivers when the occupational risk exceeds the workplace Hernández-Rodríguez, Maeso-González, Gutiérrez-Bedmar and García-Rodríguez [23] Psychosocial risk and job satisfaction in professional drivers…”

A Fadiga no Transporte Rodoviário de Cargas: Uma Revisão Sistemática Sobre os Motoristas de Caminhão

“…Dirigir requer atenção contínua durante a execução de atividades de direção complexas, que demandam a análise cautelosa do ambiente observando a existência de perigos potenciais. A percepção dos perigos pode ser afetada pela fadiga e estresse do motorista, especialmente para profissionais que muitas vezes invertem o ciclo do sono e enfrentam congestionamentos para cumprir horários rígidos (BELZER; SEDO, 2017;CARDOSO et al, 2019;GARBARINO et al, 2018;HEGE et al, 2019;ISELAND et al, 2018;SERRANO-FERNANDEZ et al, 2021).…”

The Role of High-Risk Behaviors, Fatigue, and Drowsiness in the Occurrence of Road Accidents and Near Miss Accidents among Tehran Truck Drivers in 2019

“…According to research, the rate and severity of road incidents were several times higher in developing countries than in developed ones [5,7]. Several studies have been conducted on the relationship between drowsiness and road accidents, according to which drowsiness in professional drivers can be caused by factors, such as long working hours, insufficient rest, irregular schedules, night shifts, long waking hours, physical activity, and mental obsession [8][9][10]. These factors have been reported to reduce the ability to drive, create a feeling of mental fatigue, slow the reaction time, lead to the lack of attention to important details, and cause poor performance [11][12].…”