Delivery truck drivers’ work outside the cab : psychosocial discomforts and risks based on participatory video analyses
Ojel-Jaramillo Romero, Jose Manuel; Reiman, Arto; Cañas Delgado, Jose Juan; Väyrynen, Seppo; Pekkala, Janne; Forsman, Mikael (2018-06-13)
Ojel-Jaramillo Romero, J., Reiman, A., Cañas Delgado, J., Väyrynen, S., Pekkala, J., Forsman, M. (2018) Delivery truck drivers’ work outside the cab: psychosocial discomforts and risks based on participatory video analyses. European Transport Research Review, 10 (2), 27. doi:10.1186/s12544-018-0299-3
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Purpose: Delivery truck drivers face various physical and psychosocial discomforts and risks in their work. Psychosocial perceptions are linked to physiological and psychological loads—strain and stress—affecting drivers throughout various mechanisms within activities and conditions. In this study, participatory video-assisted analyses were utilised for identifying psychosocially demanding work situations that delivery truck drivers encounter outside the cab.
Methods: Identifications were made by the drivers from previously recorded videos of their own work in their daily work environments. In addition, other stakeholders, such as managers and designers, also identified situations. The video identification data were further processed by the researchers, showing differences between the perceptions of the drivers and stakeholders on the causal conditions and intervening conditions behind the discomfort identifications.
Results: All together 99 identified situations—over half (53%) of which included a fear of causing different types of undesired events with risks of losses, such as human injuries or material damages. The results showed not only do risks and discomforts exist in demanding work situations, which seemed relevant, but they also indicated the importance of involving different stakeholders.
Conclusions: This study provides a unique methodological approach, as video observations and analyses and qualitative data analysis are combined to provide more in-depth data with visualizations into risk management processes.
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