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Delivery truck drivers’ work outside the cab: psychosocial discomforts and risks based on participatory video analyses

机译:送货卡车司机在出租车外的工作:基于参与式视频分析的社会心理不适和风险

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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.
机译:目的送货卡车司机在工作中面临各种身体和心理上的不适和风险。社会心理感知与生理和心理负荷(紧张和压力)相关联,影响着驾驶员在活动和条件下的各种机制。在这项研究中,参与式视频辅助分析被用于识别送货卡车司机在驾驶室外遇到的具有社会心理要求的工作情况。方法驾驶员根据以前在日常工作环境中录制的自己工作的视频进行识别。此外,其他利益相关者,例如经理和设计师,也确定了情况。研究人员对视频识别数据进行了进一步处理,显示了驾驶员和利益相关者对不适感背后的因果条件和干预条件的看法之间的差异。结果总共确定了99种情况,其中一半以上(53%)包括担心引起不同类型的不良事件,并带来损失的风险,例如人身伤害或财产损失。结果表明,在苛刻的工作环境中不仅存在风险和不适感,这似乎是相关的,但它们也表明了让不同利益相关者参与的重要性。结论本研究提供了一种独特的方法论方法,因为将视频观察和分析以及定性数据分析相结合,可以提供更深入的数据,并在可视化的风险管理过程中进行可视化。

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