Psychosocial factors, psychological well-being and safety incidents among long-distance bus drivers in Ghana: A cross-sectional survey

ACTA PSYCHOLOGICA(2024)

引用 0|浏览0
暂无评分
摘要
Background: Commercial bus drivers account for most road traffic crashes and related mortality. The psychosocial working conditions of these drivers have been found precarious. However, road safety initiatives in Ghana still focus on correcting risky driving behaviours, ignoring the conditions under which these drivers operate. Hence, the purpose of this study was to examine whether psychosocial work factors can predict the psychological wellbeing and risky driving behaviours of long-distance bus drivers in Ghana. Methods: This quantitative cross-sectional survey recruited 7315 long-distance bus drivers that operate from Accra to other parts of Ghana and cities in other West African countries. Hypotheses were tested using Partial Least Squares Structural Equation Modelling (PLS-SEM). Results: We found that job demands and job resources are direct and significant predictors of psychological wellbeing and safety incidents among these drivers. Moreover, psychological well-being of the drivers had a significant inverse relationship with their safety incidents. Psychosocial safety climate (PSC) had a negative association with safety incidents, and a positive but non -significant association with psychological well-being. PSC had a negative and significant association with job resources contrary to the notion of the PSC theory. Conclusion: Psychosocial work factors are predictors of psychological well-being and safety incidents of longdistance bus drivers. Owners and managers of bus transport businesses in Ghana, driver unions and station masters need to highly prioritise psychological health and safety of this bus drivers by providing suitable job resources and adopting bottom -up communication that might help the drivers effectively cope with their job demands.
更多
查看译文
关键词
Psychosocial work factors,Psychological well-being,Safety incidents,Ghana
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要