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人格特质对自行车行为的预测。

Personality traits as predictors of cyclist behaviour.

机构信息

Monash University Accident Research Centre, Monash University, VIC 3800, Australia; Monash Institute of Transport Studies, Monash University, VIC 3800, Australia.

Monash University Accident Research Centre, Monash University, VIC 3800, Australia.

出版信息

Accid Anal Prev. 2020 Sep;145:105704. doi: 10.1016/j.aap.2020.105704. Epub 2020 Aug 6.

Abstract

Road user behaviour and personality traits are important determinants of driver crash risk. While a great deal of research has been undertaken to understand the relationships between crash involvement, behaviours and personality traits for motor vehicle drivers, comparatively few studies have considered these factors for cyclists. This manuscript presents the findings of a study conducted amongst a sample of six hundred and fifteen (615) Australian cyclists, investigating these issues. The aim of this research was to establish a structure for a cycling behaviour questionnaire applicable to a cohort of Australian cyclists. Using the dimensions identified from the questionnaire, the research investigated the relationship between self-reported crashes, behaviours and personality traits, in order to further develop our understanding of risk factors associated with cycling. Personality traits (agreeableness, extroversion, conscientiousness, neuroticism and openness to experience) were measured using the Big Five Inventory. While cyclist behaviour was measured using a modified version of the cyclist behaviour questionnaire developed by the Dutch national road safety research centre (SWOV). Principal Components Analysis (PCA) was performed on the cycling behaviour questionnaire to identify underlying subscales of behaviour. The PCA identified a two dimension model representing violations (α = 0.74) and errors (α = 0.65), consisting of 16 items from the original 22 item cyclist behaviour questionnaire. Linear regressions for each of the cyclist behaviour factors identified that age was negatively associated with errors and violations, indicating that older cyclists report fewer errors or violations. Similarly, there was a negative association with average weekly kilometres travelled. Gender was a significant predictor of errors, but not violations, with male cyclists reporting fewer errors than females. When considering personality traits, there was a positive association between extroversion and both errors and violations. Significant negative associations were identified for agreeableness and conscientiousness. Neither neuroticism nor openness to experience were associated with the frequency of errors or violations. The research identified that demographics, travel characteristics and personality traits provide insight into engagement in aberrant cycling behaviours and these behaviours are associated with self-reported crash involvement. The research provides insight into behaviours that could be targeted with appropriate education and enforcement strategies.

摘要

道路使用者的行为和个性特征是驾驶员碰撞风险的重要决定因素。尽管已经进行了大量研究来了解机动车驾驶员的碰撞卷入、行为和个性特征之间的关系,但相对较少的研究考虑了这些因素在自行车骑行者中的作用。本文介绍了一项在 615 名澳大利亚自行车骑行者样本中进行的研究的结果,该研究调查了这些问题。本研究的目的是为适用于澳大利亚自行车骑行者队列的自行车行为问卷建立一个结构。使用问卷确定的维度,研究调查了自我报告的事故、行为和个性特征之间的关系,以便进一步深入了解与自行车骑行相关的风险因素。个性特征(宜人性、外向性、尽责性、神经质和开放性)使用大五人格量表进行测量。而自行车骑行行为则使用荷兰国家道路安全研究中心(SWOV)开发的自行车行为问卷的修改版进行测量。对自行车行为问卷进行主成分分析(PCA)以确定行为的潜在子量表。PCA 确定了代表违规(α=0.74)和错误(α=0.65)的二维模型,该模型由原始 22 项自行车行为问卷中的 16 项组成。为每个自行车行为因素进行线性回归,发现年龄与错误和违规呈负相关,表明年龄较大的自行车骑行者报告的错误或违规行为较少。同样,与每周平均行驶公里数也呈负相关。性别是错误但不是违规的显著预测因子,男性自行车骑行者报告的错误比女性少。考虑到个性特征时,外向性与错误和违规都呈正相关。宜人性和尽责性呈显著负相关。神经质和开放性都与错误或违规的频率无关。研究发现,人口统计学特征、出行特征和个性特征提供了对异常自行车行为参与的深入了解,这些行为与自我报告的事故卷入有关。研究为可以通过适当的教育和执法策略来针对的行为提供了深入了解。

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