Prediction of mood and risk appraisals from trait measures: Two studies of simulated driving
Prediction of mood and risk appraisals from trait measures: Two studies of simulated driving
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DOI：
10.1002/per.2410090103
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发表时间：
1995-03
影响因子：
5.9
通讯作者：
L. Dorn;G. Matthews
中科院分区：
文献类型：
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作者：
L. Dorn;G. Matthews
对人格与情绪关系的两种截然不同的假说进行了区分。首先，宽泛的性格特征可能与情绪气质有关，因此可以预测各种情况下的情绪。其次，互动主义的人格研究方法表明，狭隘的、特定于情境的特征有时可能是情境中情绪最有力的预测因素。本文报道了在车辆驾驶的背景下，情绪与广义和狭义特征测量、艾森克人格量表（EPI；艾森克和艾森克，1964年）和驾驶行为量表（DBI；古lian， Matthews, Glendon， Davies和Debney， 1989年）之间的相关性。使用UWIST情绪形容词检查表（UMACL; Matthews, Jones and Chamberlain, 1990）对模拟驾驶前后的两个样本进行情绪测量。一个样本（N = 73）进行了“被动”驾驶，在这种情况下，几乎不需要与其他车辆互动。第二个样本（N = 93）执行了一个“主动”驾驶任务，在这个任务中，受试者必须决定何时超车。结果表明，DBI特征与情绪的关系比EPI特征更强，尤其是在主动驾驶之后。DBI不喜欢驾驶量表是驾驶后情绪最强的单一预测因子。在驾驶之前，受试者还要对自己和年龄性别相近的“同行”司机的事故风险、驾驶技能和判断力进行评分。对合并样本（N = 166）的这些数据进行分析表明，DBI是对风险和驾驶能力自我评级的更一致的预测指标，尽管评级与EPI之间存在一些关系。再一次，DBI不喜欢驾驶量表是自我评价最强的单一预测因子。在这个尺度上得分高的司机似乎不受司机普遍认为自己比同龄人更安全、更有能力的偏见的影响。结果表明，在驱动环境中，狭义性状比广义性状更具预测性。数据与驾驶员压力的交易模型一致，该模型提出不喜欢驾驶源于负面的二次评价。
Two contrasting hypotheses concerning the relationship between personality and mood are distinguished. First, broad traits may relate to emotional temperament, and so predict mood across situations. Second, the interactionist approach to personality implies that narrow, context specific traits may sometimes be the most powerful predictors of mood within situations. This article reports correlations between mood and broad and narrow trait measures, the Eysenck Personality Inventory (EPI; Eysenck and Eysenck, 1964) and the Driving Behaviour Inventory (DBI; Gulian, Matthews, Glendon, Davies and Debney, 1989), within the context of vehicle driving. Mood was measured with the UWIST Mood Adjective Checklist (UMACL; Matthews, Jones and Chamberlain, 1990), in two samples before and after a simulated drive. One sample (N = 73) performed a ‘passive’ drive, in which little interaction with other traffic was required. The second sample (N = 93) performed an ‘active’ driving task, in which subjects had to decide when to overtake other vehicles. Results showed that the DBI traits were more strongly related to mood than EPI traits, particularly following the active drive. The DBI Dislike of Driving scale was the strongest single predictor of post‐drive mood. Prior to the drive, subjects also rated accident risk, driving skill, and judgement, for themselves and for a ‘peer’ driver of similar age and sex. Analysis of these data in the combined sample (N = 166) showed that the DBI was the more consistent predictor of self‐ratings of risk and driving competence, although some relationships between ratings and the EPI were found. Again, the DBI Dislike of Driving scale was the strongest single predictor of self‐ratings. Drivers scoring high on this scale seem immune to drivers' general bias towards rating themselves as safer and more competent than their peers. It is concluded that narrow traits are more predictive than broad traits within the driving context. Data are consistent with the transactional model of driver stress, which proposes that dislike of driving is derived from negative secondary appraisals.