Determinants of Emotional Experiences in Traffic Situations ... - OPUS

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38 The Emotional Spectrum in Traffic Situation! Table 2: Scenario examples from study 1 # Goal Congruency Goal Relevance x Blame Task Demand Text 1 Short Waiting Time (Circumstance x Arrival) Construction Site Sufficient Time & Low Traffic Density Today you have an important appointment downtown but there is still plenty of time to look for a parking possibility at the location. When you reach the next junction you turn onto a main road with three lanes and minimal traffic. You decide to take the right lane. All of a sudden, the traffic slows down and a warning sign predicts a narrowing of the street from three to two lanes due to a construction site. Here the road conditions are bad and you have to drive very slowly. Further ahead you can already see the end of the construction site and a clear road. 2 Near Accident (Person x Safety) Braking Car Insufficient Time & High Traffic Density Today you have an important appointment downtown, but you are running late and are under time-pressure. At the next junction you turn right onto a main road with three lanes and very dense traffic. Without a warning a car brakes directly in front of you. You have to react quickly but you manage to stop in time. 9 TL Are Functional Again (Circumstance x Safety) Malfunctioning Traffic Lights at a Junction Sufficient Time & Low Traffic Density Today you have an important appointment downtown, but there is still sufficient time to look for a parking possibility at the location. At the next junction you turn onto a main road with three lanes and minimal traffic. You decide to take the right lane. In the distance you see that the traffic lights at the next big junction are not working. Just as you reach the junction the traffic lights go on again. The green light indicates that you can proceed without delay. 10 Crossing Junction Not Possible (Person x Arrival) Car In Front Does Not Proceed Insufficient Time & High Traffic Density Today you have an important appointment downtown, but you are running late and are under time-pressure. At the next junction you turn right onto the main road with three lanes and very dense traffic. At the next traffic light you have to wait behind another car. The traffic light turns green, but the car in front of you does not proceed. Just before the traffic light turns red it accelerates and manages to cross the junction but you have to wait for the light to change again.
The Emotional Spectrum in Traffic Situations 39 2.2.3 Results On a scale from one to five the participants liked driving very much (M = 4.07; SD = 0.99) and rated its importance with M = 3.37 (SD = 1.28). Cronbach’s-Alpha of α = .60 and a correlation of r = .44, (p < .001) revealed a sufficient identity between the two tested aspects of driving motivation. Therefore, the ratings of the two items (how much one enjoys driving and how important it is) were combined into one score and labelled as driving motivation. 2.2.3.1 Occurrence of Reported Emotions and Their Relationship to Personal Characteristics From the sixteen emotions described by the GEW, seven were suitable for this study. To be selected, the emotion had to appear at least twice during the course of the experiment across all participants. Emotions such as disgust or envy were practically never triggered by the given stimulus and therefore excluded from further analysis (Table 3). The seven emotions that were used were anger, relief, anxiety, surprise, satisfaction, hope and contempt. Anger was the most prevalent emotion over all participants with M = 3.12 (SD = 0.55) in strength and M = 9.16 (SD = 3.12) in frequency in the sixteen situations. Contempt was the weakest (M = 2.14, SD = 1.11) and rarest emotion (M = 2.03, SD = 2.14) used in the more thorough analysis. The emotions anger (H1, H4), anxiety (H2, H4), relief, hope and satisfaction (H3, H4) as well as contempt (H4) were used to test the hypotheses. Surprise was an emotion that could not be associated with any hypothesis and was therefore not involved in this process. The influence of gender, annual mileage and driving motivation as well as the DAS and STAI scores (if appropriate) on reported emotion was measured with multiple linear regressions (Table 4). Personal characteristics were the independent variables and the intensities of the specific emotions were the dependent variables. Linear regression made it possible to take any relationships between the influencing attributes of the person into account, and this could lead to more precise estimates of each independent variable (the results are presented as standardized coefficients (β) to facilitate comparisons). Women reported more intense anxiety and relief than men (β = -.18; p < .048 and β = -.33; p < .001). Driving experience was negatively related to anger, and participants with low mileage reported higher levels of this emotion (β = -.25; p < .020). Participants with high driving motivation stated more intense anger (β = .22; p < .029) and contempt (β = .21; p < .037) but also more satisfaction (β = .29; p < .008) as compared to low-motivated drivers. Participants scoring high on the DAS reported stronger anger (β = .27; p < .001) and contempt (β = .31; p < .001) over the course of the experiment. High trait anxiety participants, as measured with the STAI, reported more intense anxiety (β = .40; p < .001). !
Page 1 and 2: Determinants of Emotional Experienc
Page 3 and 4: Acknowledgements I would like to th
Page 5 and 6: Abstract Emotions play a prominent
Page 7 and 8: 2.3.2.2.5 Testing H5 ..............
Page 9 and 10: List of Tables Chapter 2: The Emoti
Page 11 and 12: Introduction 11 1. Introduction 1.1
Page 13 and 14: Introduction 13 (Deffenbacher et al
Page 15 and 16: Introduction 15 emotions varies vas
Page 17 and 18: Introduction 17 Therefore, a precis
Page 19 and 20: Introduction 19 On the behavioural
Page 21 and 22: Introduction 21 A coherent model of
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Page 25 and 26: Introduction 25 Giegling, I., Hartm
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127 General Conclusion impact is si
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