Theses and Dissertations at Montana State University (MSU)
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Item Emotional intelligence and dangerous driving behaviors(Montana State University - Bozeman, College of Engineering, 2022) Ahmed, Jubaer; Chairperson, Graduate Committee: Nicholas Ward; Nicholas Ward, Jay Otto and Annmarie McMahill were co-authors of the article, 'How does emotional intelligence predict driving behaviors among non-commercial drivers?' in the journal 'Journal of transportation research part F: psychology and behaviour' which is contained within this dissertation.; Nicholas Ward, Jay Otto and Annmarie McMahill were co-authors of the article, 'The influence of emotional intelligence on dangerous driving: a comparison between commercial and non-commercial drivers' submitted to the journal 'Journal of safety science' which is contained within this dissertation.; Nicholas Ward, Jay Otto and Annmarie McMahill were co-authors of the article, 'Developing a scale to assess emotional intelligence in the context of driving' submitted to the journal 'Journal of personality assessment' which is contained within this dissertation.Dangerous driving behaviors are the leading cause of road crashes and fatalities. Many factors contribute to dangerous driving behaviors including drivers' beliefs, attitudes, personalities, and emotions. Of these, the role of emotions has received less attention. Emotional Intelligence theory provides a framework for understanding how individuals' emotional factors influence their behaviors and interactions with others. Therefore, this research aims to understand how emotional intelligence can be used to investigate and alleviate dangerous driving behaviors. The research aims of this dissertation include 1. Identify the most appropriate measure of emotional intelligence that is currently available for the driving context; 2. Examine the correlations between emotional intelligence and dangerous driving behaviors in different risk exposure groups (commercial and non-commercial drivers); 3. Develop an emotional intelligence measure specific to the context of driving. This research dissertation comprised four survey studies conducted between November 2019 to July 2021 among commercial and non-commercial drivers across the United States. The results further revealed higher emotional intelligence scores related to less dangerous driving behaviors for both commercial and non-commercial drivers. However, the relationship between emotional intelligence and dangerous driving was significantly stronger among commercial drivers than their non-commercial counterparts. In the final study, this research developed a new Drivers' Emotional Intelligence Scale (DEIS) specific to driving. Factor analysis revealed a three-factor structure for DEIS labeled as emotionality, self-control, and anxiety. The results showed that the DEIS subscales were stronger predictors of dangerous driving behaviors compared to the previously used emotional intelligence scales. This research concludes that improving emotional intelligence will be useful to reduce dangerous driving behaviors and suggests incorporating emotional intelligence to design interventions to reduce fatal road crashes. This research acknowledges some limitations such as the use of self-reported surveys and convenience quota samples, which may have limited the generalizability of these results. Future research should continue to gather evidence about the association between emotional intelligence and traffic safety through different experimental designs and longitudinal studies.Item The effects of message threat/reflection on psychological reactance in traffic safety messaging(Montana State University - Bozeman, College of Engineering, 2020) Townsend, Asher Campbell; Chairperson, Graduate Committee: Nicholas WardPsychological reactance is a motivation to regain a freedom after it has been lost or threatened, which has led people to largely resist the social influence of others (Steindl et al., 2015). Steindl et al. (2015, pg. 205) also define psychological reactance as 'an unpleasant motivational arousal that emerges when people experience a threat to or loss of their free behaviors.' Seat belt use and distracted driving are two of the highest-fatality behaviors and they pose the greatest threat to other drivers' health and safety on U.S. roadways (NHTSA, 2018a). The purpose of this research is to investigate whether psychological reactance may be a significant factor in influencing people's reactions and their choices to continually engage in risky behaviors. Moreover, this research looks at whether select individuals are more prone to experiencing reactance and how it may influence their willingness to follow driver safety messaging. Specifically, this research will investigate whether varying message threat and message reflection influence the amount of reactance experienced. Three main components of psychological reactance are of concern in the study: Reactance Attitude, Emotional Reactance, and Threat to Freedom. Each of these behaviors is measured for varying message conditions for two different message sets: one for Seat Belt Use and another for Distracted Driving. For the Emotional Reactance and Threat to Freedom reactance measures, there is a significant correlation between the measures and reactance proneness. It was found that as proneness increases, the resulting psychological reactance increases as well. For the Distracted Driving messages, there was a significant effect of Message Threat for the Emotional Reactance and Threat to Freedom conditions such that low threat messages elicited less psychological reactance than high threat messages. From this study, we recommend the following aspects for designing traffic safety messages: 1) Messages should use non-controlling language (consider, can, could, may, try) over controlling language (should, ought, must, need), 2) Messages should aim to be suggesting (try to do this), rather than commanding (you MUST do this!). Additionally, high threat messages may tend to elicit stronger reactance independent of reactance proneness, supporting the proposal of avoiding high threat messages for traffic safety.Item An analysis of road traffic factors and road safety strategies that predict road fatalities over time across fifty states in USA(Montana State University - Bozeman, College of Engineering, 2017) Benzaman; Chairperson, Graduate Committee: Nicholas WardStrategizing to decrease statewide road fatalities is an important aspect in road safety research in the United States. But obtaining information on a variety of variables, such as economic, socio-cultural, demographic and political factors, at the state level can be a difficult task. The public databases sometimes do not provide full information on these variables due to missing data. If these variables are neglected from the analysis because of missing data points. valuable information is lost in the process. Therefore, analyzing missing data has been considered as an additional step towards variable selection process in this thesis study. In order to impute the missing data, multiple imputation method was chosen. After the data imputation, the significant variables associated with road fatalities in 50 states were identified. This was done using a linear regression model which revealed that the top reasons for road fatalities are drunk driving, distracted driving and unemployment. In the process of linear regression modelling 48 predictive models were obtained. During the process of data collection, it was observed that data sources did not offer necessary information on road safety culture, behaviors, norms, attitudes and beliefs related to road fatality. This study offers two solutions for inferring a road safety culture and understanding its effects. The first solution was to analyze residuals from random effects two-way panel regression model and to generate performance indicator of inferred road safety culture. From the value of the indicators it was clear which state was the safest twenty years ago and which state is the safest now. Through the change in the value of the indicator, a state's progress in terms of safety culture was also measured. The second solution was to use people's political views on the democratic party and the republican party as a proxy for the road safety culture. This resulted in a significant increase in the goodness of fit for the linear regression model. This thesis provides prediction models, significant factors, and performance indicators of a road safety culture which can be used in state level road safety strategy development and policy making.