Personality has been found to be more strongly associated with subjective well-being in many instances than are life circumstances. In part, this might be due to the fact that temperament and other individual differences can influence people’s feelings and evaluations of their lives, but also because people’s emotions are an inherent part of personality. This chapter discusses the heritability of “happiness,” that portion of subjective well-being that is due to genetic differences between individuals. The stability of subjective well-being over time is substantial, and this is likely due in part to the stability of personality. Specific personality traits are related to various types of well-being. For example, extroversion appears to be more strongly related to positive emotions, while neuroticism is more related to negative feelings. Although personality is an important correlate of subjective well-being, situations and life circumstances can in some cases have a considerable influence as well. Furthermore, personality can to some degree change over time, and with it, levels of subjective well-being can change.

Personality and Subjective Well-Being

The Bell Curve: Intelligence and Class Structure in American Life.

Understanding subjective well-being (SWB) has historically been a core human endeavor and presently spans fields from management to mental health. Previous meta-analyses have indicated that personality traits are one of the best predictors. Still, these past results indicate only a moderate relationship, weaker than suggested by several lines of reasoning. This may be because of commensurability, where researchers have grouped together substantively disparate measures in their analyses. In this article, the authors review and address this problem directly, focusing on individual measures of personality (e.g., the Neuroticism-Extroversion-Openness Personality Inventory; P. T. Costa & R. R. McCrae, 1992) and categories of SWB (e.g., life satisfaction). In addition, the authors take a multivariate approach, assessing how much variance personality traits account for individually as well as together. Results indicate that different personality and SWB scales can be substantively different and that the relationship between the two is typically much larger (e.g., 4 times) than previous meta-analyses have indicated. Total SWB variance accounted for by personality can reach as high as 39% or 63% disattenuated. These results also speak to meta-analyses in general and the need to account for scale differences once a sufficient research base has been generated.

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Refining the relationship between personality and subjective well-being.

Personality may directly facilitate or constrain coping, but relations of personality to coping have been inconsistent across studies, suggesting a need for greater attention to methods and samples. This meta-analysis tested moderators of relations between Big Five personality traits and coping using 2,653 effect sizes drawn from 165 samples and 33,094 participants. Personality was weakly related to broad coping (e.g., Engagement or Disengagement), but all 5 traits predicted specific strategies. Extraversion and Conscientiousness predicted more problem-solving and cognitive restructuring, Neuroticism less. Neuroticism predicted problematic strategies like wishful thinking, withdrawal, and emotion-focused coping but, like Extraversion, also predicted support seeking. Personality more strongly predicted coping in young samples, stressed samples, and samples reporting dispositional rather than situation-specific coping. Daily versus retrospective coping reports and self-selected versus researcher-selected stressors also moderated relations between personality and coping. Cross-cultural differences were present, and ethnically diverse samples showed more protective effects of personality. Richer understanding of the role of personality in the coping process requires assessment of personality facets and specific coping strategies, use of laboratory and daily report studies, and multivariate analyses.

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Relations between personality and coping: a meta-analysis.

We quantitatively integrated 169 samples (N= 35,265 employees) that have been used to investigate the relationships of the following 7 work-related stressors with job performance: role ambiguity, role conflict, role overload, job insecurity, work–family conflict, environmental uncertainty, and situational constraints. Overall, we obtained a negative mean correlation between each job performance measure and each stressor included in our analyses. As hypothesized, role ambiguity and situational constraints were most strongly negatively related to performance, relative to the other work-related stressors. Analysis of moderators revealed that (a) the negative correlation of role overload and performance was higher among managers relative to nonmanagers; (b) publication year moderated the relation of role ambiguity and role overload with performance, although in opposite directions; (c) the correlations obtained for published versus unpublished studies were not significantly different; and (d) using the Rizzo et al. scale of role ambiguity and role conflict decreased the magnitude of the correlations of these stressors with performance, relative to other scales. Theoretical contributions, future research directions, and practical implications are discussed.

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A meta-analysis of work demand stressors and job performance: examining main and moderating effects

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.

Prediction of mood and risk appraisals from trait measures: Two studies of simulated driving

The drive to reduce fuel consumption and greenhouse gas emissions is one shared by both businesses and governments. Although many businesses in the European Union undertake interventions, such as driver training, there is relatively little research which has tested the efficacy of this approach and that which does exist has methodological limitations. One emerging technology employed to deliver eco-driving training is driver training using a simulator. The present study investigated whether bus drivers trained in eco-driving techniques were able to implement this learning in a simulator and whether this training would also transfer into the workplace. A total of 29 bus drivers attended an all-day eco-driving course and their driving was tested using a simulator both before and after the course. A further 18 bus drivers comprised the control group, and they attended first aid courses as well as completing the same simulator drives (before-after training). The bus drivers who were given the eco-driving training significantly improved fuel economy figures in the simulator, while there was no change in fuel economy for the control group. Actual fuel economy figures were also provided by the bus companies immediately before the training, immediately after the training and six months after the training. As expected there were no significant changes in fuel economy for the control group. However, fuel economy for the treatment group improved significantly immediately after the eco-driving training (11.6%) and this improvement was even larger six months after the training (16.9%). This study shows that simulator-based training in eco-driving techniques has the potential to significantly reduce fuel consumption and greenhouse gas emissions in the road transport sector.

Eco-driving training of professional bus drivers - Does it work?

Contents: Preface Part 1 The Novice Driver Problem: How do 'significant others' influence young people's beliefs about driving?, Amanda Green and Lisa Dorn Piloting a telemetric data tracking system to assess post-training real driving performance of young novice drivers, Robert B. Isler, Nicola J. Starkey, Peter Sheppard and Chris Yu Fault correction or self-assessment. Which way forward?, Ian Edwards and Tracey Curle New elements in the Dutch practical driving test a pilot study, Jan Vissers, Jolieke Mesken, Erik Roelofs and Rene Claesen Personality and attitudinal predictors of traffic offences among young drivers: a prospective analysis, Lisa Wundersitz and Nicholas Burns Pre-driving attitudes and non-driving road user behaviours: does the past predict future driving behaviour?, Helen N. Mann and Mark J.M. Sullman Prediction of problem driving risk in novice drivers in Ontario: part II outcome at 2 years, Laurence Jerome and Al Segal. Part 2 Emotions and Driver Behaviour: A review of studies on emotions and road user behaviour, Jolieke Mesken, Marjan Hagenzieker and Talib Rothengatter A comparison of the propensity for angry driving scale and the short driving anger scale, Mark J.M. Sullman Aggression and non-aggression amongst 6 types of drivers, Evelyne F. Vallieres, Pierre McDuff, Robert J. Vallerand and Jacques Bergeron The influence of age differences on coping style and driver behaviour, Elizabeth Andrews and Stephen Westerman. Part 3 At Work Road Safety: Effects of organisational safety culture on driver behaviours and accident involvement amongst professional drivers, Bahar Oz and Timo Lajunen Stages of change in the Australian workplace and its application to driver education, Tamara Banks, Jeremy Davey and H. Biggs Prospective relationships between physical activity, 'need for recovery', and driver accidents and absenteeism, Adrian Taylor and Lisa Dorn Predicting high risk behaviours in a fleet setting: implications and difficulties utilising behaviour measurement tools, Jeremy Davey, James Freeman and Darren Wishart Driver celeration behaviour in training and regular driving, Anders af Wahlberg and Lennart Melin A study of contemporary modifications to the Manchester driver behaviour questionnaire for organisational fleet settings, James Freeman, Jeremy Davey and Darren Wishart A comparison of seat belt use between work time and free time driving among Turkish taxi drivers, Ozlem Simsekoglu and T. Lajunen A review of developing and implementing Australian fleet safety interventions: a case study approach update, Darren Wishart, Jeremy Davey and James Freeman Designing a psychometrically based self-assessment to address fleet driver risk, Lisa Dorn and Julie Gandolfi. Part 4 Technological Interventions, Driver Behaviour and Road Safety: Development of multimedia tests for responsive driving, Erik Roelofs, Marieke van Onna, Reinoud Nagele, Jolieke Mesken, Maria Kuiken and Esther Cozijnsen The effect of simulation training on novice driver accident rates, R. Wade Allen, George D. Park and Marcia L. Cook Driving experience and simulation of accident scenarios, Catherine Berthelon, Claudine Nachtergaele and Isabelle Aillerie Investigating the contexts in which in-vehicle navigation system users have received and followed inaccurate route guidance instructions, Nick Forbes and Gary Burnett Comparison of novice drivers in Austria and the Czech Republic with and without the use of intelligent speed adaptation, Christine Turetschek and Ralf Risser. Part 5 Human Factors and the Road Environment: What factors are involved in crashes, how do we measure them and what shall we do about them?, Frank McKenna Driver training and assessment: implications of the task-difficulty homeostasis model, Ray Fuller Do we really drive by the seat of our pants?, Neale Kinnear, Steve Stradling and Cynthia McVey The impact of subjective factors on driver vigilance: a driving simulator study, Jeremy Vrignon, Andry Rakotonirainy, Dominique Gruyer and Guillaume Saint Pierre The use of local case review panels to determine contributory factors crash data, Peter Hillard, David Logan and Brian Fildes The effectiveness of new seat belt legislation in Northern Ireland, A.R. Woodside, J.R. Seymour and C. Gallagher. Part 6 Rider Behaviour: An evaluation of the Portuguese moped rider training programme, Patricia Antonio and M. Matos Flow, task capability and powered 2-wheeler (PTW) rider training, Paul Broughton Understanding inappropriate high speed by motorcyclists: a qualitative analysis, Barbara Hannigan, Ray Fuller, H.Bates, Martin Gormley, Steve Stradling, Paul Broughton, Neale Kinnear and C. O'Dolan Index.

Lisa Dorn

Papers

Prediction of mood and risk appraisals from trait measures: Two studies of simulated driving

Eco-driving training of professional bus drivers - Does it work?

Driver Behaviour and Training

Culpable versus non-culpable traffic accidents; what is wrong with this picture?

Two further studies of personality correlates of driver stress