Transportation Research Part F: Traffic Psychology and Behaviour
Validation of the German version of the Driver Skill Inventory (DSI) and the Driver Social Desirability Scales (DSDS)
Introduction
Traffic accidents are one of the most frequent causes of death in Germany. In 2012, 2,401,843 accidents occurred in Germany in which 299,637 people were injured, 3600 of whom died. Even though the number of injuries and casualties caused by traffic accidents has decreased since 1970, when 377,610 people were injured and 19,193 died, the total number of accidents on German roads has actually increased in the past few decades (German Federal Agency for Statistics, 2013). Given that traffic accidents give rise to substantial human distress and economic costs, it is particularly alarming that approximately 85–90% of road-traffic crashes are caused by driver error and could be prevented by more appropriate driving behavior (Lewin, 1982). Earlier studies have tried to detect an accident-prone personality (e.g., Elander et al., 1993, Harano et al., 1975). Nowadays, researchers consider both general factors, e.g., personality traits, and specific driving behavior factors, e.g., driving styles. The development of suitable standardized instruments is essential for this approach. Self-report measures, however, are prone to socially desirable responding (SDR). In the present study, we therefore translated an internationally wide-spread traffic behavior inventory as well as a driving specific SDR scale and submitted both measures to validation in two large samples of German drivers.
Section snippets
Driving-specific behavior factors: Concepts, measurement and correlates
In spite of the agreement on the importance of traffic-specific human factors, there is little agreement on their conceptualization (Taubman-Ben-Ari, Mikulincer, & Gillath, 2004). Two traffic-specific human factors, however, are believed to explain a large portion of individual differences in driving: driving skills and driving styles (Elander et al., 1993, Taubman-Ben-Ari et al., 2004). These two dimensions have repeatedly been shown to be associated with a variety of personality
Statistical analysis
Data were analyzed using SPSS 23 and Statistica 8. To examine the factorial structure of the German versions of the DSI and DSDS, we conducted confirmatory factor analyses using maximum likelihood estimates. Both for the DSI and the DSDS, we assumed two correlated latent dimensions with correlated residuals. Apart from the χ2-test, which is known to be overly sensitive when sample size is large, we adopted the widely accepted cutoff criteria proposed by Hu and Bentler (1999) to assess model
Participants
Study 1 was comprised of 130 drivers (82% female), most of whom were psychology students (90%) who received course credit for participation. The participants ranged in age from 18 to 59 years (M = 24.76, SD = 8.27) and had held a driver’s license for a mean period of 6.41 years (SD = 7.91). Their mean lifetime mileage was 58930.08 km (SD = 119961.79). Other-reports were provided for 84 respondents by close confidants, mostly partners (45.2%), friends (15.5%), and relatives (10.7%) who knew the interviewee
Participants
Participants were 1356 registered users of an online panel who had previously agreed to participate in exchange for a financial incentive of about 0.25 €. We excluded 157 respondents who either did not complete the survey or omitted more than 10% of the items. Of the remaining 1199 participants, 49% were female. The participants’ ages ranged from 30 to 60 years (M = 42.17, SD = 7.67). Their mean duration of license possession was 21.99 years (SD = 8.30), and their mean lifetime mileage was 465589.28 (SD
General results
In a final step, we conducted multiple linear regressions to determine the relative importance of the predictors of both motor skills and the safety motive. To this end, we collapsed participants across the two samples (N = 1324; the smaller sample size was due to missing data for some participants). The BSRS scores were z-standardized to account for the different scoring procedures used for the paper-pencil and online versions of this scale.
For the DSI safety motive, the resulting model (F
General discussion
The present work examined the psychometric properties of a newly developed German version of the DSI (Lajunen & Summala, 1995) and the DSDS (Lajunen et al., 1997). We applied both scales in a small sample of younger drivers and replicated the results in a larger sample of older, experienced drivers. Various demographic, driving-related, and personality measures were used as validation criteria. In addition, other-reported data were collected for a subsample of the participants in Study 1. The
Conclusions
In sum, the German DSI and DSDS were able to reliably distinguish between two important dimensions of driving behavior and driving-specific SDR, respectively (Elander et al., 1993, Lajunen and Summala, 1995, Lajunen et al., 1997, Paulhus, 1998). Both inventories showed good psychometric properties comparable to the Finnish originals and their various adaptations and are therefore ready to be used in both basic personality and applied traffic research.
Acknowledgments
We would like to thank Martin Baumann for providing a preliminary German version of the traffic behavior inventories, Helen-Rose Cleveland for translating the original questionnaires, and Morten Moshagen for his help with programming Study 2.
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