Literature DB >> 22269549

Differentiating risky and aggressive driving: further support of the internal validity of the Dula Dangerous Driving Index.

Isabelle Richer1, Jacques Bergeron.   

Abstract

The Dula Dangerous Driving Index (DDDI) is a cross-cultural validated instrument that measures simultaneously various manifestations of behaviours, cognitions, and affects associated with dangerous driving. The aims of the study were to translate the DDDI into French and then to verify the validity and reliability of the French version of the scale by means of observed behaviours on a driving simulator, and of self-reported measures of driving behaviours, personality and sociodemographic characteristics. A first sample of 395 drivers completed self-reported questionnaires and a second sample of 75 male drivers also completed tasks on a driving simulator. A confirmatory factorial analysis supported the internal validity of the scale. Findings also show that the French version of the DDDI yields good internal consistency, concomitant and convergent validity for each subscale (risky driving, negative cognitive/emotional driving and aggressive driving) and total score. The scale was useful to differentiate sociodemographic and psychological profiles associated with each subscale.
Copyright © 2011 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2011        PMID: 22269549     DOI: 10.1016/j.aap.2011.09.014

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  5 in total

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Journal:  Front Psychol       Date:  2017-05-11

2.  Psychosocial factors as predictors of risky driving behavior and accident involvement among drivers in Oromia Region, Ethiopia.

Authors:  Alemu Disassa; Habtamu Kebu
Journal:  Heliyon       Date:  2019-06-14

3.  Personality traits and risky behavior among motorcyclists: An exploratory study.

Authors:  Daniel Luiz Romero; Daniel Martins de Barros; Gabriel Okawa Belizario; Antonio de Pádua Serafim
Journal:  PLoS One       Date:  2019-12-05       Impact factor: 3.240

4.  Predicting Crashes Using Traffic Offences. A Meta-Analysis that Examines Potential Bias between Self-Report and Archival Data.

Authors:  Peter Barraclough; Anders Af Wåhlberg; James Freeman; Barry Watson; Angela Watson
Journal:  PLoS One       Date:  2016-04-29       Impact factor: 3.240

5.  Negativity Bias in Dangerous Drivers.

Authors:  Jing Chai; Weina Qu; Xianghong Sun; Kan Zhang; Yan Ge
Journal:  PLoS One       Date:  2016-01-14       Impact factor: 3.240

  5 in total

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