Literature DB >> 25000297

The prosocial and aggressive driving inventory (PADI): a self-report measure of safe and unsafe driving behaviors.

Paul B Harris1, John M Houston2, Jose A Vazquez3, Janan A Smither3, Amanda Harms4, Jeffrey A Dahlke4, Daniel A Sachau4.   

Abstract

Surveys of 1217 undergraduate students supported the reliability (inter-item and test-retest) and validity of the Prosocial and Aggressive Driving Inventory (PADI). Principal component analyses on the PADI items yielded two scales: Prosocial Driving (17 items) and Aggressive Driving (12 items). Prosocial Driving was associated with fewer reported traffic accidents and violations, with participants who were older and female, and with lower Boredom Susceptibility and Hostility scores, and higher scores on Agreeableness, Conscientiousness, Openness, and Neuroticism. Aggressive Driving was associated with more frequent traffic violations, with female participants, and with higher scores on Competitiveness, Sensation Seeking, Hostility, and Extraversion, and lower scores on Conscientiousness, Agreeableness, and Openness. The theoretical and practical implications of the PADI's dual focus on safe and unsafe driving are discussed.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Aggressive driving; Driver safety; Five Factor Model; Prosocial driving

Mesh:

Year:  2014        PMID: 25000297     DOI: 10.1016/j.aap.2014.05.023

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


  3 in total

1.  A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms.

Authors:  Gys Albertus Marthinus Meiring; Hermanus Carel Myburgh
Journal:  Sensors (Basel)       Date:  2015-12-04       Impact factor: 3.576

2.  The relationship between personalities and self-report positive driving behavior in a Chinese sample.

Authors:  Biying Shen; Weina Qu; Yan Ge; Xianghong Sun; Kan Zhang
Journal:  PLoS One       Date:  2018-01-11       Impact factor: 3.240

3.  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

  3 in total

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