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Implicit attitudes towards risky driving: Development and validation of an affect misattribution procedure for
Andrei Rusu1, Paul Sârbescu1, Daniela Moza1
1West University of Timișoara, Romania.
Accident; Analysis and Prevention
|January 13, 2017
Summary
This study developed a reliable tool to measure implicit attitudes towards speeding using the Affect Misattribution Procedure (AMP). The Speeding-AMP effectively predicts driving violations and accidents, aiding research into risky driving behavior.
Area of Science:
- Psychology
- Traffic Safety Research
- Behavioral Science
Background:
- Measuring implicit attitudes towards speeding is crucial for understanding risky driving.
- Existing methods may not fully capture subconscious biases related to speeding behavior.
Purpose of the Study:
- To develop and validate a novel instrument for measuring implicit attitudes towards speeding.
- To assess the reliability and validity of the Affect Misattribution Procedure (AMP) for this purpose.
- To examine the predictive power of implicit attitudes for driving violations and accidents.
Main Methods:
- The study utilized the Affect Misattribution Procedure (AMP) to measure implicit attitudes.
- Data were collected from 140 drivers.
- Statistical analyses included reliability tests (Cronbach's alpha), construct validity (correlation with explicit attitudes), and criterion validity (predicting driving violations and accidents).
Main Results:
- The developed Speeding-AMP demonstrated good reliability (α=0.80).
- A moderate correlation (r=0.22) was found between implicit and explicit attitudes, supporting construct validity.
- The Speeding-AMP incrementally predicted driving violations (ΔR²=0.034) and traffic accidents (ΔR²=0.022) beyond demographic and explicit measures, supporting criterion validity.
Conclusions:
- The Speeding-AMP is a reliable and valid instrument for measuring implicit attitudes towards speeding.
- This tool can be effectively utilized in research on risky driving behavior.
- Implicit attitudes, as measured by Speeding-AMP, contribute to understanding the predictors of driving violations and accidents.
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