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Published on: January 5, 2018
Trait anger as a predictor of dangerous driving behaviour amongst people who use methamphetamine
Aaron Mackay1, Luke A Downey2, Shalini Arunogiri3
1Centre for Mental Health and Brain Sciences, Swinburne University of Technology, Hawthorn, Australia.
Introduction:
Despite increased prevalence of methamphetamine in road trauma, it remains unclear how its use translates to an increased risk of traffic-related harm. Exploration of psychosocial factors may thus help identify relevant predictors of dangerous driving behaviour among people who regularly consume methamphetamine.
Methods:
Licenced individuals who report predominant and sustained methamphetamine use (at least 1-time/month for 6 months at heaviest use) were recruited from the Australian community and via targeted campaign (Eastern Health). Psychosocial, substance use and driving behaviour data (Dula Dangerous Driving Index, DDDI) were collected via a secure anonymous online forced-entry survey platform (Qualtrics).
Results:
Seventy-seven individuals (65.5 % male) aged between 20-50 years [mean = 29.7, ± Standard Deviation (SD) 6.1] were included. Most (90 %) respondents met criteria for problematic methamphetamine use [Severity of Dependency Scale (SDS) score ≥ 5], and 75 % were high-risk alcohol consumers [Alcohol Use Disorders Identification Test (AUDIT-C) score ≥ 4 for men and ≥ 3 for women]. On average, age of first methamphetamine use occurred at 23.3 years (±5.2). A best-possible subset's regression selection method with dangerous driving behaviour as the dependent variable determined the model with three predictors (alcohol use, substance dependence severity and trait anger) as most parsimonious. After controlling for substance use, trait anger strongly and positively predicted dangerous driving behaviour as measured by the DDDI ([F(3,74) = 26.06, p < .001, adjusted R2 = 0.50, Cohens f2 = 0.42).
Discussion And Conclusions:
Trait anger is a strong predictor of risky driving among road users who use methamphetamine. Interactions between stable negative-emotional and situational traffic and driving-related factors may increase risk of harm through greater engagement in risk-taking behaviour.
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