A recent study has examined the factors that predict dangerous driving behaviour among individuals who predominantly use methamphetamine. The research, conducted by a team of scientists, aimed to explore the relationship between psychosocial characteristics, substance use patterns, and risky driving practices in this population.

Study Sample and Methodology

The study included 77 participants who reported predominant and sustained methamphetamine use (at least once per month for six months during their period of heaviest consumption). The sample had a mean age of 29.69 years (SD = 6.12, range = 20-48 years). Most participants (95%) held a current and valid full driver’s licence, while 5% had licences that were recently expired or revoked.

Key demographic information collected included age, gender, education level, employment status, and residential area. Substance use characteristics, including methamphetamine use patterns and alcohol consumption, were also assessed.

Methamphetamine Use Characteristics

The study revealed that:

– 90% of participants met the criteria for probable amphetamine dependence (Severity of Dependence Scale score ≥ 5)

– The mean age of first methamphetamine use was 23.3 years (SD = 5.2)

– 40.3% used methamphetamine 1-2 times per month at peak use

– 42.9% used weekly at peak use

– 16.9% used daily at peak use

– 75.3% reported injection as their primary mode of administration

Alcohol Use and Other Substance Use

The researchers found that:

– 75.3% of participants were classified as hazardous drinkers with potential dependence (AUDIT-C score ≥ 4 for men and ≥ 3 for women)

– 94.8% reported lifetime use of other illicit drugs

Dangerous Driving Behaviour

The study used the Dula Dangerous Driving Index (DDDI) to assess participants’ propensity to engage in dangerous driving behaviours. The DDDI comprises three subscales: Risky Driving, Negative Emotional Driving, and Aggressive Driving.

A one-way repeated measures ANOVA revealed significant differences between the subscales:

– Risky Driving: Mean score of 28.1 (SD = 8)

– Negative Emotional Driving: Mean score of 21.2 (SD = 5.7)

– Aggressive Driving: Mean score of 17.4 (SD = 5.5)

Predictors of Dangerous Driving

Using a best-possible subset’s regression model-selection procedure, the researchers identified three key predictors of dangerous driving behaviour:

1. Trait anger (measured by the STAXI-2)

2. Severity of methamphetamine dependence (SDS score)

3. Alcohol use (AUDIT-C score)

The final model accounted for 50% of the total variation in DDDI scores among drivers who use methamphetamine [F(3,74) = 26.06, p < .001, adjusted R² = 0.50].

Individual Predictor Effects

1. Trait anger: Strongest individual positive predictor (Cohen’s f² = 0.42, p < .001)

2. Alcohol use: Statistically significant but smaller effect (f² = 0.08, p < .05)

3. Severity of dependence: Smallest individual effect but still statistically significant (f² = 0.07, p < .05)

Implications and Discussion

The study suggests that pervasive negative emotional attributes, particularly trait anger, strongly predict the propensity to engage in dangerous driving behaviours among methamphetamine users. This effect was independent of substance use characteristics.

The researchers propose that the interaction between stable emotional factors and situational stressors may increase the likelihood of engaging in risky driving practices. They note that the DDDI scores reported by this sample (M = 66.60, SD = 16.97) were higher than those previously reported for other high-risk groups such as drunk drivers and speeding drivers.

The study also highlights the potential for targeted interventions focused on addressing negative emotionality and cognitive triggers for traffic-related stress. However, the researchers note that the efficacy of such interventions has not yet been examined specifically for substance-using populations who exhibit dangerous driving behaviours.

Limitations and Future Research

The study acknowledges several limitations, including:

– Reliance on self-reported data

– Relatively small sample size

– Lack of biological verification of substance use

– Limited assessment of other substance use patterns

The researchers suggest that future studies should aim to recruit larger cohorts, include additional measures of driving exposure, and incorporate complementary questionnaires to provide a more comprehensive understanding of dangerous driving behaviours in this population.

Source: Sciencedirect