Online Program

328052
Drugged Driving and Traffic Safety Policies: A System Dynamics Framework


Monday, November 2, 2015

He Zhu, PhD, Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC
Ozgur Araz, Department of Health Promotion, Social, & Behavioral Health, University of Nebraska Medical Center, Omaha, NE
Fernando Wilson, PhD, College of Public Health, University of Nebraska Medical Center, Omaha, NE
Jim Stimpson, PhD, Health Services Research and Administration, University of Nebraska Medical Center, Omaha, NE
Li-Tzy Wu, SCD, Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC
Background:Driving under the influence of illicit drugs has become an urgent road safety and public health issue in the US. Limited research has been done to evaluate and predict the effect of traffic safety policies on reducing drugged driving and improving health outcomes.

Methods:Our study used a system dynamics (SD) approach to develop a model of drugged driving system, which is defined by determinants and interactions of the number of drugged drivers, roadway environmental factors, and intervention policies.

Results:Our simulation results suggest that implementing effective drugged driving laws (decreasing the prevalence of drugged driving) and public transportation policies (increasing public transit adequacy) reduce drug driving-related fatal crashes. Our experimental analyses showed that a 1% decrease in the prevalence of drugged driving due to the presence of a drugged driving law was associated with an extra 0.9 % reduction in drug-related fatally injured drivers (DFIDs), and annual 100 miles increase per capita resulting from a policy encouraging the use of public transportation led to about 80 decreases in DFIDs.

Conclusion: By recognizing complex interrelationships between drugged driving behavior, the policy environment, transportation modalities and other important factors, the SD model helps gauge the “real world” impact of policy interventions in ultimately improving roadway safety. Our SD model suggests that drugged driving laws are predicted to result in significant decreases in fatal crashes. Combining these laws with policies that encourage the use of public transportation may result in a further but modest reduction in decreasing drug driving-related crashes in an area.

Learning Areas:

Public health or related public policy
Systems thinking models (conceptual and theoretical models), applications related to public health

Learning Objectives:
Define a system dynamic model for drugged driving causes and consequences in the United States. Explore the complex interrelationships between drugged driving laws, public transportation, drug treatment, congestion, and other traffic-related factors.

Keyword(s): Drug Abuse Prevention and Safety, Policy/Policy Development

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am a PhD student in Health Services Research, Administration and Policy Program at College of Public Health, University of Nebraska Medical Center. I have been working on injury related researches, and published related articles.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

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