ED Intervention to Reduce Risky Behaviors in Drivers

Disability and death from injury remain a persistent problem in the U.S. and risk-taking behaviors are known to contribute to injury. Healthy People 2010 set goals to reduce deaths caused by injury: "Motor vehicle crashes are often predictable and preventable. Increased use of seat belts and reductions in driving while impaired are two of the most effective means to reduce the risk of death and serious injury of occupants in motor vehicle crashes." One preventive strategy is to establish screening and intervention procedures that can be administered in the ED to young adults who have risky driving practices and problem drinking. Goal: The specific aim of this prospective, randomized controlled trial is to test the effectiveness of a brief intervention to limit risky driving behaviors (risky driving practices, lack of seat belt compliance) and problem drinking in drivers during an ED visit. In addition, the trial will result in a benefit-cost analysis from the perspectives of both society as a whole and hospitals in particular. Methods: Young adults 18 to 44 years will be screened for problem drinking and risky driving practices during an ED visit. Subjects who screen positive for problem drinking and risky driving will be randomized to one of three groups: No Contact Control Group (NCG: after informed consent, subjects receive no screening or intervention until 12 months after injury). Contact Control Group (CCG: subjects screened at baseline and every three months for 12 months but no intervention), and a Brief Intervention Group (BIG: subjects receive screening and brief intervention with data collection points every three months for 12 months). A total of 133 subjects per group (N=400) will be enrolled. The intervention will consist of a 20 minute nurse visit in the ED and a booster intervention at 7-10 days after ED discharge. All subjects will be telephoned at 3, 6, 9, and 12 months by interviewers blinded to condition. Outcomes of interest include reported alcohol use, risky driving behaviors, driving citations, adverse health outcomes, and costs (health care utilization, property damage, travel delays, lost work productivity, criminal justice expenses, and monetarized adverse health outcomes). Analysis: Power analysis suggests that 133 subjects in each arm of the trial will have sufficient power to detect a difference of the main outcome variables of interest. A variety of regression techniques, including individual growth curve modeling and event history analysis, will be used to test the proposed hypotheses.