Work

Examination of a Dual‐Process Model Predicting Riding with Drinking Drivers

Year: 2015

Type: article

Abstract: BACKGROUND: Nearly 1 in 5 of the fatalities in alcohol-related crashes are passengers. Few studies have utilized theory to examine modifiable psychosocial predictors of individuals' tendencies to be a passenger in a vehicle operated by a driver who has consumed alcohol. This study used a prospective design to test a dual-process model featuring reasoned and reactive psychological influences and psychosocial constructs as predictors of riding with drinking drivers (RWDD) in a sample of individuals aged 18 to 21. METHODS: College students (N = 508) completed web-based questionnaires assessing RWDD, psychosocial constructs (attitudes, expectancies, and norms), and reasoned and reactive influences (intentions and willingness) at baseline (the middle of the spring semester) and again 1 and 6 months later. Regression was used to analyze reasoned and reactive influences as proximal predictors of RWDD at the 6-month follow-up. Subsequent analyses examined the relationship between the psychosocial constructs as distal predictors of RWDD and the mediation effects of reasoned and reactive influences. RESULTS: Both reasoned and reactive influences predicted RWDD, while only the reactive influence had a significant unique effect. Reactive influences significantly mediated the effects of peer norms, attitudes, and drinking influences on RWDD. Nearly all effects were constant across gender except parental norms (significant for females). CONCLUSIONS: Findings highlight that the important precursors of RWDD were reactive influences, attitudes, and peer and parent norms. These findings suggest several intervention methods, specifically normative feedback interventions, parent-based interventions, and brief motivational interviewing, may be particularly beneficial in reducing RWDD.

Source: Alcoholism Clinical and Experimental Research

DOI: 10.1111/acer.12731

Authors: Brittney A. Hultgren, Nichole M. Scaglione, Michael J. Cleveland, Rob Turrisi

Institution: Pennsylvania State University

Language: English

Topic: Traffic and Road Safety

Subfield: Safety, Risk, Reliability and Quality

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funder: National Institute on Alcohol Abuse and Alcoholism