Why Do Drivers Use Mobile Phones While Driving? The Contribution of Compensatory Beliefs

<div><p>The current study is the first to investigate the contribution of compensatory beliefs (i.e., the belief that the negative effects of an unsafe behavior can be "neutralized" by engaging in another safe behavior; e.g., "I can use a mobile phone now because I will slow down ") on drivers’ mobile phone use while driving. The effects of drivers’ personal characteristics on compensatory beliefs, mobile phone use and self-regulatory behaviors were also examined. A series of questions were administered to drivers, which included (1) personal measures, (2) scales that measured compensatory beliefs generally in substance use and with regard to driving safety, and (3) questions to measure drivers’ previous primary mobile phone usage and corresponding self-regulatory actions. Overall, drivers reported a low likelihood of compensatory beliefs, prior mobile phone use, and a strong frequency of self-regulatory behaviors. Respondents who had a higher tendency toward compensatory beliefs reported more incidents or crash involvement caused by making or answering calls and sending or reading messages. The findings provide strong support for the contribution of compensatory beliefs in predicting mobile phone usage in the context of driving. Compensatory beliefs can explain 41% and 43% of the variance in the active activities of making calls and texting/sending messages compared with 18% and 31% of the variance in the passive activities of answering calls and reading messages. Among the regression models for predicting self-regulatory behaviors at the tactical or operational level, compensatory beliefs emerge as significant predictors only in predicting shorter conversations while on a call. The findings and limitations of the current study are discussed.</p></div

Hierarchical regression analysis: predicting mobile phone usage while driving.

<p>Hierarchical regression analysis: predicting mobile phone usage while driving.</p

Descriptive statistics and zero-order correlations between the study variables.

<p>Descriptive statistics and zero-order correlations between the study variables.</p

Regression analysis: predicting self-regulatory behaviors.

<p>Regression analysis: predicting self-regulatory behaviors.</p