Testing the practical utility of implicit measures of beliefs for predicting drunk driving.

Despite the potential benefits of implicit measures over self-report measures, they are rarely used in real-world contexts to predict behavior. Two potential reasons are that (a) traditional implicit measures typically show low predictive validity and (b) the practical utility of implicit measures has hardly been investigated. The current studies test the practical utility of a new generation of implicit measures for predicting drunk driving.

Do evaluation and self-identification relate to self-reported and actual social media use?

Background And Aims: Social media use can sometimes become excessive and damaging. To deal with this issue, scholars and practitioners have called for the development of measures that predict social media use. The current studies test the utility of evaluation and self-identification measures for predicting social media use.

Predicting drunk driving using a variant of the implicit association test.

Introduction: Drunk driving is one of the primary causes of road traffic injuries and fatalities. A possible approach to reduce drunk driving rates is to identify which individuals are at risk of such behavior and establish targeted prevention. Simply asking individuals about drunk driving in real-world contexts would be problematic because of potential deception.