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. Study 1 (N = 290) examined whether an implicit measure of beliefs about past drunk driving (i.e., the Past Driving Under the Influence Implicit Association Test; P-DUI-IAT) retrospectively predicts drunk driving in driving school students, a population for which this measure could have applied value. Study 1 also explored whether P-DUI-IAT scores prospectively predicted drunk driving over six months. Due to the low number of offenders, however, Study 1 had low statistical power to test this latter question. In Study 2 (N = 228), we therefore examined the utility of the P-DUI-IAT and a new variant of this test (i.e., the Acceptability of Driving Under the Influence Implicit Association Test; A-DUI-IAT) to prospectively predict drunk driving in an online sample with a high number of offenders. Results from Study 1 show that the P-DUI-IAT predicts self-rated past drunk driving behavior in driving school students (ORs = 3.11-6.12, ps < .043, 95% CIs = [1.11, 37.69]). Results from Study 1 do not show evidence for utility of the P-DUI-IAT to prospectively predict self-rated drunk driving. Results from Study 2, on the other hand, show strong evidence for the utility of both implicit measures to prospectively predict self-rated drunk driving (ORs = 3.80-5.82, ps < .002, 95% CIs = [1.72, 14.47]). Although further applied research is necessary, the current results could provide a first step towards the application of implicit measures in real-world contexts.

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. Method: Study 1 examined the relation between evaluation (n = 58) and self-identification (n = 56) measures on the one hand and several self-report measures of social media use on the other hand. Study 2 examined whether the main results of Study 1 could be replicated and whether evaluation (n = 68) and self-identification (n = 48) also relate to actual social media use. We probed evaluation and self-identification using implicit and explicit measures. Results: Explicit evaluation and self-identification measures significantly correlated with several of the self-report measures of social media. Explicit evaluation also significantly correlated with several indices of actual social media use. Implicit measures did not relate to social media use. Discussion and conclusions: The current results suggest that researchers and practitioners could benefit from using explicit evaluation and self-identification measures when predicting social media use, especially an evaluation measure since this measure also seems to relate to actual social media use. Study 2 was one of the first to test the ecological validity of social media use measures. Although implicit measures could provide benefits for predicting social media use, the current studies did not show evidence for their predictive utility.

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. The use of implicit measures such as the Implicit Association Test (IAT) could overcome this problem because they are less controllable than self-reports and thus less susceptible to deception. However, previous studies have shown poor predictive utility of implicit measures for drunk driving behavior. The current studies aimed to test the predictive utility of a variant of the IAT designed to assess beliefs about past driving under the influence (the P-DUI-IAT). METHOD: Study 1 (N = 216) tested whether the P-DUI-IAT could predict self-reported prior drunk driving and future likelihood of drunk driving. We also examined incremental predictive validity of the P-DUI-IAT for these outcomes. Study 2 (N = 159) examined whether results from Study 1 were reproducible. RESULTS: In both studies, results showed that the P-DUI-IAT discriminated well between participants who had engaged in drunk driving and participants who had not. The P-DUI-IAT also showed independent and incremental predictive validity for past drunk driving and future likelihood of drunk driving. CONCLUSIONS: These studies provided initial evidence for the predictive utility of the P-DUI-IAT for drunk driving. PRACTICAL APPLICATIONS: The P-DUI-IAT is a promising tool for identifying which individuals are at risk of drunk driving. The application of this measure could especially be valuable for identifying young novice drivers at risk for drunk driving-related accidents.

Predicting nonsuicidal self-injury using a variant of the implicit association test.

OBJECTIVE: Nonsuicidal self-injury (NSSI) is a severe problem, and its prevalence is increasing. To aid prevention and treatment, there is an urgent need for evidence-based measures to identify individuals at risk for NSSI. Measures that probe past NSSI are most promising, but people are often motivated to conceal NSSI behavior. This problem can be overcome by using implicit measures, which do not require individuals to self-report on their behavior. Yet, prior research typically found weak predictive utility of implicit measures. Based on a new perspective on implicit measures and recent findings in NSSI research, we developed an Implicit Association Test that probes past NSSI (the P-NSSI-IAT). METHOD: We report two preregistered studies (N = 83; N = 372) in which we tested the utility of the P-NSSI-IAT to detect past NSSI and predict NSSI one month later. RESULTS: P-NSSI-IAT scores (a) differentiated injury groups from non-injury groups and (b) prospectively predicted NSSI and improved prediction above and beyond risk factors of NSSI. CONCLUSIONS: These initial findings suggest that the P-NSSI-IAT is a promising tool for NSSI risk assessment. Future studies should further examine the predictive utility of this newly developed measure for NSSI behavior.