Exposure to Movie Reckless Driving in Early Adolescence Predicts Reckless, but Not Inattentive Driving

Objective: We examine the association between exposure to depictions of reckless driving in movies and unsafe driving, modeling inattentive and reckless driving as separate outcomes. Methods: Data were obtained by telephone from 1,630 US adolescents aged 10 to 14 years at baseline who were drivers at a survey 6 years later. Exposure to movie reckless driving was measured based on movies seen from a randomly selected list of 50 movie titles that had been content coded for reckless driving among characters. Associations were tested with inattentive and reckless driving behaviors in the subsequent survey–controlling for baseline age, sex, socioeconomic status, parental education, school performance, extracurricular activities, daily television and video/computer game exposure, number of movies watched per week, self- regulation and sensation seeking. Results: Exposure to movie reckless driving was common, with approximately 10% of movie characters having driven recklessly. Confirmatory factor analysis revealed a significant distinction between items tapping reckless and inattentive driving at the 6 th wave. Age and exposure to movie reckless driving at baseline were directly associated with wave-6 reckless (but not inattentive) driving. Additionally, growth in sensation seeking mediated a prospective relation between the total number of movies watched per week at baseline and reckless driving, independent of exposure to movie reckless driving. Males and high sensation seekers reported lower seatbelt usage and more reckless driving, whereas lower self-regulation predicted inattentive driving. Discussion: In this study, exposure to movie reckless driving during early adolescence predicted adolescents’ reckless driving, suggesting a direct modeling effect. Other aspects of movies were also associated with reckless driving, with that association mediated through growth in sensation seeking. Predictors of reckless driving were different from predictors of inattentive driving, with lower self-regulation associated with the latter outcome. Making a clear distinction between interventions for reckless or inattentive driving seems crucial for accident prevention

Risky Choice in Virtual Reality Predicts Real-Life Risk-Taking Propensity

This dataset contains behavioral outcomes on risky decision making on a standard lottery task and on a virtual reality driving task. Most importantly, the number of risky choices on both tasks are entered for all participants. In addition, this dataset includes self-reports of real-life risk-taking propensity as measured by the Domain Specific Risk Taking Scale (DOSPERT

Social status determines how we monitor and evaluate our performance

Since people with low status are more likely to experience social evaluative threat and are therefore more inclined to monitor for these threats and inhibit approach behaviour, we expected that low-status subjects would be more engaged in evaluating their own performance, compared with high-status subjects. We created a highly salient social hierarchy based on the performance of a simple time estimation task. Subjects could achieve high, middle or low status while performing this task simultaneously with other two players who were either higher or lower in status. Subjects received feedback on their own performance, as well as on the performance of the other two players simultaneously. Electroencephalography (EEG) was recorded from all three participants. The results showed that medial frontal negativity (an event-related potential reflecting performance evaluation) was significantly enhanced for low-status subjects. Implications for status-related differences in goal-directed behaviour are discussed

Raw data for manuscript: Exposure to movie reckless driving in early adolescence predicts reckless, but not inattentive driving

<p>Data were obtained by telephone from 1,630 US adolescents aged 10 to 14 years at baseline who were drivers at a survey 6 years later. Exposure to movie reckless driving was measured based on movies seen from a randomly selected list of 50 movie titles that had been content coded for reckless driving among characters. Associations were tested with inattentive and reckless driving behaviors in the subsequent survey-- controlling for baseline age, sex, socioeconomic status, parental education, school performance, extracurricular activities, daily television and video/computer game exposure, number of movies watched per week, self-regulation and sensation seeking.</p

Description of analyses for the manuscript: Exposure to movie reckless driving in early adolescence predicts reckless, but not inattentive driving.

<p>A complete detailed report on the factor analysis and Structural Equation models of the manuscript: Exposure to movie reckless driving in early adolescence predicts reckless, but not inattentive driving.</p

Path diagram of structural equation model including direct and indirect effects.

<p>Numbers on pathways represent standardized effects; *.01<<i>p</i>< = 0.05, **.001<<i>p</i>< = 0.01, ***<i>p</i>< = 0.001.</p

Self reported unsafe driving behaviors at wave 6.

a<p>Refers to items that capture reckless driving.</p>b<p>Refers to items that capture inattentive driving.</p><p>Self reported unsafe driving behaviors at wave 6.</p

Odds Ratios for the indirect and double indirect effects of wave 1 high movie reckless driving exposure and sensation seeking (95th percentile) as compared to low movie reckless driving exposure and sensation seeking (5th percentile) on the separate wave 6 reckless driving items.

<p>w1  =  wave 1, OR  =  odds ratios, CI  =  confidence interval.</p><p>Odds Ratios for the indirect and double indirect effects of wave 1 high movie reckless driving exposure and sensation seeking (95th percentile) as compared to low movie reckless driving exposure and sensation seeking (5th percentile) on the separate wave 6 reckless driving items.</p