Effect of baseline self-efficacy on physical activity and psychological stress after a one-week pedometer intervention

Physical activity and psychological stress were hypothesized to improve more in participants with high self-efficacy than in those with low and medium self-efficacy after a one-week intervention. 39 female university students participated. The intervention had two steps: a lecture on self-monitoring and goal setting (160 min.) and a one-week pedometer intervention. Analyses were conducted on tertile groups according to self-efficacy at baseline. Pedometer step counts were higher in the high self-efficacy group than in the low self-efficacy group after intervention. Helplessness decreased time dependently after intervention only in the high-self-efficacy group. Because physical activity improved more in the high self-efficacy group after a one-week intervention, one hypothesis was supported.     

Modeling and prediction of driver preparations for making a right turn based on vehicle velocity and traffic conditions while approaching an intersection

This paper focuses on modeling and predicting the influence of a vehicle’s velocity and the relative position between a driver’s vehicle and a vehicle to the front or rear on the onset of driver preparations for making a right turn at an intersection. Repeated experiments were carried out on a public road to measure driver preparations, including releasing the accelerator pedal, moving the right foot to cover the brake pedal, and activating the turn signal, as well as to record vehicle velocity and the relative distances to the leading and following vehicles. Structural equation modeling was applied to estimate these relationships quantitatively. Two separate latent variables accounting for the interaction between the driver’s vehicle and leading or following vehicles, and the onset point where driving behavior changes from straight mode to preparation mode before a right turn, were introduced in the specification of the structural equation model. The model estimates and testing indicate that the proposed structural equation model represents well the relationship hypothesized by observational analysis: that the vehicle velocity and the traffic conditions surrounding the driver’s vehicle strongly influence the driver’s deceleration and more weakly influenced turn signal activation. The proposed structural equation model contributes to the prediction of the onset locations of covering the brake pedal and activating the turn signal based on the vehicle velocity and the relative distances to the front and rear vehicles when the accelerator pedal is released. The prediction accuracy is high compared with predictions in which the vehicle velocity and the headway or rear distances are not taken into account or predictions using a single regression model with one independent variable, namely driving speed. Finally, a possible new addition to in-vehicle navigation systems that detects unusual driver behavior by predicting the driver’s preparatory maneuvers is discussed.     

Correlations for Adolescent Resilience Scale with big five personality traits

Currently, individuals tend to encounter many unavoidable, painful events and hardships in the process of growth and development. To lead one's life adapting to these social conditions, it is necessary to maintain one's mental health even while experiencing challenging events; in other words, resilience is required. This study of 130 undergraduates focused on the Adolescent Resilience Scale which assesses capacity for successful adaptation despite challenging or threatening circumstances and examined correlations with scores on the Big Five Personality Inventory. A significant negative correlation of -.59 (p<.001) was noted for scores on the Adolescent Resilience Scale and the Neuroticism dimension of the Big Five Personality Inventory, accounting for 35% of the variance, and positive values with the Extraversion, Openness, and Conscientiousness dimensions (rs= .37, .40, .48, accounting for 14, 16, and 18% of the variance, respectively. Personalities of adolescents who have psychological traits leading to resilience may be partially predicted using these results.     

Should Candidates Smile to Win Elections? An Application of Automated Face Recognition Technology

Previous studies examining whether the faces of candidates affect election outcomes commonly measure study participants' subjective judgment of various characteristics of candidates, which participants infer based solely on the photographic images of candidates. We, instead, develop a smile index of such images objectively with automated face‐recognition technology. The advantage of applying this new technology is that the automated process of measuring facial traits is by design independent of voters' subjective evaluations of candidate attributes, based on the images, and thus allows us to estimate “undiluted” effects of facial appearance per se on election outcomes. The results of regression analysis using Japanese and Australian data show that the smile index has statistically significant and substantial effects on the vote share of candidates even after controlling for other covariates.