Driving anger: correlates and a test of state-trait theory

A survey and field study evaluated predictions from state-trait theory applied to driving anger. Trait driving anger, the propensity to become angry when driving, correlated positively with anger in frequently occurring driving situations and in day-to-day driving and with aggressive and risky behaviors while driving. Although not correlated with crash rates or moving violations, trait driving anger correlated with crash-related conditions such as loss concentration, loss of vehicular control, and close calls. Results generally supported predictions from state-trait theory and the construct validity of the Driving Anger Scale, as well as mapping correlates of the disposition to become angry while driving.     

The driving anger expression inventory: a measure of how people express their anger on the road

Four ways people express their anger when driving were identified. Verbal Aggressive Expression (alpha=0.88) assesses verbally aggressive expression of anger (e.g., yelling or cursing at another driver); Personal Physical Aggressive Expression (alpha=0.81), the ways the person uses him/herself to express anger (e.g., trying to get out and tell off or have a physical fight with another driver); Use of the Vehicle to Express Anger (alpha=0.86), the ways the person uses his/her vehicle to express anger (e.g., flashing lights at or cutting another driver off in anger); and Adaptive/Constructive Expression (alpha=0.90), the ways the person copes positively with anger (e.g., focuses on safe driving or tries to relax). Aggressive forms can be summed into Total Aggressive Expression Index (alpha=0.90). Aggressive forms of expression correlated positively with each other (rs=0.39-0.48), but were uncorrelated or correlated negatively with adaptive/constructive expression (rs=-0.02 to -0.22). Aggressive forms of anger expression correlated positively with driving-related anger, aggression, and risky behavior; adaptive/constructive expression tended to correlate negatively with these variables. Differences in the strengths of correlations and regression analyses supported discriminant and incremental validity and suggested forms of anger expression contributed differentially to understanding driving-related behaviors. Theoretical and treatment implications were explored.     

Facial aging, attractiveness, and distinctiveness.

A standard facial caricature algorithm has been applied to a three-dimensional (3-D) representation of human heads, those of Caucasian male and female young adults. Observers viewed unfamiliar faces at four levels of caricature--anticaricature, veridical, moderate caricature, and extreme caricature--and made ratings of attractiveness and distinctiveness (experiment 1) or learned to identify them (experiment 2). There were linear increases in perceived distinctiveness and linear decreases in perceived attractiveness as the degree of facial caricature (Euclidean distance from the average face in 3-D-grounded face space) increased. Observers learned to identify faces presented at either level of positive caricature more efficiently than they did with either uncaricatured or anticaricatured faces. Using the same faces, 3-D representation, and caricature levels, O'Toole, Vetter, Volz, and Salter (1997, Perception 26 719-732) had shown a linear increase in judgments of face age as a function of degree of caricature. Here it is concluded that older-appearing faces are less attractive, but more distinctive and memorable than younger-appearing faces, those closer to the average face.