Jaimie McNabb’s research while affiliated with Arizona State University and other places

A novel joint decision making paradigm for assessing team coordination was developed and tested using baseball infielders. Balls launched onto an infield at different trajectories were filmed using four video cameras that were each placed at one of the typical positions of the four infielders. Each participant viewed temporally occluded videos for one of the four positions and were asked to say either “ball” if they would attempt to field it or the name of the bag that they would cover. The evaluation of two experienced coaches was used to assign a group coordination score for each trajectory and group decision times were calculated. Thirty groups of 4 current college baseball players were: (i) teammates (players from same team/view from own position), (ii) non-teammates (players from different teams/view from own position), or (iii) scrambled teammates (players from same team/view not from own position). Teammates performed significantly better (i.e., faster and more coordinated decisions) than the other two groups, whereas scrambled teammates performed significantly better than non-teammates. These findings suggest that team coordination is achieved through both experience with one’s teammates’ responses to particular events (e.g., a ball hit up the middle) and one’s own general action capabilities (e.g., running speed). The sensitivity of our joint decision making paradigm to group makeup provides support for its use as a method for studying team coordination.

Previous research examining social influences on driving behavior has primarily focused on the effects of passengers and surrounding vehicles (e.g., speed contagion). Of current interest was the interaction between drivers that occurs in a “following a friend” scenario, i.e., the driver of one vehicle (the leader) knows how to get to the desired destination while the driver of a second vehicle (the follower) does not. Sixteen participants drove through a simulated city in a driving simulator under three conditions: (i) a baseline condition in which they could choose their own route, (ii) a navigation system condition in which they were given audible route instructions, and (iii) a “follow a friend” condition in which they required to follow a simulated vehicle. In the follow a friend condition, drivers engaged in significantly more risky behaviors (in comparison to the other conditions) such as making more erratic and higher speed turns and lane changes, maintaining overall higher speed, as well as maintaining a shorter time headway when following a lead vehicle. These effects suggest a relationship to time pressure caused by a fear of getting lost.

Previous research on smart phone use while driving has primarily focused on phone calls and texting. Drivers are now increasingly using their phone for other activities during driving, in particular social media, which have different cognitive demands. The present study compared the effects of four different smart phone tasks on car-following performance in a driving simulator. Phone tasks were chosen that vary across two factors: interaction medium (text vs image) and task pacing (self-paced vs experimenter-paced) and were as follows: Text messaging with the experimenter (text/other-paced), reading Facebook posts (text/self-paced), exchanging photos with the experimenter via Snapchat (image, experimenter -paced), and viewing updates on Instagram (image, experimenter -paced). Drivers also performed a driving only baseline. Brake reaction times (BRTs) were significantly greater in the text-based conditions (Mean = 1.16 s) as compared to both the image-based conditions (Mean = 0.92 s) and the baseline (0.88 s). There was no significant difference between BRTs in the image-based and baseline conditions and there was no significant effect of task-pacing. Similar results were obtained for Time Headway variability. These results are consistent with the picture superiority effect found in memory research and suggest that image-based interfaces could provide safer ways to "stay connected" while driving than text-based interfaces.

Driving Performance Data. (DOCX)