Abstract
Sport teams work in complex environments in which each member’s tasks are mutually dependent on those of the others. To function effectively, expert teams generate Shared Mental Models (SMMs) to help adapt their own behavior to that of the others and master upcoming actions. Although SMMs have been discussed in domains such as organizations, there is still little research in the context of sport. One reason for this is that measurement methods have failed to incorporate the dynamic nature of the sport context. This study reports on the development of a video-based measurement of SMMs in tennis doubles. It examined the quality criteria first in a pilot and then in a main study. The final video-based measurement consists of 35 tennis doubles video clips requiring decisions on ball-taking behavior in two conditions (Self and Partner). In the condition Self, participants reported their own responses; in the condition Partner, those of their partner. The main study analyzed 29 male tennis teams with a mean age of 34.57 years (SD = 12.25) and a mean of 22.79 years (SD = 10.49) tennis experience. SMMs were analyzed for each partner as the inter-player agreement (Self–Partner) and averaged for each team. After completing the video-based measurement, participants filled out questionnaires on SMMs, team trust, and demographics. Results indicated that not only the split-half reliability (r = .49), the content validity (ηp2 = .23), the inter-player agreement (r = .63), and the inter-player agreement and accuracy (r = .61), but also the feasibility of the measurement were good. However, no relationships to the proposed convergent or criterial validity measures were found. In sum, measuring SMMs with a video-based test is possible and a promising method. No relationship to the frequently used questionnaires was found, suggesting that the two target different parts of SMMs. Future research should carefully examine and choose the appropriate measurement.
Funder
Deutsche Forschungsgemeinschaft
Publisher
Public Library of Science (PLoS)