Implementation of a graphical interface that facilitates user estimates of the relative contributions of organismic, environmental, and task constraints to optimal human performance: Application to track and field events.

摘要

Newell (1986) devised a model of human performance constraints that has been useful for practitioners in the field of exercise science. The model, which includes task, organismic, and environmental constraint categories, has been used to investigate topics in a wide range of disciplines. Despite the utility and popularity of Newell's model, no attempt has been made to transform the model from a black-and-white triangle diagram into an interactive, computer-based research tool. In this project, a user interface was developed that incorporated various colors, shapes, and sizes to depict the constraint categories of Newell's model. The interface, termed the Meyergram, was used to quantify the differences in users' estimates of the relative contributions of constraint categories to performance in four track and field event areas: sprint running, endurance running, throwing, and jumping. Participants included equal numbers of athletes from each event area, as well as a group of non-track athletes. Each participant indicated their confidence in their estimation of the contributions of constraints categories to optimal performance. Results showed that users estimated the organismic constraint to be the largest contributor to optimal performance in track and field events, with estimates typically near 50%. Users estimated that the environmental and task constraints contributed approximately 25% each to optimal performance in track and field events. Members of the track and field event groups had the largest confidence in their estimates of constraints for their own events, while non-track athletes had similar confidence levels across the events. The results of this study can be used as a baseline for future studies that use the constraints-based approach to human performance.