Complex monitoring and its relation to the classical problem of vigilance

Classical vigilance research has provided little insight into mechanisms responsible for complex monitoring performance. It has been unsuccessful both in establishing an appropriate data base for such behavior and in generating fruitful hypotheses. An empirical approach is therefore proposed in which variables contributing to task complexity are manipulated at a molar level, and those found to influence monitoring performance are subjected to progressive refinement. Three illustrative experiments are reported using a task designed to permit manipulation of a variety of complexity variables. Low frequency, high density, and irrelevant signals all were found to inhibit detection; in addition, sizable decrements occurred under some combinations of these conditions. Refinement of the density effect suggested that pattern of scanning, probably controlled by the reinforcing properties of detected signals, is of major importance in complex monitoring performance.