With the ever increasing amount of information available, the ability to prioritize the most relevant items for full processing is increasingly necessary to maintain expertise in a domain. As a result, accurate triage decisions--initial decisions about the relevance of a given article, book, or talk in order to determine whether to pursue that information further--are very important. In the present paper, we present a model of triage decision making that includes both an information search component to determine reading strategy and a decision making component to make the final decision. We apply the model to human relevance ratings as well as binary decisions of relevance for a set of emails.

Predictions about information search behavior have been informed by extensive research in food foraging behavior. However, information foraging environments may differ in key ways from food foraging environments, and these differences may impact search behavior. We investigated the effect of patch distribution (depleting or non-depleting) and ability to return to previously searched patches on participants’ decision to switch from one patch to another while searching. Whether or not a participant could return after leaving a patch led to fewer samples and fewer relevant items found. Whether or not the patches depleted and whether it was possible to return to a patch influenced stopping rules, indicating that these factors may alter the size of the increment applied through the Incremental Rule.