All Signals Go: Investigating How Individual Differences Affect Performance on a Medical Diagnosis Task Designed to Parallel a Signal Intelligence Analyst Task

Signals intelligence analysts play a critical role in the United States government by providing information regarding potential national security threats to government leaders. Analysts perform complex decision-making tasks that involve gathering, sorting, and analyzing information. The current study evaluated how individual differences and training influence performance on an Internet search-based medical diagnosis task designed to simulate a signals analyst task. The implemented training emphasized the extraction and organization of relevant information and deductive reasoning. The individual differences of interest included working memory capacity and previous experience with elements of the task, specifically health literacy, prior experience using the Internet, and prior experience conducting Internet searches. Preliminary results indicated that the implemented training did not significantly affect performance, however, working memory significantly predicted performance on the implemented task. These results support previous research and provide additional evidence that working memory capacity influences performance on cognitively complex decision-making tasks, whereas experience with elements of the task may not. These findings suggest that working memory capacity should be considered when screening individuals for signals intelligence positions. Future research should aim to generalize these findings within a broader sample, and ideally utilize a task that directly replicates those performed by signals analysts.