An operator's performance and mental workload when interacting with a complex system, such as the main control room (MCR) of a nuclear power plant (NPP), are major concerns when seeking to accomplish safe and successful operations. The impact of performance on operator workload is one of the most widely researched areas in human factors science with over five hundred workload articles published since the 1960s (Brannick, Salas, & Prince, 1997; Meshkati & Hancock, 2011). Researchers have used specific workload measures across domains to assess the effects of taskload. However, research has not sufficiently assessed the psychometric properties, such as reliability, validity, and sensitivity, which delineates and limits the roles of these measures in workload assessment (Nygren, 1991). As a result, there is no sufficiently effective measure for indicating changes in workload for distinct tasks across multiple domains (Abich, 2013). Abich (2013) was the most recent to systematically test the subjective and objective workload measures for determining the universality and sensitivity of each alone or in combination. This systematic approach assessed taskload changes within three tasks in the context of a military intelligence, surveillance, and reconnaissance (ISR) missions. The purpose for the present experiment was to determine if certain workload measures are sufficiently effective across domains by taking the findings from one domain (military) and testing whether those results hold true in a different domain, that of nuclear. Results showed that only two measures (NASA-TLX frustration and fNIR) were sufficiently effective at indicating workload changes between the three task types in the nuclear domain, but many measures were statistically significant. The results of this research effort combined with the results from Abich (2013) highlight an alarming problem. The ability of subjective and physiological measures to indicate changes in workload varies across tasks (Abich, 2013) and across domain. A single measure is not able to measure the complex construct of workload across different tasks within the same domain or across domains. This research effort highlights the importance of proper methodology. As researchers, we have to identify the appropriate workload measure for all tasks regardless of the domain by investigating the effectiveness of each measure. The findings of the present study suggest that responsible science include evaluating workload measures before use, not relying on prior research or theory. In other words, results indicate that it is only acceptable to use a measure based on prior findings if research has tested that measure on the exact task and manipulations within that specific domain.