Evaluation of the Validity, Acceptability and Usability of Bio-mathematical Models to Predict Fatigue in an Operational Environment

Bio-mathematical models hold promise as tools that can be used to manage fatigue risks in an operational setting. There are numerous models available to predict fatigue-related performance impairment arising from sleep loss, circadian misalignment, and sleep inertia. It is imperative that any model considered for use during spaceflight missions be validated in an operational setting in order to ensure that predictions are reliable and consistent. Given the complexity of the underlying causes of fatigue, there are wide individual differences in response to mission stressors; however, the majority of candidate models provide predictions based on average human responses, making it difficult to use the models to make operational decisions for individuals. In addition, there are no published reports on the acceptability, usability, and feasibility of any of the current models. Effective incorporation in a spaceflight environment requires model-based software systems that are easy to use by a wide-range of operators and are integrated with other scheduling constraints that are relevant in spaceflight operations.

We will work with NASA to identify which model(s) are the best candidates for inclusion in 4 Human Exploration Research Analog (HERA) studies. Once complete, our evaluation will provide operational personnel with an understanding of 1) the validity of the model predictions in an operational setting, including how predictions may vary by individual; 2) the acceptability, usability, and feasibility of using the software in an operational setting; and 3) a preliminary assessment of the utility of integrating the model predictions into existing scheduling tools.

Specific Aim 1: Validate model predictions in a spaceflight analog. To accomplish this aim, we will conduct two analyses. First, we will evaluate the performance of the selected model against gold-standard and operational estimates of fatigue among participants (n=16) during four HERA missions. Second, we will assess individual characteristics. We will use a battery of astronaut selection tests in order to collect characteristic parameters and evaluate how well they improve our ability to estimate resiliency and vulnerability to fatigue. The results of this analysis should help crew and support personnel to better understand and estimate performance based on individual as well as situational factors.

Specific Aim 2: Evaluate acceptability, usability, and feasibility of the selected sleep-wake model software user interface. The current candidate models available for consideration in a spaceflight environment utilize a variety of platforms and it is unclear whether such tools are feasible for implementation in a spaceflight environment. Often, these software tools require significant expertise in modeling sleep-wake activity and experience using such platform. To accomplish this aim, we will conduct think-aloud usability user tests, post-debrief surveys, and in mission short surveys to measure subjective acceptability ratings and number of usability issues.

Specific Aim 3: Incorporate model predictions into Playbook and assess usability and acceptability of model in the context of scheduling & planning. Although each fatigue model has been incorporated into a stand-alone interface, it may be difficult for crew to apply the performance predictions generated by the selected model(s) to operational demands due to the need for two separate software interfaces (i.e., one for performance predictions and one for scheduling decisions). The complexity of such a task may deter crew from accepting or using the bio-mathematical predictions. Therefore, it is desirable to incorporate the model predictions into scheduling tools used by crew. In order to accomplish this aim, we will conduct a nested pilot study, whereby we integrate the model predictions into Playbook, NASA’s self-scheduling tool, and evaluate which interface is preferred by crew.

Bio-mathematical models are useful tools for predicting when an individual may be too sleepy to complete tasks. The information gained from this project should provide insight into how well these models predict performance impairment in an operational environment. There are many other occupational groups that could benefit from this information, including shiftworkers, military personnel, and individuals working in high pressure occupations, such as medicine, aviation, and the oil industry.

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