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Using Real-Time Lexical Indicators to Detect Performance Decrements in Spaceflight Teams: A Methodology to Dynamically Monitor Cognitive, Emotional, and Social Mechanisms that Influence Performance

Principal Investigator:
Eduardo Salas, Ph.D.

University of Central Florida

The NSBRI Neurobehavioral and Psychosocial Factors Teams (NSBRI-NBPF) has identified the requirement for the development of “entirely non-obtrusive objective means of detecting and mitigating cognitive performance deficits, stress, fatigue, anxiety and depression for the operational setting of spaceflight.” This project proposes a methodology to assess cognitive and emotional state “at a distance” though the analysis of spontaneous verbal output in real-time communications. One product of this research will be a real-time assessment tool to detect cognitive performance deficits, stress, fatigue, anxiety, and depression in the spaceflight operational setting. This tool would provide an unobtrusive, real-time indicator of individual and team functioning, allowing interventions to mitigate and manage potential decrements in performance to be implemented should the need arise.

NASA Taskbook Entry

Technical Summary

The operational context of spaceflight is dynamic, complex, and demanding. Flight crews are exposed to an array of environmental, task, and interpersonal stressors that can negatively impact performance as well as jeopardize the safety and wellbeing of crewmembers. The requirement exists to develop non-obtrusive means of detecting and mitigating cognitive performance deficits, stress, fatigue, anxiety, and depression in the spaceflight operational setting. One problem with many existing assessment methods is that most require direct observation of behavior or performance or self-assessment by a pen and paper-type instrument. The requirement to assess individual and team functioning "at a distance" suggests the potential efficacy of a methodology to assess cognitive and emotional state in real-time from ongoing or spontaneous verbal output.

The basic premise of this work is that spontaneous verbal output provides a natural and valid indicator of basic cognitive processes. Natural word use is not prone to the typical limitations of self-report measurements. That is, natural language use is less subject to social desirability bias, and can be derived in real-time without interfering with the cognitive processes being measured, and without interrupting team performance. Moreover, natural word use is reliable and consistent across time and context, and can be meaningfully measured in individuals and teams. However, to date, there has been no effort to develop a lexical-based approach to tracking and mitigating stress effects in spaceflight. What is needed is a means of extracting valid indicators of the relevant elements of cognitive processes occurring during spaceflight from crew members' spontaneous verbal output. In other words, how can one extract valid operational measures of stress, fatigue, or anxiety? The approach to be developed in this effort is derived from recent developments in the study of associative meaning in linguistics and information science. Specifically, for any given construct or process, a lexicon of words indicative of that construct or process is developed. The relative prevalence of those words is used as an indicator of the degree to which that construct is engaged / that process is occurring.

The simplest and most straightforward approach would be to employ standard corpora of word association norms. These word association norms have been derived by soliciting free associations from large samples of participants. For example, when presented with the stimulus word "sickness," frequent free-associate response words are "ill," "fever," and "nausea." An indicator of the construct of "sickness" in some ongoing interaction would be the relative prevalence in spontaneous verbal output of these high-frequency associate words. However, there are several difficulties with the standard corpora of word association norms. For example, the largest and most highly-cited of these corpora is over 40 years out of date. Linguists and information scientists have recently developed alternative approaches to the study of associative meaning, by using an Internet-based approach to examine lexical co-occurrence. For any given construct, a lexicon of words most indicative of that construct can be defined by examining the lexical co-occurrence of those words in online usage. In other words, rather than relying upon a sample of participants to indicate which words co-occur in their thoughts, this approach uses the massive lexical corpus of linguistic output on the Internet to determine which words actually co-occur in use. Research has shown that conditional probabilities derived from lexical co-occurrence in internet websites renders results that are highly consonant with the patterns obtained from the standard corpora of word association norms. This approach has the advantages of being current and capable of handling exhaustively large lexicons for scores of different constructs.

In brief, conditional probabilities derived from lexical co-occurrence can produce lexical indicators of relevant cognitive/emotional states. Once such lexicons are developed, then analysis can be focused on automated tabulation of the relative prevalence of construct- or process- relevant lexicon words as a real-time, unobtrusive indicator of cognitive/emotional processes.

The perceived impact of the proposed work will contribute to the state of knowledge in the field in several ways. First, it directly responds to the requirement to "refine entirely non-obtrusive objective means of detecting and mitigating cognitive performance deficits, stress, fatigue, anxiety and depression for the operational setting of spaceflight." These real-time, unobtrusive indicators of cognitive processes could be used to measure individual cognitive and emotional state without interfering with the process and performance being studied. Second, comparison of individual and crew indices can suggest optimal avenues for mitigation. For example, real-time measures may illuminate whether a team-based or individually focused countermeasure is needed. Third, this approach can be employed to gauge a full complement of constructs relevant to spaceflight performance, including stress, fatigue, and anxiety as well as team collaboration processes. Finally, the advantages of this approach extend beyond spaceflight and would be practically useful in a number of distributed or high stakes environments such as aviation crews and medical teams.

Earth Applications

The outcome of this research effort will not only allow for the dynamic and unobtrusive detection stress and related cognitive deficits of spaceflight teams during spaceflight, but will also be directly applicable to earth-based applications. It is expected that a real-time assessment and graphical display of stress effects (such as attentional focus, cognitive load, negative emotion, anxiety, and social impairment), as well as measures of fatigue, mood, and team functioning (i.e., collective orientation, synchronicity) drawn from ongoing verbal or textual communications can be used in healthcare, military, education, law enforcement, and workplace applications.