Last Published:  07/30/20 02:45:13 PM (Central)
Responsible Element: Human Factors and Behavioral Performance (HFBP)
Status: Open

There is little evidence available to help us understand what psychological and psychosocial factors contribute the most to the process of composing teams with the best chances of successfully living and working together for long duration exploration missions. Within social and organizational psychology research there are some studies around “group composition” or putting together project/ mission teams within already- existing, larger work or social groups. We do not know what combination of these traditionally predictive combinations of psychological measures will most efficiently and accurately predict individuals most or least likely, to succeed in terms of team health and performance for long duration spaceflight. The astronaut job is unique and difficult to compare with other jobs that have evidence available, and the standards for successful astronaut performance are much broader, higher, and longer than performance standards are in typical jobs. We do know that some psychological factors (like social support) predict team health and performance in some working conditions but not in others, and at different levels at times within a team’s lifespan together. However, with the outcome of interest being the whole performance of the sub- group or team rather than individual performance, research has more difficulty obtaining sufficient sample sizes to finely identify contributing psychosocial factors. A long history of research exists in the field of personnel psychology, and this research provides evidence that several psychological measures can be implemented during employee selection to save organizations time and money by reducing the selection of individuals who cannot actually or easily be trained to perform the job without significant risk of injury or error. The benefits to organizations are reduced error in selecting the wrong people, reduced training costs, reduced errors on the job, etc. However, many of the most predictive psychological measures are most predictive in certain combination for specific types of jobs in specific contexts for a limited time period of performance. Researchers need a large number of teams to effectively test predictors, and teams are both harder to gain access to or recruit and harder to research due to changing membership (e.g. teams break-up, exchange team members, or exclude team members for various operational reasons). Current research evidence is entirely in populations that are dissimilar to astronauts and offer limited value in predicting their (astronaut’s) team performance. Further, the performance outcomes used in these studies rarely resemble astronaut performance requirements and are studied in contexts that are nothing like long duration space missions. Additionally, most work groups or teams are composed from a larger set of individuals than NASA has available to choose from when composing crews (e.g. most organizations the size of NASA/JSC have dozens of engineering employees to pick from for a particular role within one project team, but NASA usually has only a couple of qualified astronauts to pick from to fill particular role, like robotics lead, for an expedition team). We do not know what, if any, factors should be considered when composing a crew of astronauts from a small set of qualified astronauts for a long-duration space flight mission. At this point, research cannot advise operations what factors are most likely to ensure that the best decisions are made regarding crew composition. An algorithm is needed to describe both what factors are important and what the trade-offs are in terms of risk of performance decrements for ignoring one psychological factor for a higher priority psychological factor or operational requirement. Research needs to inform operations of those psychological measures that are most predictive of high performance (and low error impact and frequency) in populations and job contexts that resemble those of astronauts and long duration spaceflight, and determine the combination of psychological measures that would most accurately predict astronaut performance long term.


Based on using the job analysis results and criteria selected from that, which will ultimately lead to the selection of adequate measures for employee selection and performance prediction, we will be able to utilize effective measures that will enable us to close this particular gap. The conclusions/results from tasks will determine the metrics used to quantify the completion of the Gap. Research findings will guide the selection of the most accurate measures, key indicators, and mission attributes that will then provide the foundation of the proposed Team composition algorithm. In order to ensure this is done successfully, we will consider research findings, mission requirements, consult with SMEs using a thorough vetting process with relevant stakeholders (e.g., BHP Ops). By taking these progressive steps, we can confidently suggest valuable and effective measures that will allow Operations to select crewmembers with relevant psychological and psychosocial characteristics most associated with high functioning team performance.

Target for Closure
  1. Identify robust predictors (psychological measures that have research evidence supporting their predictive and (criterion-related) validity) and recommend a behavioral competency standard for exploration for task performance, teamwork, and psychosocial adaptation over mission-relevant durations among populations similar to astronauts.
  2. Using robust predictors, develop an algorithm to inform crew composition decisions that incorporates the validated set of measures (from Team -101 & Team-102) and key indicators (from Team-101) that predict outcomes for different mission durations and provides effective teaming for increasingly earth independent, autonomous long duration missions.

a. Validated measures and indicators that have research evidence supporting their predictive (criterion-related validity) for task performance, teamwork, and psychosocial adaptation over time among populations who are similar to and doing work similar to astronauts.

b. An algorithm that weights individual characteristics (e.g., KSAs), roles, positions, mission attributes and scenarios and informs crew composition decisions.


Risk Risk of Performance and Behavioral Health Decrements Due to Inadequate Cooperation, Coordination, Communication, and Psychosocial Adaptation within a Team
You are here! Gap Team-103: We need to identify psychological and psychosocial factors, measures, and combinations thereof for use in selecting individuals and composing highly effective crews most likely to maintain team function during shifting autonomy in increasingly earth independent, long duration exploration missions.

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