Latent personality profiles of analog astronauts: An unsupervised clustering method analysis

The selection of astronauts for space missions is an important process that involves the assessment of multiple factors, including personality traits. Previous studies have corroborated that these traits exert a significant influence on the performance and adaptation of the crew during the execution of space missions. In this study, International Personality Item Pool - NEO – 120 (IPIP-120) was used to assess the personality of participants in a sample of 43 analog astronauts who took part in 9 different analog missions between 2022 and 2023. The objective was to identify specific personality profiles among the analog astronauts using the unsupervised k-means clustering method. The centroids of each cluster were analyzed to describe distinctive personality profiles. The results revealed the existence of two distinct personality clusters among the analog astronauts. The first cluster showed a greater propensity toward adventure, intellect, goal striving, extroversion, and cooperation. In contrast, the second cluster exhibited lower scores on these traits. The identification of these two differentiated personality profiles reinforces the importance of personality assessment as a valuable tool in the astronaut selection process. Furthermore, the application of the k-means method demonstrates its utility as an effective technique for identifying underlying patterns in complex datasets. These findings may inform future astronaut selection strategies, contributing to the formation of more effective and cohesive teams for space missions. • Astronaut selection is a critical task for the success of manned space missions. • Personality profile of astronauts can influence their performance and adaptation to extreme environments. • The K-means method,unsupervised clustering algorithm represents a valuable tool in psychological research. • Two diffrenciated clusters have been obtained, that is, two personality profiles in our study.