Abstract
As space missions venture beyond low-Earth orbit, adaptive team processes become vital to mission success. Using a team process framework, this study analyzed 60 problem-solving events from manned Apollo missions. Findings reveal differential cognitive and interpersonal behaviors across mission phases and problem criticality. Implications include the importance of contextualized training, fostering support behaviors, and developing autonomy-compatible protocols (e.g., AI scaffolds) to sustain team performance in future high-risk, communication-delayed environments.
Introduction and Background
As space exploration extends beyond Earth’s orbit and into deep space, understanding how astronaut crews collaborate to solve mission-related challenges becomes increasingly critical. Crews must engage in effective, coordinated problem-solving among themselves and in collaboration with the Mission Control Center (MCC) on Earth to ensure mission success and crew safety.
Space travel’s isolated, confined, and extreme (ICE) environment presents unique challenges, particularly when responding to unexpected technical issues. Key sources of adversity in problem-solving during space missions include the need to rapidly monitor multiple sensor inputs, diagnose issues from numerous potential causes, and implement solutions that integrate both the crew’s direct observations and MCC’s remote guidance (Paris, 2014). While these challenges are not exclusive to space missions, the inherent nature of the space environment (e.g., microgravity, remoteness) increases the stakes in solving those issues (Schmutz et al., 2023).
Moreover, future space missions are positioned to be even longer in duration (e.g., the Artemis Moon missions) and further from Earth (e.g., Mars expeditions) than the Apollo missions. Consequently, additional stressors, including crew fatigue, interpersonal strain, and communication delays with the MCC, may further complicate successful problem resolution (Parisi et al., 2022). While no human has yet gone farther from Earth than the Moon, the approximately 2.5-s Lunar communication delay can already disrupt normal team functioning (Fischer et al., 2013). Therefore, analyzing the communication patterns of past Moon missions is the best we currently have to truly understand the different patterns of adaptive team processes in response to increased communication lag between the MCC and astronaut crews.
Recent reviews on spaceflight teamwork highlight how the processes of responding to such challenges are shaped by various inputs (e.g., team composition, mission context) and influence important team outcomes such as team performance and mission success (Golden et al., 2018; Käosaar et al., 2022). Therefore, examining team processes in this context offers valuable insight into how space crews navigate complex problem-solving scenarios.
When considering social and cognitive factors through the study of analog environments, studies show that crews experience a range of challenges (Marques-Quinteiro et al., 2024). These can be task-related (e.g., technology failure) or social, such as conflict within the team. Such problems are exacerbated given the extreme environments that produce changes in mood and cognition (see Palinkas & Suedfeld, 2021).
Other work has examined specifics of collaborative problem solving through archival analyses (Käosaar et al., 2024) and space analog simulations (DeChurch et al., 2024; Lungeanu et al., 2023; Marcinkowski et al., 2021). These works pointed to the importance of shared mental models as well as a focus on task understanding and multiteam-system (MTS) coordination. While Käosaar et al. (2024) noted that the majority of problem solving of Apollo crews was done by mission control and communicated to the crew, Lungeanu et al. (2023) and DeChurch et al. (2024) showed how important established communication networks are for efficient problem-solving of the space MTS. Another important finding from the Apollo missions was that crews adapt communication patterns depending on mission phase (e.g., in near-Earth orbit, simple processes are the norm), but that communication patterns are consistent across mission-critical and non-mission-critical events (Käosaar et al., 2024). Finally, regarding crew conflict, Marcinkowski et al. (2021) showed how, in the case of ICE teams, a more nuanced approach for unpacking crew conflict is needed to fully grasp the impact of task-related and interpersonal disagreements.
Recent work has also examined expert insights into team cognition and interpersonal relationships for long-distance space missions (Burke et al., 2024; Fiore et al., 2024). Recurrent themes related to team cognition included a blend of both teamwork and taskwork factors. From the perspective of taskwork, one issue was identifying the amount of technical knowledge needed by crew members, given that they will be more autonomous. SMEs suggested this issue should influence space technology design to reduce the likelihood that this becomes problematic. From the teamwork standpoint, SMEs noted that teams would need to better manage social and emotional relationships. Importantly, this was not only for the flight crew but also the ground crew, and the flight crew’s families. Another important teamwork consideration included the importance of co-located training for crews to ensure development of shared knowledge and team familiarity.
In sum, research increasingly shows the importance of collaboration and cognition for long-duration and long-distance space missions. Next, we will discuss how we further our understanding of team processes in preparation for future space missions.
Teamwork Processes for Long-Distance Missions
A foundational perspective on team processes by Marks et al. (2001) defines team processes as team members’ interdependent acts that convert inputs to outcomes through cognitive, verbal, and behavioral activities to achieve collective goals. Their model identifies three types of team processes: transition, action, and interpersonal processes, which teams do not undergo linearly but rather shift between based on situational demands. This framework provides a valuable lens for connecting existing teamwork research in ICE environments. However, while some mapping of team processes in ICE contexts has been conducted, a deeper understanding of how teams successfully enact these processes under adversity remains lacking.
More specifically, to train astronauts and other professionals in similar perilous environments, an understanding of adaptive patterns of team processes to situational variables is required (Salas et al., 2012). For example, knowing whether focusing on transition, action, or interpersonal processes during critical or non-critical events supports solving the task at hand would be crucial to train astronauts to engage in those processes.
Thus, this study aims to enhance our understanding of functional team process enactment in complex problem-solving scenarios in space. Specifically, we seek to:
Bridge the theory-practice gap by adapting a well-established team processes framework to communications data from real space teams.
Identify process patterns exhibited by highly successful spaceflight teams, offering insights into behaviors contributing to effective problem-solving in space missions.
Method
To answer the stated aims, we analyzed archival mission communication transcripts of manned Apollo missions. Archival datasets have been considered valuable for gaining insights without new data collection Shultz et al. (2005). Moreover, since acquiring data from current astronaut teams is challenging (Bell et al., 2018) and most teamwork research in ICE teams is conducted on space analogs (Käosaar et al., 2022), studying historical astronaut teams offers the closest available proxy for what future space teams may experience.
It could be argued that a lot has changed regarding human space flight over the 5 decades since the last Moon landing. Nevertheless, all manned missions have since been low-earth orbit (LEO, e.g., to and on the International Space Station) missions with instant communication, most of them with somewhat robust and tested systems, and a quick evacuation opportunity (Landon et al., 2017). The upcoming Artemis missions are very different from LEO missions and much more similar to the Apollo missions. Therefore, although archival data, the Apollo missions transcripts represent a foundational set of experiences for helping us understand teamwork on the way to the Moon, on the Moon, and beyond.
We analyzed publicly available Apollo crew and MCC communications (Apollo 7–Apollo 17) to examine problem-solving, leveraging the Apollo program’s consistent objectives across missions, standardized spacecraft design, and publicly available data for meaningful cross-mission comparisons. Sixty problem-solving events were extracted from the mission transcripts, which were then categorized by mission phase and criticality (Käosaar et al., 2024). Events met these criteria: (1) involved a challenge without an obvious solution, (2) required team-level response, (3) had clear details on participants and resolution, and (4) did not follow standard protocols. Events were identified using NASA reports and a systematic transcript review.
A structured coding approach was developed and refined through pilot testing. The codebook was based mainly on Marks et al.’s (2001) team processes framework, but other team processes frameworks (Gibson et al., 2003; Hoegl & Gemuenden, 2001; Morgeson et al., 2010) were also consulted. While the general processes in the codebook remained the same as in the Marks et al. (2001) framework, the high-level transition vs action processes distinction was omitted due to the low suitability to differentiate between them from the communications transcript. Thus, the final codebook consisted of seven task and three interpersonal processes (see Table 1 for specific codes).
Standardized Values (Codes Per 100 Utterances) of Team Processes Across Phases and Criticality of Events. The Intensity of the Blue Color Indicates the Lower (Lighter) and Higher (Darker) Distribution of the Codes.
Based on the content analysis method (Denzin & Lincoln, 2018), four trained coders analyzed the transcripts using the developed codebook to extract the team processes data. Each critical incident file was coded by two coders independently, achieving an intercoder agreement of .740 (considered acceptable; Krippendorff, 2014). After individual coding, agreement meetings among pairs of coders who coded the same file were held to achieve complete agreement on the specific codes before analysis. Since the file length varied between 2-page and 40-page files, code counts were standardized to reduce the confounding effect of file length, and the number of codes per 100 coded utterances was used for the analysis.
To answer the research questions, comparison tables across event criticality and mission phase were produced. The tables were qualitatively investigated.
Findings
The findings of this study provide a standardized analysis of team process behaviors across different mission phases and levels of problem criticality. We examined the distribution of coded team processes to determine which behaviors were most frequently enacted during problem-solving events. As shown in Table 1, the most frequently observed team processes during problem-solving included planning and strategy formulation, progress monitoring, and systems/environment monitoring. In contrast, disagreement and conflict management, motivation and confidence building, and backup and helping behaviors were infrequently observed. Surprisingly, backup and helping behaviors were rarely coded, suggesting that individual autonomy or reliance on protocol-based responses may have played a stronger role in problem resolution than direct team support.
Team processes varied across mission phases and problem criticality. Motivation and confidence-building behaviors were most prominent during high-stress phases, such as near-Earth, near-Lunar, and on the Lunar Surface, but were largely absent on the return trip to Earth. Identification of problem space peaked near-Earth, while planning and strategy formulation were most frequently enacted on the way to the Moon. Backup and helping behaviors were rarely observed early in the mission but increased near-Lunar and peaked on the Lunar Surface. Coordination followed a similar trend, with the highest enactment occurring on the Lunar Surface. Progress monitoring remained relatively stable throughout the mission, but peaked on the way back to Earth. Systems and environment monitoring peaked en route to the Moon and near-Lunar surface. Team monitoring was most frequent near-Earth and again on the return to Earth, with middle phases showing a more balanced distribution. Affect management was least enacted on the way to the Moon but became more prominent near-Earth and on the Lunar Surface. Interestingly, disagreement and conflict management were only observed on the way to the Moon. This may suggest the accumulation of stress that became explicit in the last phase of the mission, thus requiring it to be managed.
Regarding event criticality, disagreement and conflict management were present almost exclusively in mission-critical situations, indicating that high-stakes problem-solving may induce more disagreement. Similarly, motivation and confidence-building behaviors were more frequently enacted in mission-critical events, likely to maintain team morale and focus under stress. Identification of problem space and planning and strategy formulation were slightly more common in non-mission-critical events, suggesting that crews may have had more time for structured decision-making in lower-pressure situations. Backup and helping behaviors were also significantly more frequent in non-mission-critical events, implying that collaborative support was more prevalent when immediate resolution was less urgent. Monitoring processes varied, with progress and team monitoring more common in non-critical situations, whereas systems and environment monitoring was slightly more frequent in mission-critical events, likely due to the need for heightened situational awareness in high-risk scenarios.
Discussion and Implications
The findings offer several implications for human factors and operational psychology, particularly in preparing teams for high-autonomy, high-risk missions beyond low-Earth orbit.
Process Agility and Functional Adaptation
The findings indicate that astronaut teams dynamically modulated their use of problem-solving related team processes across different mission phases and problem criticality levels. For example, motivation and confidence-building processes were more salient during high-stress mission phases (e.g., lunar surface operations), whereas planning and strategy formulation, and problem space identification were more prominent in lower-pressure contexts. This flexibility aligns with Marks et al.’s (2001) conceptualization of team processes as dynamic and recursive rather than linear. It also supports theories of adaptive team performance (e.g., Burke et al., 2006), emphasizing teams’ ability to shift process focus in response to contextual demands.
From a human factors and operational psychology standpoint, these findings support the incorporation of process agility training in pre-mission training. Instead of rigidly scripting teamwork competencies, astronaut preparation should include scenario-based problem-solving training that prompts teams to move between interpersonal, planning, and monitoring behaviors based on evolving stressors related to a critical incident. Operational psychologists may also consider developing behavioral markers for phase-specific team adaptation (cf. Wiltshire et al., 2018), which could serve as diagnostic tools for evaluating team readiness.
Underutilization of Backup Behavior
One of the more surprising findings was the infrequency of backup and helping behaviors, especially during high-criticality events. While autonomy and self-reliance are valued traits in astronaut selection and training (Landon et al., 2017), the low enactment of supportive behaviors raises questions about team-level resource sharing under pressure. In long-duration missions, a rigid adherence to individual autonomy may compromise team resilience and increase the risk of performance decrements under overload or fatigue (Salas et al., 2005).
Training protocols should explicitly address the autonomy–support trade-off by fostering skills in mutual performance monitoring and help-seeking within a high-autonomy context, especially during critical events. This aligns with teamwork models in high-risk domains, such as aviation and critical care (Baker et al., 2006), which emphasize the importance of backup behavior in sustaining collective performance. Operational psychologists can develop simulation scenarios in which performance success hinges on timely and context-sensitive support behaviors, especially during degraded operations.
Preparing for Communication Delay
Apollo missions operated under near-instantaneous communication (near Earth) or short communication delay (near and on the Moon) with MCC, but future deep-space missions will face significant communication delays (e.g., 5–20 min each way for Mars). This study found that planning, monitoring, and problem identification processes were prevalent under conditions of real-time coordination. These findings provide a baseline for anticipating how teams may need to restructure communication workflows when time-critical input from MCC is no longer feasible.
Human factors psychologists should work toward developing and validating anticipatory coordination protocols that enable teams to operate autonomously during periods of communication blackout or lag. Such protocols may include pre-authorization strategies, shared mental model alignment, and decision heuristics for high-uncertainty conditions (Fiore et al., 2024). Training should incorporate graduated communication-delay simulations, allowing crews to progressively build confidence in self-directed decision-making.
Scaffolding Team Processes With Intelligent Systems
Finally, the structured nature of many Apollo team behaviors, particularly in planning and monitoring, suggests an opportunity for future missions to integrate AI-driven decision support tools that facilitate team process enactment. Rather than replacing human cognition, intelligent agents could prompt critical processes (e.g., “Have you clarified the problem space?”) or flag lapses in coordination, especially during periods of high workload or isolation.
Human factors psychologists must ensure that automated systems scaffold rather than supplant adaptive team processes as human-AI teaming becomes integral to space operations. Designing these tools requires a deep understanding of naturalistic team behaviors derived from studies like this one. For example, recent work on human-AI teaming shows that human team members’ dispositional characteristics (e.g., teamwork potential) can influence how they respond to AI-developed team coaching (Bendell et al., 2024). The development of process-aware AI companions, informed by empirical models of teamwork, can enhance collective efficacy while preserving crew autonomy.
Conclusion
This study focused on the theoretical and methodological foundations of analyzing team processes of problem-solving events in space using archival Apollo space missions’ data. We provided initial findings regarding adaptive team processes in team problem-solving and discuss the main themes stemming from this study. In this way we help set the stage for future research as humans prepare to continue a deeper exploration of space.
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Writing of this paper was partially supported by US Air Force Office of Scientific Research (AFOSR) grant FA9550-22-1-0151, awarded to Stephen M. Fiore under Contract No. W911NF-20-1-0008. Any opinions, findings and conclusions expressed in this material are those of the authors and do not necessarily reflect the views of the AFOSR or the University of Central Florida.
