What changes the picture: task complexity and the limits of each method
Task demands appear to shift how shared mental models play out. In the ambulance missions, the profile of communication differed between high- and low-complexity missions, with more frequent use of coordinating mechanisms and team competencies in low-complexity missions [2]. The study also found that shared mental models and closed-loop communication were the only coordinating mechanisms observed, and leadership and team orientation the only competencies exercised [2]. That narrow range may reflect the specific emergency setting rather than virtual teams in general.
Measurement choices carry their own scope limits. The virtual-reality method was tested with handball teams, not workplace virtual teams, so its promise for organizational settings is suggested rather than established [5]. The ambulance study used voice recordings from real missions, which gives ecological validity but captures only what is spoken [2]. And the 2025 review's central finding—that methods lack standardization—means that a result from one measurement approach may not transfer cleanly to another [1].
Where measurement is heading, and what is still missing
The push is toward situational, behavior-based measures and toward consistency. The 2025 review calls for innovative approaches and standardized measurement to move the field forward [1]. The virtual-reality study positions itself as a starting point for more situational group research, arguing that situational measures have the highest ecological transfer to behavior [5].
A related line of work on human-AI teams reaches a similar conclusion from a different direction: a theoretical review found that a lack of consistency in terms and of effective means for measuring shared mental models in human-AI teams currently impedes realization of the concept [4]. That review also notes it remains unclear how the shared mental model construct may differ when some teammates are AI agents, how and under what conditions such models form, and how they should be quantified [4]. For virtual teams of humans, the practical takeaway is that shared mental models are clearly useful to understand, but the field has not settled on one trustworthy way to count them.
Sources used in this answer
Understanding Shared Mental Models in Virtual Teams: Key Insights and Future Directions
A systematic review of virtual-team research from 2004 to 2023 found that diverse types of shared mental models impact team functioning, but measurement methods lack standardization and need innovative approaches.
The Effect of Complexity of Ambulance Missions on Shared Mental Models in Virtual Teams
In real ambulance missions, high-complexity missions showed lower frequencies of team competencies and coordinating mechanisms than low-complexity missions, and the authors proposed that lack of visual input could lead to team process loss.
The influence of shared-representation on shared mental models in virtual teams
The study tested how the availability of shared representation affects collaboration and the development of shared mental models in virtual teams.
The role of shared mental models in human-AI teams: a theoretical review
A theoretical review of human-AI teams found that inconsistency in terms and lack of effective measurement methods currently impede realization of the shared mental model concept.
Are you thinking what I am thinking? A feasibility study of a virtual reality measurement for shared mental models in team sports
A virtual-reality method in which teammates indicated their own and their partner's decisions measured shared mental models above chance in team sports, while questionnaire scores correlated with team trust and subjective performance but the VR measure did not confirm assumed influences on objective performance.
