Facilitating Translational Team Science

This project examines team performance in science meetings in order to explore how translational, interdisciplinary teams succeed. We propose a mixed method approach that 1) combines a meeting interaction network analysis based on graph theory (‘meetomes’) with an analysis of how team members actually interact; and 2) relates the findings from the beforementioned analyses to post-meeting questionnaires that were filled out by all participants to the meetings.

This project draws on a unique dataset collected within the multidisciplinary Clinical Neuroscience section of the department of Anatomy and Neurosciences (ANW). Between 2017 and 2019, all weekly lab meetings were recorded (n=70) and post-meeting questionnaires were filled out by all participants after most meetings (n=48). Questionnaire items measured meeting satisfaction, group processes, individual perceptions on taking charge and the meeting’s translational value. The goal of these recordings and questionnaires was to better understand group dynamics that may foster translational and interdisciplinary collaboration between team members. As a first step towards understanding these dynamics, we quantified interaction patterns between different team members using network analysis by creating ‘meetomes’ (a visual explanation of this method can be found here). 

Preliminary results show that (1) interaction patterns show variable network topologies; (2)  post-meeting assessments vary considerably; and (3) the two relate, such that team members may rate the meeting as contributing more to on-the-job effectiveness when they were part of many locally clustered interactions. As another example, we found that team members who are generally more inclined to take charge (i.e. being more proactive) more often play a ‘hub’ role in connecting subgroups within the team. 

     What is missing, however, is an in-depth analysis of the thematic content of each meeting, and how multidisciplinary information is exchanged in situ. This is why we propose to combine expertise from both partners involved in this project. 

Researchers: Linda Douw, Joyce Lamerichs