What Can Analytics for Teamwork Proxemics Reveal About Positioning Dynamics In Clinical Simulations

Effective teamwork is critical to improve patient outcomes in healthcare. However, achieving this capabilityrequires that pre-service nurses develop the spatial abilities they will require in their clinical placements, suchas: learning when to remain close to the patient and to other team members; positioning themselves correctlyat the right time; and deciding on specific team formations (e.g. face-to-face or side-by-side) to enable effectiveinteraction or avoid disrupting clinical procedures. However, positioning dynamics are ephemeral and caneasily become occluded by the multiple tasks nurses have to accomplish. Digital traces automatically capturedby indoor positioning sensors can be used to address this problem for the purpose of improving nurses' reflection, learning and professional development. This paper presents; i) a qualitative study that illustrateshow to elicit spatial behaviours from educators' pedagogical expectations, and ii) a modelling approachthat transforms nurses' low-level position traces into higher-order proxemics constructs, informed by sucheducatos' expectations, in the context of simulation-based teamwork training. To illustrate our modellingapproach, we conducted an in-the-wild study with 55 undergraduate students and five educators from whompositioning traces were captured in eleven authentic nursing education classes. Low-levelx-ydata was usedto model three proxemic constructs: i) co-presence in interactional spaces, ii) socio-spatial formations (i.e.f-formations), and ii) presence in spaces of interest. Through a number of vignettes, we illustrate how indoorpositioning analytics can be used to address questions that educators and researchers have about teamwork inhealthcare simulation settings.