Turning Clinical Reasoning Research Toward Intervention: Validating a Process Model Using VR Simulation Data

Clinical reasoning in acute care unfolds under time pressure as teams must continuously interpret evolving patient information while coordinating treatment. While research has predominantly focused on diagnostic reasoning, it remains insufficiently understood how care teams generate, coordinate, and enact interventions, and how these processes are organized. To address this gap, we introduce the Collaborative Diagnostic–Intervention Reasoning (CDI-R) model, a theory-driven process model that conceptualizes clinical reasoning as the interplay of diagnostic activities (DAs), intervention activities (IAs), and collaborative activities (CAs). We provide an initial empirical examination of the model using a virtual reality cardiac arrest simulation with 29 teams ( N = 116 participants). Team interactions were coded at the utterance level. Lag Sequential Analysis (LSA) was used to examine transitions between DAs and IAs, and Epistemic Network Analysis (ENA) was used to examine the structural organization of CAs. Findings reveal three key patterns. First, DAs and IAs constitute structurally distinct reasoning modes, characterized by different configurations of CAs. Second, reasoning unfolds in non-linear and recurrent sequences, with sustained engagement within and transitions between reasoning modes. Third, expertise shapes the organization of reasoning: expert-led teams engaged in a higher proportion of IA-oriented activity, transitioned more frequently from diagnosis to intervention, and showed more differentiated collaborative structures, whereas trainee-led teams exhibited more loops within reasoning modes. By explicitly integrating intervention reasoning into models of clinical reasoning, this study advances a process-oriented account of team-based reasoning. The CDI-R model provides a framework for examining how teams coordinate diagnosis and intervention in dynamic clinical settings.