Shadowbox simulation helps medical trainees learn expert decision-making

A new study published in Advances in Simulation describes the implementation of a hybrid shadowbox simulation format within Scotland’s national Internal Medicine Training program. The research, led by Victoria Ruth Tallentire and colleagues, details how this educational approach makes expert reasoning visible to learners, allowing them to compare their own decision-making processes with those of experienced clinicians. By synthesising evidence from high-stakes fields like firefighting and the military with recent healthcare adaptations, the authors position shadowbox simulation as a theory-informed, resource-efficient method that advances current simulation practice. The article highlights the method’s potential to develop complex non-technical and behavioural skills, such as communication, prioritisation, and situational awareness, which are often difficult to teach through traditional immersive simulation alone.

The ShadowBox method, originally developed in 2008 from the Masters’ thesis of Neil Hintze, a retired Fire Battalion Chief in New York, was co-developed with cognitive psychologist Gary Klein. It was initially used to train New York fire department personnel, enabling them to compare their decision-making with expert reasoning in realistic scenarios. The core of the method involves scenario-based cognitive instruction that teaches tacit decision-making using experts’ mental models. Key features include presenting scenarios with specific decision-points where learners choose options and justify their rationale, revealing the experts’ reasoning for those same points, and providing an opportunity for learners to reflect on the differences between their own decisions and those of the experts. This approach allows learners to “see through the expert’s eyes” without the experts needing to be physically present, refining performance through low-stakes rehearsal against an imagined but realistic counterpart.

The theoretical basis of shadowbox simulation is grounded in cognitive transformation theory and the naturalistic decision-making framework. Cognitive transformation theory emphasises changes in mental models and frames, including the recognition and revision of flawed assumptions, rather than the simple accumulation of facts. The method operationalises this by asking learners to engage with realistic scenarios, articulate their reasoning, and compare it with the prioritisation, cue use, and rationale of experts. The naturalistic decision-making framework studies how experts make rapid, high-stakes decisions in contexts characterised by uncertainty. Within this framework, recognition-primed decision models suggest that experts often recognise familiar patterns and generate a plausible course of action, mentally simulating it to test feasibility. The educational goal is not to reproduce an expert’s initial pattern match uncritically, but to help learners recognise what experts notice, how they frame the problem, and when they check, revise, or override an initial impression.

In healthcare, the adaptation of the classic ShadowBox method into shadowbox simulation introduces important pedagogical differences. While the classic method systematically compares learner choices to expert responses with performance judged by alignment, shadowbox simulation applies these principles within the broader pedagogy of simulation-based education. Video vignettes or simulated encounters are typically combined with facilitated discussion or debriefing, with an emphasis on reflective exploration rather than scoring against expert responses. Early applications in healthcare, such as a 2020 study by Harder and Turner, demonstrated the feasibility of the approach for developing non-technical skills in nursing students without high resource demands. In Scotland, the approach was adapted for online learning in 2021, and by 2024, video resources were designed for synchronous debriefing and personal reflective study on topics relating to palliative care.

The Scottish Internal Medicine Training simulation program, which has been running since 2019, faced challenges in meeting learner requests for more immersive simulation due to limited equipment availability. Feedback from early iterations of the third-year “registrar ready” course indicated that round-table sessions discussing theoretical clinical decisions were not well-received. Consequently, a modified shadowboxing approach was utilised to develop a “hybrid shadowbox simulation” format. This model combines video vignettes of expert practice, structured decision-points, group discussion, and procedural practice, all supported by expert facilitation. Clinical scenarios were divided into short video clips, each focused on a particular intended learning outcome. During pauses between clips, questions were posed to small groups of learners in a format similar to a debriefing following an immersive simulation scenario.

When a procedure was required within a case, such as central venous catheterisation or management of tracheostomy emergencies, learners undertook the procedure on a part-task trainer before returning to the debriefing conversation and video. This innovative approach integrates video exemplars and the lens of an expert from shadowboxing with expert facilitation and group reflection from immersive simulation. The hybrid format was designed to provide sufficient authenticity for learners to engage credibly with the underlying judgement, prioritisation, and procedural steps required in context. The authors note that functional authenticity may be more important than high physical fidelity, particularly when the goal is orientation to sequence and decision-making rather than the refinement of psychomotor technique.

Evaluation of the hybrid shadowbox simulation format began with a pilot phase involving seven sessions and 40 learners. Feedback showed that many learners preferred this format to the more familiar immersive simulation approach they had encountered earlier in the program. They valued the opportunity to acknowledge uncertainty and discuss a variety of options, and the peer reflection fostered a sense of shared experience and purpose. The procedural refreshers allowed engagement to be maintained throughout the two-hour sessions. The nature of the sessions also appealed to learners who found immersive simulation highly anxiety-provoking, and facilitation was less cognitively burdensome for faculty because the video content was familiar prior to the session. This positive feedback, along with the format winning the best oral presentation at the Association for Simulated Practice in Healthcare conference in November 2024, encouraged the team to embed the sessions permanently within the longitudinal simulation program.

Between February and June 2025, 36 hybrid shadowbox simulation sessions were delivered to groups of four to six learners as part of the “registrar ready” course. Free-text comments from 95 learners reiterated the findings from the pilot phase, indicating that the format provided a safe and less anxiety-provoking learning environment compared with traditional immersive simulation. Learners reported being able to engage in open discussion without the pressure of performance. They valued the opportunity to explore ambiguity, share different perspectives, and contrast their reasoning with expert input, which was seen as enhancing information retention and reinforcing key physiological principles. The hybrid design, combining video vignettes, facilitated discussion, and practical tasks, was considered engaging and effective for consolidating both cognitive and procedural skills.

From a faculty perspective, the shadowbox simulation sessions offered several benefits over traditional immersive, full-scenario approaches. The ability to openly critique, analyse, and disagree with the management of an expert contrasted with conversations in immersive simulation debriefings, where contesting the decisions of a peer could be socially awkward or divisive. By shifting the focus from critique of a peer’s live performance to discussion of an externalised expert response, the format may have reduced interpersonal risk and social threat. Clinical cases were presented in short, digestible video clips, allowing a period of reflection after each one. This encouraged focused discussion on specific aspects of the case, as opposed to post-scenario debriefings in immersive simulation, which tend to cover broader topics or focus disproportionately on particular timepoints within the scenario.

Throughout the sessions, faculty observed that peer discussions drew on the experiences of doctors training across different specialty areas, demonstrating the shared decision-making expected in clinical practice. The authors note that such openness depends on facilitation that promotes psychological safety and supports an educational alliance in which learners feel able to voice uncertainty and dissent. Although a minority of learners questioned whether video added value beyond seminar-style teaching, the majority regarded shadowbox simulation as a refreshing and effective complement to immersive simulation. The format is distinct from other decision-making training approaches, such as Tactical Decision Games or case-based discussions, in that it systematically integrates expert rankings and rationales to make tacit knowledge visible in a structured, resource-efficient, and scalable way.

The study concludes that shadowbox simulation offers particular promise for developing non-technical or behavioural skills, supporting reflective learning, and widening access to simulation-based education. By synthesising evidence from outside healthcare, reviewing recent adaptations, and presenting the principles and outcomes of national implementation, the authors argue that shadowbox simulation represents a scalable, resource-efficient, theory-informed approach that advances current simulation practice. Future potential applications extending to leadership, delegation, and induction training across healthcare professions are discussed. The key ingredients of the method can be included in various quantities for different contexts and learners, allowing for flexibility in how expert mental models are engaged through videos and written materials.

The research highlights the importance of making expert cognition explicit in medical education, as it is often an opaque process for learners who may observe what is done without understanding how the expert has interpreted cues or prioritised competing concerns. By rendering those underlying cognitive moves visible, shadowboxing supports learners in understanding the reasoning processes that make adaptive and context-sensitive performance possible in challenging conditions. This approach is particularly salient in safety-critical settings, where fixation and premature closure can contribute to harm. The study demonstrates that by externalising expert judgement through structured rankings, rationales, and explicit comparison with learner responses, shadowbox simulation can help surface both intuitive and reflective aspects of expert judgement, including the cues, priorities, and moments of reconsideration that support safer decision-making.

Subject of Research: Implementation and evaluation of hybrid shadowbox simulation in medical education

Article Title: Into the light: the rise of shadowbox simulation to illuminate decision-making

Article References: Tallentire, V. R., Dick, L., Hart, R., Monro-Somerville, T., Clarke, B., & Allan, R. (2026). Into the light: the rise of shadowbox simulation to illuminate decision-making. Advances in Simulation, 11(1), Article 63. https://doi.org/10.1186/s41077-026-00450-x

Image Credits: AI Generated

DOI: 10.1186/s41077-026-00450-x

Keywords: shadowbox simulation, medical education, decision-making, cognitive transformation theory, naturalistic decision-making, Internal Medicine Training, simulation-based education, expert reasoning, non-technical skills, hybrid simulation format, clinical decision-making, learner feedback, psychological safety, tacit knowledge, Scottish healthcare