“Some Kind of Magic?” How Adaptive Experts Navigate Complexity in Pediatric Ultrasound-Guided Vascular Access
Bibliographic record
Abstract
Introduction: Technological innovations hold great promise for enhancing clinical practice, especially in high-stakes settings. Although simulation-based education can help to develop skill proficiency, transferring skills into real-world high-stakes settings remains challenging. By investigating 'super-users'-exceptional performers who have successfully implemented new technologies in demanding contexts-this study zooms in on ultrasound-guided vascular access (UGVA) in young, awake, and often non-compliant children and aims to unravel complexities and strategies for successful performance in complex contexts. Methods: Using a constructivist grounded theory approach, sensitized by concepts from expertise theory, we conducted incident-based interviews with 11 experts in pediatrics. Results: Two main results were identified through theoretical sampling, thematic and conceptual analysis, and constant comparison within a multidisciplinary research team. First, participants described multiple, intersecting dimensions of complexity: conceptual, psychomotor, contextual, and educational. Second, experts articulated their largely tacit knowledge and collaborative dynamics for navigating these complexities metaphorically. Successful pediatric UGVA was likened to a "choreography", where "orchestration" of dynamic socio-material aspects was perceived to yield "some kind of magic" engagement and synergy of the collective. Discussion: This study's conceptualization of dynamic, high-stakes, and morally charged performance reflects adaptive expertise and illustrates how motor skill expertise is intertwined with cognitive, social, and contextual aspects. Hence, in helping to demystify the "magic" in expert performance, this work discusses insights to advance adaptive expertise theory and motor learning theory, particularly on how to prepare future adaptive experts for the inherent complexities and transfer challenges of procedural performance in clinical practice. The findings underscore the need for training approaches that move beyond routine skill acquisition towards dynamic, context-rich learning environments that foster perceptual-motor adaptability, collaborative coordination, and moral readiness for high-stakes performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".