Analysis of behaviors exemplified by clinicians utilizing an online pediatric peritoneal dialysis simulator
OA Version
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Abstract
BACKGROUND: Peritoneal dialysis (PD) is a critical treatment modality for pediatric patients with end-stage renal disease (ESRD), yet many healthcare providers have limited exposure to hands-on PD training. The OPENPediatrics PD simulator was designed to address this educational gap by providing an interactive learning platform for clinicians.SPECIFIC AIMS: This study aimed to analyze learner behavior within the PD simulator to identify gaps in knowledge, engagement trends, and commonly missed clinical concepts. By using the widely known educational framework Design Thinking, we aimed to evaluate learner activity to further refine and inform future simulator design improvements.
METHODS: We conducted a retrospective analysis of learner clickstream data from the PD simulator, capturing engagement metrics, diagnosis selection, and action performance. We categorized learner actions into three key areas: Dialysis Prescription, Electrolyte Issues, and Mechanical Adjustments. Descriptive statistics were used to describe trends in learner behavior and knowledge gaps.
RESULTS: 1,283 learners accessed the simulator worldwide, with 14% of learners completing all sections. Learners spent an average 49 minutes in the simulator. As metrics of active engagement, we observed that 10-28% of learners viewed the entire videos in the Knowledge Guide section, and 4-26% of learners scrolled to the bottom of lessons or end of case summaries suggesting they read the entire text. The category of tactics that was easiest for learners to diagnose on the first attempt was ‘Dialysis Prescription’, and the most difficult was ‘Mechanical Adjustments’. The category of tactics that was easiest for learners to treat on the first attempt was ‘Mechanical Adjustments’ and the most difficult was ‘Dialysis Prescription’.
CONCLUSION: This analysis provides an in-depth analysis of learner behaviors, helping to identify areas of strength and weakness to further inform the development of future PD educational offerings. Using the Design Thinking framework, this analysis or testing phase will inform next phases in the iterative cycle to craft future iterations of the simulator.
Description
2025