(SELF): A FRAMEWORK FOR SELF-DIRECTED PROCEDURAL TRAINING catherine.mohr@intusurg.com

 

(SELF): A FRAMEWORK FOR SELF-DIRECTED PROCEDURAL TRAINING

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United States

Oral only

Surgical and anesthesia care remains inaccessible to nearly five billion people worldwide, contributing to preventable disability and mortality. Existing training pathways fail to meet the global need for procedural competence, especially in low-resource settings. The Surgical Education Learners Forum (SELF) was established to address this gap by developing cost-effective, scalable, and self-directed training modules for surgical and critical care practitioners.

In 2023, over 40 global medical, educational, and technology leaders convened at the SELF Symposium to formalize the SELF training framework. The consensus-building process followed a modified nominal group technique to distill expert input into a shared approach for module development. The SELF framework consists of three core components: structured knowledge acquisition, simulation-based practice using locally sourced materials, and self-administered skills assessment (SASA), enabling learners to independently evaluate procedural competence without instructor oversight.

Participants produced six consensus manuscripts for training module developers on SASA, simulator fidelity, digital delivery platforms, module prioritization, research methodology, and theory of change. The framework has since guided the development and evaluation of modules targeting diverse procedural skills, from laparoscopic surgery to hemorrhage control. Early results show that learners can attain clinical competence through these modules in resource-constrained environments.

The SELF framework offers a practical, evidence-informed model for delivering procedural training at scale. By supporting self-directed learning and integrating assessment into simulation, it equips practitioners to safely expand their skills in low-resource settings. SELF represents a promising strategy to help close the global surgical training gap.