Prioritize longitudinal studies tracking trainees from simulation to real-world surgical performance¶

Strategy · All strategies
Evidence · 2 claims (2 for) · 1 study (1 review), q3 · 0 of 1 report an effect size · 2 claims rest on one study

Description¶

The review recommends that future research prioritize longitudinal designs connecting simulation-based learning with operative outcomes. The authors state: "Future research should prioritize longitudinal studies that track the progression of trainees from simulation-based learning to real-world surgical performance, ensuring that these tools provide meaningful educational value beyond the simulated environment." This strategy addresses the sparse transferability evidence identified in the review.

Design Implications¶

Context¶

Requirements¶

• Objective proficiency metrics to complement subjective assessments

Constraints¶

• Current evidence base lacks standardized objective metrics, complicating widespread implementation

Target Learners¶

• neurosurgery trainees
• neurosurgery residents

Target Learning Goals¶

• surgical skill acquisition
• transfer of training to operative performance

Claims¶

• Most reviewed simulation studies demonstrated face and content validity, but few assessed construct or predictive validity [+W]
• Evidence for transfer of simulation training to operating-room outcomes was sparse in neuro-oncological simulation research [+W]

Related Strategies¶

• Develop standardized simulation-based leadership curricula with longitudinal evaluation and multi-center randomized comparison of formats
• Prioritize multicenter, randomized designs with standardized reporting and longitudinal follow-up in future surgical education research
• Research agenda: standardize reporting, run comparative efficacy studies, and track longitudinal transfer to clinical practice
• Combine objective metrics with validated subjective tools and audio-visual recording to contextualize interpretation of surgical performance data
• Prioritize larger multi-center RCTs with standardized AR systems, uniform metrics, and long-term follow-up when evaluating AR surgical training
• Validate automated video analytics and reach metric consensus before widespread adoption in surgical training
• Prioritize operational-setting protocols, longitudinal expertise tracking, team dynamics, and real-time monitoring as next steps for educational neuroimaging
• Evaluate mental practice with longitudinal mixed-method designs in real clinical teams, and embed MP in organisational routines such as pre-surgical briefings

Examples¶

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Key Sources¶

• Menna Grazia, Riva Dora, Marino Salvatore, Garber Jocelyn, Gerritsen Jasper Kees Wim, Mattogno Pier Paolo, Young Jacob Stewart, Olivi Alessandro, Doglietto Francesco, Berger Mitchel Stuart, Della Pepa Giuseppe Maria. (2025). Simulation tools in neuro-oncological surgery: a scoping review of perioperative and training applications. Journal of Neuro-Oncology. https://doi.org/10.1007/s11060-025-04972-8