Callum Pearse

Callum Pearse

Fourth-year medical student, King’s College London · Surgical research · Surgical education & robotics

Alongside my studies, I contribute to research in surgical education and objective assessment of operative performance, with interests spanning robotic skill acquisition, simulation-based training, and workforce wellbeing.

Systematic reviews & meta-analysis Surgical education Robotics Workforce wellbeing

About

I am a fourth-year medical student at King’s College London with an academic interest in surgical research, surgical education, and technology-enabled training. I am particularly interested in methods that allow robust, objective assessment of technical performance and learning curves in robotic surgery.

My work includes evidence synthesis in workforce wellbeing and robotic training, and I am keen to contribute to projects that translate methodological rigour into practical improvements in training and service sustainability.

Research focus

  • Robotic surgical skill acquisition and objective performance assessment
  • Simulation-based training and cross-platform skill transferability
  • Evidence synthesis (systematic reviews, meta-analysis)
  • Clinician wellbeing and workforce sustainability in surgery

Research outputs

Journal articles

Assessing Effectiveness and Skill Transferability in Multi-Platform Simulated Training for Robotic Surgical Skills: A Systematic Review
Journal of Robotic Surgery · 2025 · DOI: 10.1007/s11701-025-03090-x

Systematic review evaluating cross-platform skill transferability across robotic systems in simulated settings, with implications for training design and transition between platforms.

Burnout among paediatric surgeons: a systematic review and meta-analysis
BMJ Paediatrics Open · 2025 · DOI: 10.1136/bmjpo-2025-004030

Systematic review and meta-analysis estimating burnout prevalence in paediatric surgery and synthesising associated risk and protective factors.

Conference Papers, Posters & Presentations

Precision in Motion: Objective Hand-Tracking Kinematic Metrics Correlate With Reviewer-Assessed Robotic Surgical Skill – A Pilot Longitudinal Study
Accepted oral presentation · ASiT Annual Conference (Manchester) · 6–8 March 2026

Pilot longitudinal study examining whether objective hand-tracking kinematic metrics correlate with expert reviewer assessments of robotic surgical skill.

Acquisition and analysis of a multimodal dataset for skill evaluation across two robotic surgical systems
Conference poster · 22nd Meeting of the EAU Robotic Urology Section (London) · 2025 · DOI: 10.1016/s2666-1683(25)00543-9

Multimodal dataset capturing kinematic and complementary data streams across two robotic surgical platforms to support objective skill evaluation and performance analytics.

Bimanual Dexterity as an Objective Marker of Robotic Surgical Expertise for a Machine Learning Model
Conference poster · RCSEd Triennial & ICOSET Conference (Edinburgh) · 2025

Poster exploring bimanual dexterity metrics as an objective marker of robotic expertise to inform machine-learning based performance modelling.

Hands On: A Comparative Analysis of Left- and Right-Hand Workspaces in Surgical Robotic Skills Training
Conference paper · Hamlyn Symposium of Medical Robotics (London) · 2025

Comparative analysis of left- and right-hand workspaces in robotic skills training to support targeted practice design and assessment.

Contact

For academic collaboration or research enquiries: