Pretest Scores Uniquely Predict 1-Year-Delayed Performance in a Simulation-Based Mastery Course for Central Line...

Area of Science:

• Medical Education
• Simulation-Based Training
• Skill Acquisition

Background:

• Simulation-based mastery learning (SBML) courses often omit pretesting due to resource constraints.
• Pretesting may offer benefits like deliberate practice and personalized learning pathways.
• The predictive value of pretesting for long-term learner performance in SBML is underexplored.

Purpose of the Study:

• To investigate the potential of pretest scores to predict long-term learner performance in central line insertion using SBML.
• To determine if pretest scores offer predictive value beyond other common metrics like program year and experience.

Main Methods:

• Twenty-seven residents underwent central line insertion training via SBML.
• Participants were assessed pre-course, immediately post-course, and 64-82 weeks later.
• Statistical analysis examined the correlation between pretest scores and delayed test scores, controlling for other variables.

Main Results:

• Pretest scores strongly predicted delayed test scores (r = 0.59, P = 0.01).
• The number of central lines inserted also correlated with delayed scores (r = 0.44, P = 0.02), but pretest remained a significant predictor in regression analysis (β = 0.487, P = 0.011).
• Program year and immediate posttest scores did not significantly predict long-term performance.

Conclusions:

• Pretesting is a significant predictor of long-term learning gains in SBML.
• Results suggest a need for targeted refresher training based on pretest performance.
• Relying solely on immediate mastery in SBML may mask disparities in long-term skill retention.