INFORMATION TECHNOLOGY FOR ANALYSING AND QUANTIFYING THE EFFECTIVENESS OF VR TRAINING FOR FIRST AID SKILLS IMPROVEMENT IN EMERGENCIES BASED ON BEHAVIOURAL AND STATISTICAL MODELS

Abstract

Context. The study’s relevance stems from the urgent need to improve the effectiveness of prehospital first aid training under heightened risk to civilian populations, particularly in emergency scenarios involving damage to civilian infrastructure. Traditional training approaches are limited in their ability to realistically simulate hazardous situations, objectively monitor participants’ actions, and quantitatively analyse learning dynamics. Virtual reality (VR) technologies enable the creation of fully controlled and repeatable simulation environments with automated logging of temporal, behavioural, and performance-related parameters, providing new opportunities for objective assessment of training effectiveness.
Objective of the study is to develop and experimentally validate an information technology for the quantitative evaluation of VR-based training effectiveness in developing prehospital first aid skills, compared with traditional training methods.
Method. An experimental study was conducted using a controlled design with VR and control groups, including pre-test, posttest, and delayed retention measurements. Training effectiveness was evaluated using a set of quantitative metrics, including reaction time RT, action accuracy, number of critical errors, Precision, Recall, F1-score, and a composite performance score S. Learning dynamics were analysed using exponential learning curve models, mixed-effects models for repeated measurements, parametric and non-parametric statistical tests, bootstrap confidence intervals, and effect size estimation (Cohen’s d).
Results demonstrate a statistically confirmed advantage of VR-based training over traditional methods. The average reaction time for critical actions in the VR group was reduced by approximately 10–20% compared to the control group (e.g., 34 seconds vs. 40 seconds in bleeding control scenarios). Action accuracy increased from approximately 0.78 in the control group to 0.86 in the VR group, corresponding to an improvement of about 8–10%. The composite performance score S was higher in the VR group by 0.05–0.12 (on a 0–1 scale), depending on the scenario. F1-scores for automated action classification reached 0.90–0.92, and large effect sizes were observed, with Cohen’s d values up to approximately 2.3. Retention testing further indicated improved stability and long-term preservation of skills following VR-based training.
Conclusions. The proposed information technology and experimental results support the use of VR as an effective, scalable, and data-driven approach for prehospital first aid training for civilians, emergency responders, and medical personnel in emergency and disaster-response contexts.