Development of a Human Factors Approach to Equine-Related Human Accident Analysis, and Preliminarily Evaluation with Simulated Incidents

Abstract

Accident analysis frameworks such as Human Factors Analysis and Classification System (HFACS) are widely used in high-risk industries to determine risk mitigation strategies. In comparison, equestrianism which is classified high-risk due to human-horse interactions at work, sport, and social activities, rarely utilizes accident analysis. This study developed and tested the validity and inter-rater reliability of an equestrian-specific accident analysis framework, that included elements of human error, horse risk factors, and environmental factors. The study involved three coders who independently classified 10 simulated horse-related human accident reports with the novel Human Factors Analysis and Classification System-Equestrianism (HFACS-Eq) framework. The results demonstrated that the HFACS-Eq framework achieved moderately reliable to reliable coding percentage agreement. In addition, substantial to reliable agreement was achieved for HFACS-Eq nominal category and nano-codes levels. This study is the first step towards an equestrian industry-specific, accident analysis framework to improve industry safety. Elimination of possible bias and validation with real incident data are required before the wider application of the framework can be recommended. The study highlights organizational and procedural failures, segregating the horse as a contributing factor as well as the environment in which the human acts or makes decisions informing risk.