Mining Recurring Themes in Firefighter Decision-Making: An LDA Topic Modeling Analysis

The research on firefighter decision-making has expanded over the years, but the findings are scattered, and gaps persist in understanding the factors affecting the cognitive performance of firefighters. Hence, it is essential to reveal the latent cognitive, physical, and operational factors in firefighter decision-making. This study employs Latent Dirichlet Allocation (LDA) topic modeling to analyze firefighter decision-making by mining themes from abstracts of 57 research articles. The findings revealed eight distinct topics, each characterized by 10 keywords. Thematic analysis of the topics revealed four major clusters: (1) the effect of safety and training on decision-making, (2) the effect of overall health on firefighter performance, (3) the influence of stress on decision-making, and (4) expertise in firefighter decision-making. Findings provide a thorough understanding of current research trends and inform training design and future research in firefighter decision-making.