Browsing by Department "Department of Biomedical Science"

Road traffic accidents are increasingly recognised as a serious public health concern. Each year road traffic accidents cause 1.2 million deaths worldwide and the number is expected to increase by 65 percent in 20 years. One of the challenges to solving this issue is that many accident investigation studies employed methods that gave less emphasis on systemic factors of road traffic accidents such as enforcement and government policies but rely on a direct cause-effect chain to analyse an accident causation process. By contrast, more contemporary approaches of investigating accidents are based on systemic accident models that can be used to analyse the interactions between various components of a sociotechnical system. Different systemic accident models, however, can lead to different analyses and subsequently different conclusions. As such, this study sought to compare three different systemic accident models, namely, the Driving Reliability and Error Analysis Method (DREAM), System-Theoretic Accident Model and Process (STAMP), and AcciMap in analysing the accident causation process of the 2013 Genting Highlands Bus Crash, which was the deadliest road traffic accident in Malaysia. Using DREAM, this study found that most of the contributing factors originated from maintenance errors and road design issues. On the other hand, STAMP identified inadequate controls and flaws within the road transportation system as contributing factors while AcciMap indicated various direct and indirect factors across different levels within the system. Findings of this study suggest that DREAM can present the accident factors in a succinct graphical representation by using a classification system thus making it easy to carry out and simple to understand. In addition, although both AcciMap and STAMP analyse road traffic accident across different system levels, STAMP is more comprehensive and flexible. However, because STAMP is time consuming and complex, it is more suitable for analyzing major road traffic accidents.