Development of semi-quantitative model for occupational stress risk assessment matrix at port terminal in Penang, Malaysia

The port sector is a subsystem of the supply chain and is considered vital in Malaysia. Occupational stress is increasing among port employees due to a high-risk working environment. Risk assessment is the first step in identifying any potential risk or flaw related to OHS issues and supporting decision-making in OHS implementation to decrease ill health issues. While legislation establishes rules for risk assessment, employers often lack adequate guidance and are exposed to psychosocial issues such as occupational stress. The main objective of this study is to develop a risk matrix model that is primarily focused on occupational stress. The model will be designated the Occupational Stress Risk Assessment Matrix (OSRAM), and it will have three dimensions: Likelihood (L), Severity (S), and Control Modification Factor (CMF). This approach was used to identify hazards and determine the initial and residual risk associated with risk factors that contributed to occupational stress. A cross sectional survey was conducted in Penang port terminal, resulting in the selection of 310 respondents from a total population of 380 using a simple random sample approach that met inclusion and exclusion criteria. The processes consisted of two stages. Specifically, the first phase comprised the collecting of baseline data, and the second phase involved the development of a risk assessment matrix applying a semi-quantitative methodology approach. Additionally, SPSS version 25.0 and SPSS AMOS were performed to examine all data from the Socio-Demographic Survey, Job Content Questionnaire (JCQ), and Occupational Health Safety Monitoring Questionnaire (OHSMQ). The OSRAM technique was used to determine the probability of a hazard, the severity of the hazard, and the CMF of the assessed activities linked with this risk factor. The statistical analysis included descriptive analysis, chi-square, structural equation modelling (SEM), and paired sample t-test analysis. The response rate was 98 percent as a result. The sociodemographic distribution was studied, and age was shown to be significantly associated with occupational stress (p = 0.03). Job strain was found to be prevalent in 68.8 percent of cases. The majority of occupational stress risk factors are strongly associated with occupational stress, and SEM analysis proves that a modest risk contributed to occupational stress. OSRAM was constructed as a 5x5 matrix containing STRESSOR dimensions, severity level, and CMF. The five risk categories are very low (VL), low (L), moderate (M), high (H), and extremely high (EH), with a score ranging from one to twenty-five. OSRAM was applied in a container port, and the majority of hazards analysed indicated a reduction in the risk level associated with the eight selected activities. A comparison has been made between OSRAM and present RAM, as well as the stress scale. As a result, a significant link between OSRAM and the current matrix was discovered, with a p value less than 0.05. According to the stress scale, all work activities were deemed significant. The OSRAM responds more accurately than existing RAM as a risk estimator. In conclusion, OSRAM has established itself as a critical OHS risk assessment instrument, particularly in the Malaysian port industry.

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