The core vision of MATES in Construction centres on suicide prevention, which is supported by its mission to partner with industry and research institutions to better understand mental health and suicide-risk. An enhanced understanding of the precursors of mental health and suicide risk is needed to create intervention strategies aiming to improve them effectively. With this in mind, this study aimed to answer the question, “what combinations of work-related stressors are most likely to determine whether a worker will exhibit poor mental health?” To answer this question, we drew on survey responses obtained from 2,715 construction workers. The survey included questions about general mental health, and from this, we were able to classify workers as exhibiting higher levels of mental health (labelled “typical”) and lower levels of mental health (labelled “not-typical”). The survey also included a series of measures on work-related stressors, including high levels of work-related demands (e.g., role ambiguity and overload), low levels of work-related resources (e.g., supervisor support and job control), and past and future suicide ideation. Using Bayesian networks (BNs), we were able to explore connections between work-related stressors (high demands and low resources), general mental health, and past and future suicide ideation, with general mental health representing the target outcome variable.
