Poor hazard recognition skills and high tolerance for risk are well-known contributing factors to high fatality rates plaguing the construction industry. The prevailing safety training techniques involve one-way delivery of slideshow presentations with written handouts that often describe common hazards and generic solutions. Such delivery does not facilitate active learning, development of contextual examples, or emotional engagement necessary for adult learners to gain new knowledge. To address these limitations, this paper proposes a new multimedia learning simulation-based training program called naturalistic injury simulation (NIS). Naturalistic injury simulation involves demonstrating the cause and effect of hand injuries using a hyperrealistic replica of a human hand within realistic scenarios. Out of 1,200 workers that participated, 489 workers were randomly selected for the quasi-field-based longitudinal experiment. Change in emotional states among the participants due to the simulations was analyzed across various demographical dimensions. Analysis showed that workers experienced a surge in negative emotions. Findings suggest that NIS will lead workers across the different demographical groups to perceive more risk by being more vigilant and detail oriented.

There is emerging evidence that emotional states can influence human decision making under uncertainty. However, it remains unclear if and how emotions influence people’ ability to recognize hazards, assess safety risk, and make decisions within an occupational safety context. Literature from construction safety, risk perception, and decision science domains was leveraged to create a conceptual model on the influence of incidental and integral emotions on hazard identification, risk assessment, and decision-making skills. The model was then tested via controlled laboratory experiment where participants ($N=73$ ) were placed in a high-fidelity augmented virtual construction environment. A mixed-model analyses revealed that contextually relevant emotional responses to the construction hazards modulated subsequent valuations of risk associated and ultimate safety decisions. However, no direct relationship was found between induced emotional states and hazard-identification performance. These results also provide preliminary evidence that emotions, not objective evaluations, may be the primary driver of safety-related decision making. The importance of these findings as they relate to improving safety training programs and well-being of the workforce is detailed in this paper.

Construction safety prediction is an emerging field where various forms of information and analytical techniques are used to predict the likelihood or severity of a future injury. A review of this literature reveals that even though the approaches are used for the same goal of predicting future safety outcomes, they are modeled independently and exclusively from one another. To organize thinking in safety prediction, the literature is organized into four operationally-defined predictive families: (1) safety risk assessment, which considers the characteristics and dangers of the work; (2) precursor analysis, which considers the conditions of the workers; (3) leading indicators, which consider the quantity of safety management activities; and (4) safety climate assessments, which considers worker perceptions of safety. Additionally, a unified model is proposed where the four families are considered together and opportunities for synergy and cross-validation are exploited. Researchers may benefit from this model as they create points of departure, propose and test novel approaches, and attempt to contextualize their findings within the existing body of literature. Furthermore, practitioners may use the model to make more accurate and robust safety predictions that account for the interconnectedness of the work attributes, human resources, and management strategies that affect safety.

Despite the development and implementation of intensive health and safety training programs, the construction industry still remains one of the most dangerous industries. To remain safe, workers must be able to effectively identify, value, and respond to dangers in their work environment. The sense of comfort or discomfort associated with a hazard (i.e., risk tolerance) can play a significant role in the propensity to engage in an unsafe behavior. However, it remains unclear if, and to what extent, risk tolerance in personal life is associated with risk tolerance at work or with the propensity to break safety rules at work. To address this knowledge gap, this research tested the hypotheses that personal risk tolerance influences both work-related risk tolerance and the propensity to break safety rules. These hypotheses were tested using linear mixed-effects models with data from a survey administered to 11,811 workers from 19 countries. Results indicated that personal risk-tolerance is positively associated with both work-related risk tolerance and risk-taking behavior. However, when controlling for demographic dimensions, the relationship between personal risk tolerance and risk-taking behavior was no longer significant. Practically, these results suggest that holistic training programs for reducing or calibrating safety risk tolerance should focus on personal life in addition to work, and the demographics and social interactions of the workers also should be considered when studying safety behavior.