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Objective: Using eye tracking technology, this study sought to determine if differences in hazard statement (HS) compliance based on design elements are attributable to attention maintenance (AM). Background: Recent empirical work has demonstrated counter-intuitive findings for HS designs embedded in procedures. Specifically, prevalent HS designs in procedures were associated with lower compliance. Method: The current study utilized eye tracking technology to determine whether participants are attending to HSs differently based on the inclusion or absence of visually distinct HS design elements typically used for consumer products. We used two different designs that previously yielded the largest gap in HS compliance. In a fully-crossed design, 33 participants completed four rounds of tasks using four procedures with embedded HSs. To assess AM, eye tracking was used to measure gaze and fixation duration. Results: The results indicated there are differences in AM between the two designs. The HSs that included elements traditionally considered effective in the consumer products literature elicited lower fixation duration times, and were associated with lower compliance. However, AM did not mediate the design effect on compliance. Conclusions: The study results suggest the design of HSs are impacting individuals as early as the AM stage of the C-HIP model. The absence of HS design-AM-compliance mediation suggests other C-HIP elements more directly explain the HS design-compliance effects. Application: These results provide more evidence that the communication of Health, Environment, and Safety information in procedures may need to be different from those on consumer products, suggesting design efficacy may be task dependent. [ABSTRACT FROM AUTHOR]

Interaction has been recognised as an essential lens to understand how cognition is formed in a complex adaptive team such as a multidisciplinary crisis management team (CMT). However, little is known about how interactions within and across CMTs give rise to the multi-team system's overall cognitive functioning, which is essential to avoid breakdowns in coordination. To address this gap, we characterise and compare the component CMTs' role-as-intended (RAI) and role-as-observed (RAO) in adapting to the complexity of managing informational needs. To characterise RAI, we conducted semi-structured interviews with subject matter experts and then made a qualitative synthesis using a thematic analysis method. To characterise RAO, we observed multiteam interaction networks in real-time at a simulated training environment and then analysed the component CMTs' relative importance using node centrality measures. The resulting inconsistencies between RAI and RAO imply the need to investigate cognition in multiple CMTs through the lens of interaction. Practitioner summary: When a disaster occurs, multidisciplinary CMTs are expected to serve their roles as described in written or verbal guidelines. However, according to our naturalistic observations of multiteam interaction networks, such descriptions may be (necessary but) insufficient for designing, training, and evaluating CMTs in the complexity of managing informational needs together. [ABSTRACT FROM AUTHOR]

Objective: The objective of these studies was to identify hazard statement (HS) design elements in procedures that affected whether both workers and lab participants performed the associated hazard mitigation. Background: Many of the incidents in high-risk industries are the result of issues with procedures (e.g., standard operating procedures; SOPs) workers use to support their performance. HSs in these procedures are meant to communicate potential work hazards and methods of mitigating those hazards. However, there is little empirical research regarding whether current hazard design guidelines for consumer products translate to procedures. Method: Two experimental studies—(1) a laboratory study and (2) a high-fidelity simulation—manipulated the HS design elements present in procedures participants used while performing tasks. Participants' adherence to the mitigation of the hazard was compared for the HS designs. Results: The guidelines for HSs from consumer products did not translate to procedures. Specifically, the presence of an alert icon, a box around the statement, and highlighting the statement did not improve adherence to HSs. Indeed, the only consistent finding was for the Icon, with its presence reliably predicting nonadherence in both studies. Additionally, the total number of design elements did not have a positive effect on adherence. Conclusion: These findings indicate that more fundamental procedure HSs research is needed to identify effective designs as well as to understand the potential attentional mechanisms associated with these findings. Application: The findings from these studies indicate that current regulations and guidelines should be revisited regarding hazard presentation in procedures. [ABSTRACT FROM AUTHOR]

Resilience is an important attribute of incident management teams (IMTs) for managing disasters. Previous research on resilience of IMTs has focused on comparing work-as-imagined (WAI) and work-as-done (WAD) but predominantly used narrative analyses which limited comparisons between IMTs. This paper presents a novel Interaction Episode Analysis (IEA) method to identify the IMT's WAI and WAD episodes by analyzing dynamic interactions that occur between different roles that carry out information management tasks. Observations and audio--visual recordings of two high-fidelity IMT exercises were conducted to capture WAD episodes, and semi-structured interviews with experts elicited corresponding WAI episodes. Quantitative analyses using five interaction-based measures were conducted to detect differences of the WAD episodes between two IMTs. Next, qualitative analyses were focused on identifying reasons why such differences have occurred by comparing the gaps between WAI and WAD episodes. Some of the reasons for WAI-WAD gaps included the non-occurrence of critical interactions that were expected and occurrence of unexpected interactions between IMT members. This paper also identifies cases of preparatory, proactive, and reactive performance adjustment that characterizes IMT resilience. The IEA method shows promise for investigating how and why the gaps between WAI and WAD in IMTs occur. With the identification of these gaps, future research can be conducted to reconcile the gaps between WAI and WAD episodes, and thus enhance resilience of IMTs in future disasters. [ABSTRACT FROM AUTHOR]

Objective: The goal of this study is to assess machine learning for predicting procedure performance from operator and procedure characteristics. Background: Procedures are vital for the performance and safety of high-risk industries. Current procedure design guidelines are insufficient because they rely on subjective assessments and qualitative analyses that struggle to integrate and quantify the diversity of factors that influence procedure performance. Method: We used data from a 25-participant study with four procedures, conducted on a high-fidelity oil extraction simulation to develop logistic regression (LR), random forest (RF), and decision tree (DT) algorithms that predict procedure step performance from operator, step, readability, and natural language processing-based features. Features were filtered using the Boruta approach. The algorithms were trained and optimized with a repeated 10-fold cross-validation. After training, inference was performed using variable importance and partial dependence plots. Results: The RF, DT, and LR algorithms with all features had an area under the receiver operating characteristic curve (AUC) of 0.78, 0.77, and 0.75, respectively, and significantly outperformed the LR with only operator features (LROP), with an AUC of 0.61. The most important features were experience, familiarity, total words, and character-based metrics. The partial dependence plots showed that steps with fewer words, abbreviations, and characters were correlated with correct step performance. Conclusion: Machine learning algorithms are a promising approach for predicting step-level procedure performance, with acknowledged limitations on interpolating to nonobserved data, and may help guide procedure design after validation with additional data on further tasks. Application: After validation, the inferences from these models can be used to generate procedure design alternatives. [ABSTRACT FROM AUTHOR]