Faces of Oppression: Future directions for Ergonomics and Human Factors.

The growing interest in Diversity, Equity, and Inclusion (DEI) centred work in the field of Ergonomics and Human Factors (EHF) can greatly benefit from Iris Young's Five Faces of Oppression theory, which details how well-intentioned systems can perpetuate harm in a number of ways. We call for a greater focus on systems of oppression in EHF research and practice along with increased collaboration with social sciences to tackle important societal issues. This article reviews the current state of research in the child welfare domain and provides examples for how cognitive engineering approaches can take inspiration from the social sciences to help create a more equitable future. These examples outline the potential mutualism between social sciences and EHF and the way this collaboration might dismantle various oppressive systems.

EHF work is often situated within sociotechnical systems that can generate oppression, or injustices imposed on social groups by societal structures. This publication shows the value that social science frameworks and literature can bring to EHF practice by supporting a more nuanced understanding of these systems of oppression.

Cell phone-related driver distraction: Habits predict behavior over and above the theory of planned behavior variables.

INTRODUCTION: Habits have often been overlooked in studies investigating cell phone-related driver distractions. This paper examines the association between habits and cell phone-related driver distractions within a mediation model based on the Theory of Planned Behavior (TPB). Additionally, it explores potential differences in behaviors across urban and rural driving environments and between males and females. METHOD: We conducted an online survey in China with 1,016 respondents, measuring attitudes, subjective norms, perceived behavioral control, self-reported behavior, and habits associated with cell phone use while driving. RESULTS: Data was analyzed using a two-stage structural equation modeling approach. Results indicate that the measurement model provided a good fit to the data and was invariant across urban and rural driving environments, as well as across genders. The latent path model investigating mediation also demonstrated a good fit and revealed that TPB variables (attitudes, subjective norms, and perceived behavioral control) partially mediated the relationship between cell phone-related habits and cell phone use while driving. The structural model was invariant across driving environments but not across genders, for which the extent of the differences were limited. Moreover, habits were strongly associated with subjective norms and perceived behavioral control, emerging as the strongest predictor of cell phone-related distractions. CONCLUSIONS: The findings suggest that habits should be considered in research on phone-related distracted driving behaviors and in the development of intervention designs.

Testing Senders' Visual Occlusion Model: Do Operators (Drivers) Really Predict During Visual Occlusion?

OBJECTIVE: The present study tests the hypothesis that humans are capable of predicting the state of a system during visual occlusion, an assumption often made in models of sampling behaviour, but seldom tested. BACKGROUND: In 1967, John Senders introduced the visual occlusion paradigm to evaluate attentional demand of tasks such as automobile driving. Despite multiple studies employing this paradigm, the concept of operators actually being able to resolve uncertainty during occlusion by predicting system output has remained unvalidated. METHOD: A self-paced visual occlusion monitoring task was contrived, involving a randomly rotating basin with a ball at the bottom. Participants were required to detect critical events (ball falling off the edge) while looking only as often as subjectively deemed necessary. Assuming the need to resolve uncertainty imposed by the random rotations, we examined relations between occlusion durations and system states preceding occlusion, for different glance durations, to infer whether predicting may have taken place. RESULTS: Results suggested that glance requests were consistent with the use of simple first order predictions. This pertained not only for longer (300 and 500 ms) glances, but even for 100 ms glances whenever critical events were imminent. CONCLUSION: The presumption that human operators are capable, under certain circumstances, of predicting system state in the absence of visual information appears feasible; however, glance duration plays an important role. APPLICATIONS: By providing support for some of its basic premises, the use of Senders' visual occlusion paradigm as a potential tool for evaluating human monitoring performance has been strengthened.

Opportunities and Recommendations for Improving Medication Safety: Understanding the Medication Management System in Primary Care Through an Abstraction Hierarchy.

BACKGROUND: Despite making great strides in improving the treatment of diseases, the minimization of unintended harm by medication therapy continues to be a major hurdle facing the health care system. Medication error and prescription of potentially inappropriate medications (PIMs) represent a prevalent source of harm to patients and are associated with increased rates of adverse events, hospitalizations, and increased health care costs. Attempts to improve medication management systems in primary care have had mixed results. Implementation of new interventions is difficult because of complex contextual factors within the health care system. Abstraction hierarchy (AH), the first step in cognitive work analysis (CWA), is used by human factors practitioners to describe complex sociotechnical systems. Although initially intended for the nuclear power domain and interface design, AH has been used successfully to aid the redesign of numerous health care systems such as the design of decision support tools, mobile patient monitoring apps, and a telephone triage system. OBJECTIVE: This paper aims to refine our understanding of the primary care office in relation to a patient's medication through the development of an AH. Emphasis was placed on the elements related to medication safety to provide guidance for the design of a safer medication management system in primary care. METHODS: The AH development was guided by the methodology used by seminal CWA literature. It was initially developed by 2 authors and later fine-tuned by an expert panel of clinicians, social scientists, and a human factors engineer. It was subsequently refined until an agreement was reached. A means-ends analysis was performed and described for the nodes of interest. The model represents the primary care office space through functional purposes, values and priorities, function-related purposes, object-related processes, and physical objects. RESULTS: This model depicts the medication management system at various levels of abstraction. The resulting components must be balanced and coordinated to provide medical treatment with limited health care resources. Understanding the physical and informational constraints on activities that occur in a primary care office depicted in the AH defines areas in which medication safety can be improved. CONCLUSIONS: Numerous means-ends relationships were identified and analyzed. These can be further evaluated depending on the specific needs of the user. Recommendations for optimizing a medication management system in a primary care facility were made. Individual practices can use AH for clinical redesign to improve prescribing and deprescribing practices.

Voluntary- and Involuntary-Distraction Engagement: An Exploratory Study of Individual Differences.

Objective The aim of this study was to explore individual differences in voluntary and involuntary driver-distraction engagement. Background Distractions may stem from intentional engagement in secondary tasks (voluntary) or failing to suppress non-driving-related stimuli or information (involuntary). A wealth of literature has examined voluntary distraction; involuntary distraction is not particularly well understood. Individual factors, such as age, are known to play a role in how drivers engage in distractions. However, it is unclear which individual factors are associated with voluntary- versus involuntary-distraction engagement and whether there is a relation between how drivers engage in these two distraction types. Method Thirty-six participants, ages 25 to 39, drove in a simulator under three conditions: voluntary distraction with a self-paced visual-manual task on a secondary display, involuntary distraction with abrupt onset of irrelevant visual-audio stimuli on the secondary display, and no distraction. Results The number of glances toward the secondary display under voluntary distraction was not correlated to that under involuntary distraction. The former was associated with gender, age, annual mileage, and self-reported distraction engagement; such associations were not observed for the latter. Accelerator release time in response to lead-vehicle braking was delayed similarly under both conditions. Conclusion Propensity to engage in voluntary distractions appears to be not related to the inability of suppressing involuntary distractions. Further, voluntary and involuntary distraction both affect braking response. These findings have implications for design of in-vehicle technologies, which may be sources of both distraction types.

What drives technology-based distractions? A structural equation model on social-psychological factors of technology-based driver distraction engagement.

BACKGROUND: With the proliferation of new mobile and in-vehicle technologies, understanding the motivations behind a driver's voluntary engagement with such technologies is crucial from a safety perspective, yet is complex. Previous literature either surveyed a large number of distractions that may be diverse, or too focuses on one particular activity, such as cell phone use. Further, earlier studies about social-psychological factors underlying driver distraction tend to focus on one or two factors in-depth, and those that examine a more comprehensive set of factors are often limited in their analyses methods. OBJECTIVE: The present work considers a wide array of social-psychological factors within a structural equation model to predict their influence on a focused set of technology-based distractions. A better understanding of these facilitators can enhance the design of distraction mitigation strategies. METHOD: We analysed survey responses about three technology-based driver distractions: holding phone conversations, manually interacting with cell phones, and adjusting the settings of in-vehicle technology, as well as responses on five social-psychological factors: attitude, descriptive norm, injunctive norm, technology inclination, and a risk/sensation seeking personality. Using data collected from 525 drivers (ages: 18-80), a structural equation model was built to analyse these social-psychological factors as latent variables influencing self-reported engagement in these three technology-based distractions. RESULTS: Self-reported engagement in technology-based distractions was found to be largely influenced by attitudes about the distractions. Personality and social norms also played a significant role, but technology inclination did not. A closer look at two age groups (18-30 and 30+) showed that the effect of social norms, especially of injunctive norm (i.e., perceived approvals), was less prominent in the 30+ age group, while personality remained a significant predictor for the 30+ age group but marginally significant for the younger group. CONCLUSION: Findings from this work provide insights into the social-psychological factors behind intentional engagement in technology-based distractions and in particular suggesting that these factors may be sensitive to demographic differences.