Adapting the task-taxon-task methodology to model the impact of chemical protective gear

Simpkins, Benjamin G.; Anno, G.H.; Fallon, Corey K.; Price, Owen; McClellan, Gene E.

doi:10.1007/s10588-011-9093-7

Cited by 10 publications

(10 citation statements)

References 31 publications

(26 reference statements)

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“…The stressors placed on healthcare professionals through their work environment and the added burden of wearing personal protective equipment are cumulative. 7 The "Task-Taxon-Task" method can be used to develop a predictive model of how physiologic and psychologic stressors can interact to impair a practitioner's ability to function in the clinical environment. 7 This model assumes that each task uses a measurable set of skills taxons, and environmental stressors cause a decrement in each skill by a measurable amount.…”

Section: Special Articlementioning

confidence: 99%

COVID-19, Personal Protective Equipment, and Human Performance

Ruskin

Musselman

et al. 2021

Anesthesiology

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Clinicians who care for patients infected with coronavirus disease 2019 (COVID-19) must wear a full suite of personal protective equipment, including an N95 mask or powered air purifying respirator, eye protection, a fluid-impermeable gown, and gloves. This combination of personal protective equipment may cause increased work of breathing, reduced field of vision, muffled speech, difficulty hearing, and heat stress. These effects are not caused by individual weakness; they are normal and expected reactions that any person will have when exposed to an unusual environment. The physiologic and psychologic challenges imposed by personal protective equipment may have multiple causes, but immediate countermeasures and long-term mitigation strategies can help to improve a clinician’s ability to provide care. Ultimately, a systematic approach to the design and integration of personal protective equipment is needed to improve the safety of patients and clinicians.

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Section: Special Articlementioning

confidence: 99%

COVID-19, Personal Protective Equipment, and Human Performance

Ruskin

Musselman

et al. 2021

Anesthesiology

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“…to modeling psychological and cognitive impacts of protective clothing (Mueller et al 2011), the use of fuzzy cognitive mapping techniques to model situation awareness (Jones et al 2011), and the challenge of exploration and optimization of cognitive models (Moore 2011). Overall, they represent how the 2010 conference addressed modeling from small-scale models, for example, predicting eye movements, to largescale parameter exploration using high-performance computing facilities.…”

mentioning

confidence: 99%

Behavioral representation in modeling and simulation: introduction to CMOT special issue—BRiMS 2012

Best

Kennedy

Amant

2015

Comput Math Organ Theory

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The BRiMS Society and Conference (Behavioral Representation in Modeling and Simulation (BRiMS, brimsconference.org) promote cross-disciplinary communication for basic and applied scientific research in the realm of modeling and simulation of human behavior, with a particular emphasis on defense government-related tasks and behavior. Thus, the BRiMS conference brings together scientists, engineers, practitioners, and application users to discuss modeling behavior ranging from that of individuals to the behavior of whole societies, their interactions, and their implications. For a few days each year, we get to meet to share ideas and experiences, identify gaps in current capabilities, discuss new directions, highlight promising technologies, and showcase applications.This special issue is similar to our previous special issue ( Kennedy et al. 2010) in that it includes four papers based on the award winning conference papers of the 2010 annual conference, reviewed and extended to journal article length. The papers include a new model integrating top-down and bottom-up factors affecting visual target acquisition (Jungkunz and Darken 2011), the application of a statistical methodology

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“…IE was developed by Ashby (1978, 1983) to measure energy consumption over time and the power of energy systems, and it is popularly used as a method to summarize both RTs and accuracy simultaneously in cognitive psychology. One interpretation of IE (see Mueller, Simpkins, Anno, Fallon, Price, & McClellan, 2011) is that it provides a total work throughput for the system, assuming zero error recovery costs and fixed-time completion costs: A task that takes 1 min with 100 accuracy is equivalent to a task that takes 40 s with 2/3 chance of succeeding on each try, since the latter on average will take 60 s to complete. However, some research suggests that IE scores should not be the only independent measure regarded in experimental psychology, because the ratio used will produce large variances that make them difficult to interpret (Bruyer & Brysbaert, 2011), and this is especially true for situations such as ours, with relatively few trials per condition and some low accuracy (Akhtar & Enns, 1989).…”

Section: Combining Time and Accuracy: Inverse Efficiencymentioning

confidence: 99%

Adapting cultural mixture modeling for continuous measures of knowledge and memory fluency

Tan

2015

Behav Res

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Previous research (e.g., cultural consensus theory (Romney, Weller, & Batchelder, American Anthropologist, 88, 313-338, 1986); cultural mixture modeling (Mueller & Veinott, 2008)) has used overt response patterns (i.e., responses to questionnaires and surveys) to identify whether a group shares a single coherent attitude or belief set. Yet many domains in social science have focused on implicit attitudes that are not apparent in overt responses but still may be detected via response time patterns. We propose a method for modeling response times as a mixture of Gaussians, adapting the strong-consensus model of cultural mixture modeling to model this implicit measure of knowledge strength. We report the results of two behavioral experiments and one simulation experiment that establish the usefulness of the approach, as well as some of the boundary conditions under which distinct groups of shared agreement might be recovered, even when the group identity is not known. The results reveal that the ability to recover and identify shared-belief groups depends on (1) the level of noise in the measurement, (2) the differential signals for strong versus weak attitudes, and (3) the similarity between group attitudes. Consequently, the method shows promise for identifying latent groups among a population whose overt attitudes do not differ, but whose implicit or covert attitudes or knowledge may differ.

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Adapting the task-taxon-task methodology to model the impact of chemical protective gear

Cited by 10 publications

References 31 publications

COVID-19, Personal Protective Equipment, and Human Performance

COVID-19, Personal Protective Equipment, and Human Performance

Behavioral representation in modeling and simulation: introduction to CMOT special issue—BRiMS 2012

Adapting cultural mixture modeling for continuous measures of knowledge and memory fluency

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