The Impact of Higher Levels of Automation on Performance and Situation Awareness

Jipp, Meike; Ackerman, Phillip L.

doi:10.1177/1555343416637517

Cited by 31 publications

(7 citation statements)

References 61 publications

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“…In our previous study examining the associations between neuropsychological tests and driving ability in healthy older people, lower working memory function was associated with greater risk of unsafe driving ( Yamamoto et al, 2020 ). Furthermore, working memory has been reported to be associated with a driver’s ability to retain traffic information for several seconds ( Da-Wei et al, 2017 ) and predict traffic conditions ( Jipp and Ackerman, 2016 ). Considering that our final model identified the cortical regions involved in cognitive functions essential for driving, such as voluntary orienting of attention, decision making, and working memory, as important inputs, the current study provides new insights into the neural basis of driving behavior.…”

Section: Discussionmentioning

confidence: 99%

Regional Gray Matter Volume Identifies High Risk of Unsafe Driving in Healthy Older People

Yamamoto

Yamagata

Hirano

et al. 2020

Front. Aging Neurosci.

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In developed countries, the number of traffic accidents caused by older drivers is increasing. Approximately half of the older drivers who cause fatal accidents are cognitively normal. Thus, it is important to identify older drivers who are cognitively normal but at high risk of causing fatal traffic accidents. However, no standardized method for assessing the driving ability of older drivers has been established. We aimed to establish an objective assessment of driving ability and to clarify the neural basis of unsafe driving in healthy older people. We enrolled 32 healthy older individuals aged over 65 years and classified unsafe drivers using an on-road driving test. We then utilized a machine learning approach to distinguish unsafe drivers from safe drivers based on clinical features and gray matter volume data. Twenty-one participants were classified as safe drivers and 11 participants as unsafe drivers. A linear support vector machine classifier successfully distinguished unsafe drivers from safe drivers with 87.5% accuracy (sensitivity of 63.6% and specificity of 100%). Five parameters (age and gray matter volume in four cortical regions, including the left superior part of the precentral sulcus, the left sulcus intermedius primus [of Jensen], the right orbital part of the inferior frontal gyrus, and the right superior frontal sulcus), were consistently selected as features for the final classification model. Our findings indicate that the cortical regions implicated in voluntary orienting of attention, decision making, and working memory may constitute the essential neural basis of driving behavior.

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Section: Discussionmentioning

confidence: 99%

Regional Gray Matter Volume Identifies High Risk of Unsafe Driving in Healthy Older People

Yamamoto

Yamagata

Hirano

et al. 2020

Front. Aging Neurosci.

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“…Compared to other employees, Yves will consequently spend less cognitive resources and he will perceive the thinking that he is doing as fairly low. Other employee related moderating variables include, e.g., differences in working memory capacity (Jipp and Ackerman 2016), dexterity (Mayer and Sims 1994;Pillay 1997), technological literacy (cf., Venkatesh et al 2003), experience, motivation and personality differences in, e.g., conscientiousness (Guastello et al 2014), tendency to worry (Grassmann et al 2017) and coping style (Hart and Staveland 1988;Young et al 2014). Also, Yves could have had the possibility to, on his own initiative, consult assistive technology indicating matching assembly parts as well.…”

Section: Two Antecedents Are Identified (Cognitive Work Demands and Tmentioning

confidence: 99%

Understanding mental workload: from a clarifying concept analysis toward an implementable framework

et al. 2018

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The growing need for mental workload (MWL) optimization on the shop floor yields an impressive increase in theoretical and applied references to the concept of mental workload (Young et al. 2014). However, do we really understand and agree upon what mental workload exactly is? Does it include emotional load? Can we rely upon an explanatory framework? The present account first runs a critical concept analysis on mental workload, based on the Walker and Avant (2011) method. Results show that existing definitions and theoretical accounts arbitrarily include and exclude defining variables and describe these variables on various levels of abstraction, misuse pivotal terms such as mediation and moderation, and do not theoretically explicitate the role of yet repeatedly operationalized emotional load variables such as frustration. We therefore clarify the concept by disentangling MWL into its antecedents, defining attributes and consequences. Next, we derive a clearcut conceptual definition and present a generic explanatory frameworkthe latter extended with insights from Cognitive Load Theory (Sweller 1988; 1994). We conclude with a set of suggestions for future research and practice. Next to contributing to the theoretical clarification of this hallmark concept, the concept analysis and derived explanatory framework, as proposed, can foster solid research practices and support practitioners in contextualizing MWL-assessment and in effectively optimizing MWL.

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“…All results included in the meta-analysis, even those with a repeated measures experimental design, analysed relationships among SA and performance by treating the data as betweenparticipants through either, 1) averaging, or 2) separate analyses to avoid overfitting. For example, Jipp and Ackerman (2016) assessed SA and performance 12 times for each participant (three levels of automation x four trials each) in a simulated air traffic control task. The authors correlated the average SA and average performance by participant (across the 12 trials).…”

Section: Repeated Measures Designs and Overfittingmentioning

confidence: 99%

The validity of situation awareness for performance: a meta-analysis

Bakdash

Marusich

Cox

et al. 2021

Theoretical Issues in Ergonomics Science

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Major changes in version 4 of the preprint: We added additional information and analyses in response to reviewers.-Item 1: Conclusions too strong? (R1). In the response letter, we describe how metaanalysis typically permits stronger and more generalizable inferences than narrative reviews and individual studies. -Item 2: Value of meta-analysis in general? (R2). Note that Bakdash et al. 2020 is a critique of an existing synthesis, but not a meta-analysis in its own right. The critique points out the need for a correctly-implemented, quantitative meta-analysis based on systematic review, a gap filled by the current work. We also clarify the scientific value of meta-analysis in the response letter (also see Item 1). -Item 3: Clarify prediction interval (R3). We revised the explanation and added equations.-Item 4: Drawn relevant connections (R2 and R3). We have drawn connections in the Discussion to relevant literature/fields suggested by R2 and R3We also had several minor corrections to the data: we corrected the sample sizes in two papers (Albina, 2019 [N = 30 to N = 28]; Onal et al. 2014 [N = 94 to N = 95]), added coding for a second experiment in one paper where all effects were previously coded as a single experiment (Lafond et al. 2012), and excluded one paper that does not appear to have assessed SA-performance associations (Dong et al. 2003). The meta-analysis now has 678 effects from 77 papers.Major changes in version 3 of the preprint: New systematic review from scratch, better detection and exclusion of overfit results (excessive degrees of freedom), meta-analysis now has 682 effects from 78 papers, new draw method for estimating ghost results, and analyses of proportions of effects below three meaningful thresholds. The validity of situation awareness for performance: A meta-analysisSituation awareness (SA) is a widely used cognitive construct in human factors, often theoretically posited to be a critical causal factor and/or construct for performance.However, there are concerns that SA may not sufficiently capture the psychological processes underlying performance. We address these conflicting perspectives using metaanalysis to evaluate the patterns of associations among SA-performance effect sizes.Specifically, we focus on the validity of SA for performance-how well SA captures the relevant psychological processes for task performance. In our systematic review of the empirical literature, we coded associations of ten unique measures of SA with performance: 678 effects from 77 papers. The meta-analytic means for SA measures were all of approximately medium or lower effect sizes. The overall mean effect, while significant, was also limited in magnitude (r = 0.26, p < 0.001). Furthermore, there was high unexplained systematic variation with an enormous plausible range for individual effects (r = -0.15 to 0.60). The results indicate that SA's validity for performance tends to be, on average, weak with large variations among effects. Interventions that improve SA may not correspond to meaningful improvement...

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The Impact of Higher Levels of Automation on Performance and Situation Awareness

Cited by 31 publications

References 61 publications

Regional Gray Matter Volume Identifies High Risk of Unsafe Driving in Healthy Older People

Regional Gray Matter Volume Identifies High Risk of Unsafe Driving in Healthy Older People

Understanding mental workload: from a clarifying concept analysis toward an implementable framework

The validity of situation awareness for performance: a meta-analysis

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