Assessing cross-modal interference in the detection response task

Thorpe, Alexander; Innes, Reilly J.; Townsend, James T.; Heath, Rachel A.; Nesbitt, Keith; Eidels, Ami

doi:10.1016/j.jmp.2020.102390

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…Several recent studies have considered the influence the operators workload context plays on processing capacity. Thorpe et al (2020) found increasing load within a task led to impaired processing capacity (measured using a novel continuous-to-discrete variation of capacity analysis) in that same task. Conversely, Morey et al (2018b) and Morey, Thomas and McCarley (2018a) found no evidence that processing efficiency (measured by standard capacity and resilience functions; Houpt & Townsend, 2012) in a secondary task, consisting of redundant, peripherally displayed targets, changed with the addition or difficulty of a primary task.…”

Section: Context Effectsmentioning

confidence: 95%

“…Conversely, Morey et al (2018b) and Morey, Thomas and McCarley (2018a) found no evidence that processing efficiency (measured by standard capacity and resilience functions; Houpt & Townsend, 2012) in a secondary task, consisting of redundant, peripherally displayed targets, changed with the addition or difficulty of a primary task. There is a key distinction between the studies in that Thorpe et al (2020) did not consider capacity within a dual task environment, where attention must be split between the primary and peripheral components. Thus, to-date, there is no evidence that primary task workload impairs processing capacity to a peripherally presented task.…”

Section: Context Effectsmentioning

confidence: 99%

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Switch It Up! How Context Influences the Efficiency of Redundancy Gains in a Peripheral Task

2022

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Optimizing the time and accuracy with which peripheral tasks can be monitored concurrent with a central primary task is of paramount importance for human factors researchers developing human systems. Nonetheless, the design of peripheral task are often evaluated in isolation, and their effectiveness is assumed to generalize to multi-task contexts. Our work acknowledges that peripheral displays may be utilized in a variety of operational contexts. Across four experiments we examine peripheral task detection speeds under several contextual factors related to operator workload and task-set. We use the capacity coefficient from the Systems Factorial Technology framework to quantify the extent that context influences redundant signal enhancements in a peripheral detection task. Across four experiments we manipulated the presence, difficulty and stability of the primary task to simulate different workload contexts.Using a novel time-varying estimate of workload capacity, we show that efficiency in detecting redundant peripheral targets decreases with high primary task demands, contrary to previous findings. Our results also indicated higher capacity in less stable environments but a correspondingly greater workload impairment in these conditions.Implications for system design include consideration of the expected operator workload, as well as attention recruiting strategies to improve peripheral task detection speeds.

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Section: Context Effectsmentioning

confidence: 95%

Section: Context Effectsmentioning

confidence: 99%

Switch It Up! How Context Influences the Efficiency of Redundancy Gains in a Peripheral Task

2022

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“…Generalizing to a dual-task context, Thorpe et al (2020) found a single highly salient peripheral signal typically leads to faster response times (RTs) and higher detection rates. Further, recent work set in a dual-task context demonstrates processing efficiency to a single peripherallypresented visual signal is reduced and cognitive processing strategies shift under high demands (Howard, Evans, et al, The Quantitative Methods for Psychology 2020; Garrett et al, 2019).…”

Section: Context Dependencementioning

confidence: 99%

Influence of dual-task load on redundant signal processes

Fox¹,

Cook²,

Yang³

et al. 2023

TQMP

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In high demand contexts, uni-or multi-modal signals are used to convey redundant information and improve performance. This is especially the case with improving the detection of discrete peripheral signals. However, how one processes peripheral signals may change depending on the greater environmental context. The underlying cognitive processing of signals is important to determine how they may influence the degree to which each signal enhances, as opposed to slows down, detection. Until now, it was unclear if i) the introduction of, or increased difficulty of, a second task changes how people combine peripheral signals (that is, in a parallel, serial, or coactive fashion) and ii) if processing efficiency depends on the salience of the peripheral signals or the presence/difficulty of a centrally located and continuous tracking task. This manuscript describes an application of Systems Factorial Technology to investigate the cognitive processing mechanisms of redundant signals in the context of a multiple object tracking (MOT) task. The MOT task load (track 0, 1, or 4 dots) and the salience of peripheral signals (bright, dim) were manipulated. The data indicate peoples' processing of peripheral signals changed depending on the MOT task load. Under a high MOT task load, most people processed redundant signals in a parallel fashion. Alternatively, nearly half of people processed the signals in a serial fashion when asked to simultaneously track 0 or 1 dot. Implications for the use and design of redundant signals in multi-task contexts that vary in task demands are discussed.

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