The Integrated Workload Scale (IWS): A new self-report tool to assess railway signaller workload

Pickup, Laura; Wilson, John R.; Norris, Beverley; Mitchell, Lucy; Morrisroe, Ged

doi:10.1016/j.apergo.2005.05.004

Cited by 69 publications

(37 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Previous research has shown that unidimensional scales are better in providing a global rating of workload, while being easier and quicker to administer (Hendy et al, 1993;Pickup et al, 2005). In addition, subjective preferences of individual functions of both interfaces were assessed by a structured post-interview.…”

Section: Methodsmentioning

confidence: 99%

Combining situated Cognitive Engineering with a novel testing method in a case study comparing two infusion pump interfaces

et al. 2016

View full text Add to dashboard Cite

Section: Methodsmentioning

confidence: 99%

Combining situated Cognitive Engineering with a novel testing method in a case study comparing two infusion pump interfaces

et al. 2016

View full text Add to dashboard Cite

“…The Integrated Workload Scale (Pickup et al, 2005) was used to measure participants' perceived workload. This is a nine-point scale developed specifically to measure perceived mental workload in the signalling environment.…”

Section: Apparatus and Materialsmentioning

confidence: 99%

“…A high score on the IWS indicates a high workload. Pickup, Wilson, Norris, Mitchell, and Morrisroe (2005) report that this tool has proven to be a valuable measure of peaks and troughs in workload over time or within a set of scenarios. They also report that the tool is acceptable to signallers, having been developed specifically for use in the signalling environment, and maps well onto expected workload measured using other techniques.…”

Section: Apparatus and Materialsmentioning

confidence: 99%

Impact of automation: Measurement of performance, workload and behaviour in a complex control environment

2015

View full text Add to dashboard Cite

This paper describes an experiment that was undertaken to compare three levels of automation in rail signalling; a high level in which an automated agent set routes for trains using timetable information, a medium level in which trains were routed along pre-defined paths, and a low level where the operator (signaller) was responsible for the movement of all trains. These levels are described in terms of a rail automation model based on previous automation theory (Parasuraman, Sheridan, & Wickens, 2000). Performance, subjective workload, and signaller activity were measured for each level of automation running under both normal operating conditions and abnormal, or disrupted, conditions. The results indicate that perceived workload, during both normal and disrupted phases of the experiment, decreased as the level of automation increased and performance was most consistent (i.e. showed the least variation between participants) with the highest level of automation. The results give a strong case in favour of automation, particularly in terms of demonstrating the potential for automation to reduce workload, but also suggest much benefit can achieved from a mid-level of automation potentially at a lower cost and complexity. Impact StatementResearch in the area of automation, and in particular in the examination of human interaction with different levels of automation, has normally been undertaken in Balfe et al, Impact of Automation: Measurement of Performance, Workload and Behaviour in a Complex Control Environment 2 laboratory settings using simple tasks and naïve participants where the level of automation can be easily manipulated. This research was undertaken with expert participants using complex simulation of three ecologically valid levels of automation and provides empirical field validation of some of the results found in laboratory studies.

show abstract

“…Tailoring of existing artifacts to maximize information extraction can be related to the strategies 'prepare for future work' (Blandford and Furniss 2006) and 'cue creation in action' (Perin 2005), with the broader markers of 'preparation' and 'strategies that maximize information extraction' (Blandford and Furniss 2006). The awareness of (incoming) data limitations and the proactive steps taken at present (i.e., enhanced monitoring) increased the readiness to adequately respond to ongoing developments (efficient management of the performance variability) and provided the opportunity to anticipate and prepare for future situational demands.…”

Section: Resilience Behavior Episodesmentioning

confidence: 99%

“…In order to guide this process and enhance the efficiency, outcomes of real-time workload measurements were used to focus on situations in which train dispatchers experienced increased workload. Workload measurements were conducted using an automated version of the Integrated Workload Scale (IWS; Pickup et al 2005), a unidimensional self-report tool consisting of a 9-point scale in which 1 = not demanding and 9 = work too demanding, that enabled numerical entering of rail dispatchers' subjective workload at 5-min intervals. An interface was developed to display the 5-min interval entering of the subjective workload for all individual rail dispatchers and all individual workstations in real time (Fig.…”

Section: Resilience Observationsmentioning

confidence: 99%

Toward quantifying metrics for rail-system resilience: identification and analysis of performance weak resilience signals

2015

View full text Add to dashboard Cite

This paper aims to enhance tangibility of the resilience engineering concept by facilitating understanding and operationalization of weak resilience signals (WRSs) in the rail sector. Within complex socio-technical systems, accidents can be seen as unwanted outcomes emerging from uncontrolled sources of entropy (functional resonance). Various theoretical models exist to determine the variability of system interactions, the resilience state and the organization's intrinsic abilities to reorganize and manage their functioning and adaptive capacity to cope with unexpected and unforeseen disruptions. However, operationalizing and measuring concrete and reliable manifestations of resilience and assessing their impact at a system level have proved to be a challenge. A multimethod, ethnographic observation and resilience questionnaire, were used to determine resilience baseline conditions at an operational rail traffic control post. This paper describes the development, implementation and initial validation of WRSs identified and modeled around a 'performance system boundary.' In addition, a WRS analysis function is introduced to interpret underlying factors of the performance WRSs and serves as a method to reveal potential sources of future resonance that could comprise system resilience. Results indicate that performance WRSs can successfully be implemented to accentuate relative deviations from resilience baseline conditions. A WRS analysis function can help to interpret these divergences and could be used to reveal (creeping) change processes and unnoticed initiating events that facilitate emergence that degrades rail-system resilience. Establishing relevant change signals in advance can contribute to anticipation and awareness, enhance organizational learning and stimulate resilient courses of action and adaptive behavior that ensures rail operation reliability.

show abstract

The Integrated Workload Scale (IWS): A new self-report tool to assess railway signaller workload

Cited by 69 publications

References 15 publications

Combining situated Cognitive Engineering with a novel testing method in a case study comparing two infusion pump interfaces

Combining situated Cognitive Engineering with a novel testing method in a case study comparing two infusion pump interfaces

Impact of automation: Measurement of performance, workload and behaviour in a complex control environment

Toward quantifying metrics for rail-system resilience: identification and analysis of performance weak resilience signals

Contact Info

Product

Resources

About