The development and validation of a short-duration sustained visual search task for process control environments.


Journal

Applied ergonomics
ISSN: 1872-9126
Titre abrégé: Appl Ergon
Pays: England
ID NLM: 0261412

Informations de publication

Date de publication:
Feb 2021
Historique:
received: 12 03 2018
revised: 21 10 2020
accepted: 29 10 2020
pubmed: 10 11 2020
medline: 28 7 2021
entrez: 9 11 2020
Statut: ppublish

Résumé

This study was designed to validate a short-duration sustained visual search task for the assessment of sustained attention in process control environments. The task consists of 10 short dynamic scenarios, which require participants (N = 121) to monitor simulated operating power transmission interfaces, and identify system faults. A vigilance decrement was demonstrated throughout the sustained visual search task, as evident in increased response latencies and decreased accuracy over time. Further, changes in response latency throughout the sustained visual search task were positively associated with changes in response latency during a 30-min, low signal probability task, a 45-min low signal probability task, and a 45-min high signal probability task. The findings indicate that the sustained visual search task may be a valid alternative to a longer-duration process control task for experimental studies, and is likely to be of value for assessments of the capacity for sustained attention of operators in process control environments.

Identifiants

pubmed: 33166915
pii: S0003-6870(20)30250-7
doi: 10.1016/j.apergo.2020.103302
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

103302

Informations de copyright

Copyright © 2020. Published by Elsevier Ltd.

Auteurs

Daniel Sturman (D)

Macquarie University, NSW, Australia. Electronic address: daniel.sturman@adelaide.edu.au.

Mark W Wiggins (MW)

Macquarie University, NSW, Australia.

William S Helton (WS)

George Mason University, VA, United States.

Jaime C Auton (JC)

Macquarie University, NSW, Australia.

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Classifications MeSH