Evidence map›Paper›PMID 38247319›Full record

ReviewHuman factors2024

Adopting Stimulus Detection Tasks for Cognitive Workload Assessment: Some Considerations.

Francesco N Biondi

Abstract readReview
In one paragraph

Review in Human factors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Francesco N BiondiUniversity of Windsor, Canada.ORCID 0000-0002-5558-4707

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis article tackles the issue of correct data interpretation when using stimulus detection tasks for determining the operator's workload.

backgroundStimulus detection tasks are a relative simple and inexpensive means of measuring the operator's state. While stimulus detection tasks may be better geared to measure conditions of high workload, adopting this approach for the assessment of low workload may be more problematic.

methodThis mini-review details the use of common stimulus detection tasks and their contributions to the Human Factors practice. It also borrows from the conceptual framework of the inverted-U shape model to discuss the issue of data interpretation.

resultsThe evidence being discussed here highlights a clear limitation of stimulus detection task paradigms.

conclusionThere is an inherent risk in using a unidimensional tool like stimulus detection tasks as the primary source of information for determining the operator's psychophysiological state. APPLICATION: Two recommendations are put forward to Human Factors researchers and practitioners dealing with the interpretation conundrum of dealing with stimulus detection tasks.

Indexed as

CognitionTask Performance and AnalysisWorkloadErgonomicsHumansautomated driving systemsautomationdetection response taskDrowsinessFatigueISO DRTpsychomotor vigilance taskPVTresponse timesstimulus detection taskvigilanceworkload

Identifiers

PMID38247319
PMCPMC11475934

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.