Evidence map›Paper›PMID 37115493›Full record

ArticleAttention, perception & psychophysics2023

Psychometric curves reveal changes in bias, lapse rate, and guess rate in an online vigilance task.

Shannon P Gyles, Jason S McCarley, Yusuke Yamani

Abstract read
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In one paragraph

Article in Attention, perception & psychophysics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. An examination of sustained attention during complex multitasking scenarios.Cognitive research: principles and implications · 2025
    Article
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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

3 authors.

Shannon P GylesSchool of Psychological Science, Oregon State University, 2950 SW Jefferson Way, Corvallis, OR, 97331, USA. shannongyles@oregonstate.edu.ORCID http://orcid.org/0000-0001-5079-6033
Jason S McCarleySchool of Psychological Science, Oregon State University, 2950 SW Jefferson Way, Corvallis, OR, 97331, USA.ORCID https://orcid.org/0000-0002-8824-7491
Yusuke YamaniDepartment of Psychology, Old Dominion University, Norfolk, VA, USA.ORCID https://orcid.org/0000-0001-8990-0010

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

When human monitors are required to detect infrequent signals among noise, they typically exhibit a decline in correct detections over time. Researchers have attributed this vigilance decrement to three alternative mechanisms: shifts in response bias, losses of sensitivity, and attentional lapses. The current study examined the extent to which changes in these mechanisms contributed to the vigilance decrement in an online monitoring task. Participants in two experiments (N = 102, N = 192) completed an online signal detection task, judging whether the separation between two probes each trial exceeded a criterion value. Separation was varied across trials and data were fit with logistic psychometric curves using Bayesian hierarchical parameter estimation. Parameters representing sensitivity, response bias, attentional lapse rate, and guess rate were compared across the first and last 4 minutes of the vigil. Data gave decisive evidence of conservative bias shifts, an increased attentional lapse rate, and a decreased positive guess rate over time on task, but no strong evidence for or against an effect of sensitivity. Sensitivity decrements appear less robust than criterion shifts or attention lapses as causes of the vigilance loss.

Indexed as

AttentionPsychomotor PerformanceBayes TheoremHumansModafinilPsychometricsReaction TimeModafinilAttentionBayesian modelingSignal detection theory

Identifiers

PMID37115493

What OpenQuestion holds

Textmetadata
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.