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Record W2035587563 · doi:10.1167/8.6.15

Does the prolonged attentional blink to emotional stimuli affect driving performance?

2010· article· en· W2035587563 on OpenAlexaff
Lana M. Trick, Seneca Brandigampola, James T. Enns

Bibliographic record

VenueJournal of Vision · 2010
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsUniversity of British ColumbiaUniversity of Guelph
Fundersnot available
KeywordsArousalPsychologyDriving simulatorValence (chemistry)Stimulus (psychology)Attentional blinkBrakeEmotional valenceAffect (linguistics)AudiologyCognitive psychologySimulationSocial psychologyCognitionCommunicationComputer scienceEngineeringMedicineAutomotive engineeringNeuroscience

Abstract

fetched live from OpenAlex

The attentional blink is a temporary delay in responding to a second stimulus in a stream after attending to the first. Recent investigations suggest the duration of the attentional blink is longer after viewing pictures with a negative emotional valence (Most, Chen, & Widders, 2005) though this effect has never been demonstrated in a day-to-day task. This study investigated whether this extended attentional blink would have an impact on driving performance. Participants were tested in a DriveSafety DS-600c driving simulator (a full car body surrounded by six viewing screens that immersed drivers in a 300 degree wrap-around virtual driving environment). They were required to drive down a virtual highway, following a lead vehicle. During the 75 minute drive they were exposed to high and low arousal pictures from the International Affective Picture System (IAPS: Lang, Bradley, & Cuthbert, 2001), pictures that had either a positive or negative emotional valence. In most cases, participants would simply be required to indicate whether the picture was positive or negative while lane keeping performance was assessed. However, occasionally the lead-vehicle would brake unexpectedly, forcing the participant to brake. Braking response times after positive and negative pictures were compared to those in a baseline (no picture) control condition. Results have practical implications as they relate to the enhanced collision risk that may occur as the result of upsetting images displayed on billboards or on in-vehicle entertainment devices (e.g., onboard DVD players).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.709
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.379
Teacher spread0.360 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2010
Admission routes1
Has abstractyes

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