Crisis-related stimuli do not increase the emotional attentional blink in a general university student population
Bibliographic record
Abstract
Crises such as natural disasters or pandemics negatively impact the mental health of the affected community, increasing rates of depression, anxiety, or stress. It has been proposed that this stems in part from crisis-related stimuli triggering negative reactions that interrupt daily life. Given the frequency and prominence of crisis events, it is crucial to understand when crisis-related stimuli involuntarily capture attention and trigger increased stress and distraction from obligations. The emotional attentional blink (EAB) paradigm-in which emotional distractors hinder report of subsequent targets in streams of rapidly displayed stimuli-allows examination of such attentional capture in a rapidly changing dynamic environment. EABs are typically observed with generally disturbing stimuli, but stimuli related to personal traumas yield similar or greater effects, indicating strong attentional capture by stimuli related to individual trauma history. The current study investigated whether a similar comparable or increased crisis-related EAB exists within a community affected by large-scale crisis. Specifically, effects of conventional emotional distractors and distractors related to recent crises were compared using EABs in university students without a mental health diagnosis. Experiment 1 used images related to Hurricane Harvey, evaluating a crisis 4 years prior to data collection. Experiment 2 used words related to the COVID pandemic, evaluating an ongoing crisis at the time of data collection. In both experiments, the conventional EAB distractors yielded strong EABs, while the crisis-related distractors yielded absent or weak EABs in the same participants. This suggests that crisis-related stimuli do not have special potency for capturing attention in the general university student population. More generally, crises affecting communities do not necessarily yield widespread, strong reactivity to crisis-related stimuli.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".