Investigating the Change in State Boredom After Completion of the Attentional Blink Paradigm
Bibliographic record
Abstract
Boredom is defined as an individual’s feeling of dissatisfaction with surroundings causing disengagement and discontentment with the present. State boredom is specifically boredom in the present moment, and has been theorized to be caused by attentional failures. State boredom is measured using the Multidimensional State Boredom Scale (MSBS), a 29- question scale scored using a 7-point Likert scale. There are 5 subscales in the MSBS: disengagement, high arousal, inattention, low arousal and time perception. This study focuses on the change in the subscale scores after attentional failures take place. This study uses the attentional blink paradigm to trigger attentional failures in participants to see how their state boredom changes after completing the paradigm. The attentional blink is a phenomenon that reflects the cognitive failure explaining the inability to identify a target when it is presented within 200-500ms of a previous target. Participants completed the MSBS before and after completing the attentional blink paradigm. A 2-factor repeated measures ANOVA showed a significant increase in state boredom for the disengagement and time perception subscales. A paired samples t-test also showed a strong attentional blink across both the lag positions and the participants. Overall, there was evidence of a significant increase in state boredom for disengagement and time perception after completion of the attentional blink paradigm.
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 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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".