Boredom proneness is predicted by difficulties in emotion regulation that are mediated by corresponding problems with attention and cognitive flexibility
Bibliographic record
Abstract
The association between boredom proneness and elevated rates of problematic substance abuse, gambling, and smartphone use has been taken as evidence that difficulties with emotion regulation can lead to maladaptive attempts to cope with negative affect. There is minimal research on how individual differences in emotion regulation may be linked to boredom proneness. We therefore sought to identify specific aspects of emotion regulation that may be helpful for predicting boredom proneness. We hypothesized that boredom proneness may be associated with aspects of emotion regulation that are often unproductive (e.g., suppression and rumination) or that rely on effective executive functions (e.g., attention, working memory, cognitive flexibility). Undergraduate students (N = 219) completed a battery of self-report scales regarding their boredom proneness, emotion-regulation abilities, and cognitive abilities, including attention, memory and cognitive flexibility. Results indicated that difficulties in emotion regulation predicted boredom proneness and was mediated by attentional difficulties and lower levels of cognitive flexibility, but not memory failures. Individual differences in emotion-suppression and rumination were predictive of boredom proneness, but the use of distraction was not. Our results underscore the importance of specific cognitive-affective mechanisms of emotion regulation to better understand boredom proneness and its long-term consequences.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".