Attention control mediates the relationship between mental imagery vividness and emotion regulation
Bibliographic record
Abstract
• Imagery vividness may both protect against and exacerbate negative affect. • Considering attention control may reconcile these past mixed findings. • Attention control mediated a positive relationship between imagery and reappraisal. • Imagery vividness predicted decreases in negative affect via attention control. • Imagery vividness facilitates adaptive outcomes when paired with attention control. Contradictory findings suggest mental imagery may both exacerbate and protect against negative affect. We aimed to reconcile these contradictory findings by considering individual differences ( N =989) in imagery vividness, attention control, resilience, emotion regulation strategy, and negative affect (depressive, anxious, and posttraumatic stress symptomology). We hypothesized that attention control would mediate relationships between imagery vividness and emotion regulation strategy use, and psychopathology symptomology. Results revealed that imagery vividness, as mediated by attention control, predicted greater levels of healthy reappraisal and deleterious rumination. Attention control also mediated negative relationships between imagery vividness and catastrophizing, self-blame, and psychopathology symptomology. An exploratory latent structural equation model revealed that imagery vividness and attention control aggregated positively with reappraisal and resilience scores. The present investigation suggests an adaptive function of imagery vividness via the indirect effects of attention control, facilitating adaptive emotion regulation and limiting maladaptive strategy use, thereby protecting against negative affect.
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 | 0.001 | 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".