How do you choose and how well does it work?: the selection and effectiveness of emotion regulation strategies and their relationship with borderline personality disorder feature severity
Bibliographic record
Abstract
There is little research examining whether the selection of emotion regulation strategies is compromised among individuals characterised by emotion dysregulation. In a sample of 149 undergraduates, we examined the selection and effectiveness of 2 emotion regulation strategies (reappraisal or distraction) in response to emotionally evocative stimuli, and their relationship with emotion dysregulation, measured by borderline personality disorder (BPD) feature severity. Stimulus intensity and self-reported negative emotional intensity were also compared as predictors of strategy selection. Results indicated that self-reported negative emotional intensity was a stronger predictor of strategy selection than stimulus intensity, and participants generally selected reappraisal over distraction. However, increases in self-reported negative emotional intensity was associated with an increased likelihood of choosing distraction, particularly among individuals higher in BPD features. In general, distraction exhibited less effectiveness than reappraisal, and higher BPD features did not differentially impact such effectiveness. Our findings indicate that individuals higher in emotion dysregulation prefer to use distraction as self-reported negative emotional intensity increases, a strategy which, overall, may not be as effective as reappraisal. Selection, rather than effectiveness of emotion regulation strategy might be a key feature of individuals characterised by emotion dysregulation.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".