Multimodal assessment of emotional reactivity and regulation in response to social rejection among self-harming adults with and without borderline personality disorder.
Bibliographic record
Abstract
Theories of borderline personality disorder (BPD) highlight the central role of emotional dysfunction in this disorder, with a particular emphasis on emotional reactivity and emotion regulation (ER) difficulties. However, research on emotion-related difficulties in BPD has produced mixed results, often related to the particular indices of emotional responding used in the studies. As such, the specific nature of emotional dysfunction in BPD, as well as the extent to which subjective emotion-related difficulties map onto corresponding physiological deficits, remains unclear. This study examined both subjective and physiological indices of emotional reactivity and ER difficulties in response to a social rejection emotion induction (relative to a neutral emotion induction) across three groups of participants: self-harming young adults with BPD, self-harming young adults without BPD, and clinical controls with no self-harm history or BPD. Consistent with the hypotheses, results revealed a lack of convergence between subjective and physiological indices of emotional reactivity and ER difficulties among participants with BPD. Whereas participants with BPD reported both greater emotional reactivity and greater ER difficulties in response to the negative emotion induction than participants without self-harm or BPD, there were no significant differences in physiological indices of emotional reactivity or ER between participants with BPD and either of the control groups. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.002 |
| 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) | 0.001 | 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".