Heart rate variability during a cognitive reappraisal task in female patients with borderline personality disorder: the role of comorbid posttraumatic stress disorder and dissociation
Bibliographic record
Abstract
BACKGROUND: Emotion dysregulation is a core feature of borderline personality disorder (BPD), which often co-occurs with posttraumatic stress disorder (PTSD). Difficulties in emotion regulation (ER) have been linked to lower high-frequency heart rate variability (HF-HRV), a measure of autonomous nervous system functioning. However, previous research on vagally-mediated heart rate in BPD revealed heterogeneous findings and the effects of comorbid PTSD and dissociation on HF-HRV are not yet completely understood. This study aim to investigate HF-HRV during resting-state and an ER task in female BPD patients with comorbid PTSD (BPD + PTSD), patients without this comorbidity (BPD), and healthy controls (HC). METHODS: 57 BPD patients (BPD: n = 37, BPD + PTSD: n = 20) and 27 HC performed an ER task with neutral, positive, and negative images. Participants were instructed to either attend these pictures or to down-regulate their upcoming emotions using cognitive reappraisal. Subjective arousal and wellbeing, self-reported dissociation, and electrocardiogram data were assessed. RESULTS: Independent of ER instruction and picture valence, both patient groups (BPD and BPD + PTSD) reported higher subjective arousal and lower wellbeing; patients with BPD + PTSD further exhibited significantly lower HF-HRV compared with the other groups. Higher self-reported state dissociation predicted higher HF-HRV during down-regulating v. attending negative pictures in BPD + PTSD. CONCLUSIONS: Findings suggest increased emotional reactivity to negative, positive, and neutral pictures, but do not provide evidence for deficits in instructed ER in BPD. Reduced HF-HRV appears to be particularly linked to comorbid PTSD, while dissociation may underlie attempts to increase ER and HF-HRV in BPD patients with this comorbidity.
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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 | 0.001 |
| 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".