A negative bias in decoding positive social cues characterizes emotion processing in patients with symptom-remitted Borderline Personality Disorder
Bibliographic record
Abstract
BACKGROUND: Impairments in the domain of interpersonal functioning such as the feeling of loneliness and fear of abandonment have been associated with a negative bias during processing of social cues in Borderline Personality Disorder (BPD). Since these symptoms show low rates of remission, high rates of recurrence and are relatively resistant to treatment, in the present study we investigated whether a negative bias during social cognitive processing exists in BPD even after symptomatic remission. We focused on facial emotion recognition since it is one of the basal social-cognitive processes required for successful social interactions and building relationships. METHODS: Ninety-eight female participants (46 symptom-remitted BPD [r-BPD]), 52 healthy controls [HC]) rated the intensity of anger and happiness in ambiguous (anger/happiness blends) and unambiguous (emotion/neutral blends) emotional facial expressions. Additionally, participants assessed the confidence they experienced in their own judgments. RESULTS: R-BPD participants assessed ambiguous expressions as less happy and as more angry when the faces displayed predominantly happiness. Confidence in these judgments did not differ between groups, but confidence in judging happiness in predominantly happy faces was lower in BPD patients with a higher level of BPD psychopathology. CONCLUSIONS: Evaluating social cues that signal the willingness to affiliate is characterized by a negative bias that seems to be a trait-like feature of social cognition in BPD. In contrast, confidence in judging positive social signals seems to be a state-like feature of emotion recognition in BPD that improves with attenuation in the level of acute BPD symptoms.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".