Executive functions and social cognition in highly lethal self-injuring patients with borderline personality disorder.
Bibliographic record
Abstract
Risk for potentially lethal self-injurious behavior in borderline personality disorder (BPD) may be associated with deficits in neuropsychological functions and social cognition. In particular, individuals with BPD engaging in more medically damaging self-injurious behaviors may have more severe executive function deficits and altered emotion perception as compared to patients engaging in less lethal acts. In the current study, 58 patients with BPD reporting a lifetime history of self-injurious behavior were administered neuropsychological measures of response inhibition, planning and problem-solving,and tests of facial emotion recognition and discrimination. Patients who engaged in more medically lethal self-injurious behaviors reported engaging in impulsive behaviors more frequently and displayed neuropsychological deficits in problem-solving and response inhibition. They were also less accurate in recognizing happy facial expressions and in discerning subtle differences in emotional intensity in sad facial expressions. These findings suggest that patients with BPD that engage in more physically damaging self-injurious behaviors may have greater difficulties with behavioral control and employ less efficient problem-solving strategies. Problems in facial emotion recognition and discrimination may contribute to interpersonal difficulties in patients with BPD who self-injure.
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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 | 0.001 | 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".