Impact of Childhood Maltreatment in Borderline Personality Disorder on Treatment Response to Intensive Dialectical Behavior Therapy
Bibliographic record
Abstract
Childhood maltreatment (CM), including emotional, physical, and sexual abuse and emotional and physical neglect, is associated with severity of borderline personality disorder (BPD). However, knowledge on the impact of CM on treatment response is scarce. The authors investigated whether self-reported CM or one of its subtypes affected treatment retention, depressive symptoms, and impulsivity throughout short-term intensive dialectical behavior therapy (I-DBT) in 333 patients with BPD. Data were analyzed with linear and logistic regressions and linear mixed models, using a Bayesian approach. Patients who reported childhood emotional abuse had a higher dropout rate, whereas it was lower in patients who reported childhood emotional neglect. Emotional neglect predicted a greater decrease of depressive symptoms, and global CM predicted a greater decrease of impulsivity. The authors concluded that patients with BPD who experienced CM might benefit from I-DBT in specific symptom domains. Nonetheless, the impact of emotional abuse on higher dropout needs to be considered.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.000 | 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 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".