How Do We Target NSSI in BPD? Exploring The Relationship Between Emotion Dysregulation, Interpersonal Dysfunction, And Non-Suicidal Self-Injury
Bibliographic record
Abstract
The current research investigated: 1) the trajectory of changes in emotion dysregulation, interpersonal dysfunction, and nonsuicidal self-injury (i.e., NSSI) over the course of DBT, and 2) whether changes in emotion dysregulation mediate the recovery of other features of BPD in treatment. Individuals with BPD (N = 120) enrolled in a multi-site study were assessed at five timepoints over 12 months of dialectical behaviour therapy (i.e., DBT). Results indicated that interpersonal dysfunction and NSSI decreased linearly over the course of DBT. Emotion dysregulation decreased in a quadratic manner; most of the gains in emotion dysregulation may occur in earlier phases of DBT. Results also revealed that although changes in emotion dysregulation was not a significant mediator of the relationship between changes in interpersonal dysfunction and in NSSI, changes in interpersonal dysfunction predicted changes in emotion dysregulation. Future research directions regarding NSSI, emotion dysregulation, and interpersonal dysfunction within DBT are discussed.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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 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".