A randomized trial of brief dialectical behaviour therapy skills training in suicidal patients suffering from borderline disorder
Bibliographic record
Abstract
OBJECTIVE: Evidence-based therapies for borderline personality disorder (BPD) are lengthy and scarce. Data on brief interventions are limited, and their role in the treatment of BPD is unclear. Our aim was therefore to evaluate the clinical effectiveness of brief dialectical behaviour therapy (DBT) skills training as an adjunctive intervention for high suicide risk in patients with BPD. METHOD: Eighty-four out-patients were randomized to 20 weeks of DBT skills (n = 42) or a waitlist (WL; n = 42). The primary outcome was frequency of suicidal or non-suicidal self-injurious (NSSI) episodes. Assessments were conducted at baseline 10, 20 and 32 weeks. RESULTS: DBT participants showed greater reductions than the WL participants on suicidal and NSSI behaviours between baseline and 32 weeks (P < 0.0001). DBT participants showed greater improvements than controls on measures of anger, distress tolerance and emotion regulation at 32 weeks. CONCLUSIONS: This abbreviated intervention is a viable option that may be a useful adjunctive intervention for the treatment of high-risk behaviour associated with the acute phase of BPD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".