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Record W2135269363 · doi:10.1002/cpp.1956

Assertive Anger Mediates Effects of Dialectical Behaviour‐informed Skills Training for Borderline Personality Disorder: A Randomized Controlled Trial

2015· article· en· W2135269363 on OpenAlexaff
Uëli Kramer, Antonio Pascual‐Leone, Laurent Berthoud, Yves de Roten, Pierre Marquet, Stéphane Kolly, Jean‐Nicolas Despland, Dominique Le Page

Bibliographic record

VenueClinical Psychology & Psychotherapy · 2015
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversity of Windsor
FundersUniversité de Lausanne
KeywordsPsychologyAngerAssertivenessBorderline personality disorderRandomized controlled trialClinical psychologyDialectical behavior therapyPersonalityPsychotherapistSocial psychologyMedicine

Abstract

fetched live from OpenAlex

UNLABELLED: Dialectical behaviour therapy (DBT)-informed skills training for borderline personality disorder (BPD) aims at the development of specific emotion regulation skills in patients, particularly with regard to the regulation of problematic anger. While the effects of dialectical behaviour skills training have been shown, their processes of change are rarely examined. Neacsiu, Rizvi and Linehan (2010) found that patient's self-reported use of emotion regulation skills was a mediator of therapeutic change in these treatments; however, they found no effect for problematic anger. From an integrative perspective on anger (Pascual-Leone & Greenberg, 2007; Pascual-Leone & Paivio, 2013), there are several forms of anger, varying in their degree of therapeutic productivity. The present add-on randomized controlled trial included n = 41 patients with BPD (n = 21 DBT-informed skills training versus n = 20 treatment as usual). The first study examined the outcome of the DBT-informed skills training encompassing basic components of training in mindfulness, distress tolerance, interpersonal effectiveness and emotion regulation. Results showed that symptom reduction was significantly greater in the DBT-informed skills training, compared with the treatment as usual. The second study used process assessment, for which all patient completers underwent a 50-min-long psychological interview both early and late in treatment, which was rated using the Classification of Affective Meaning States. DBT-informed skills training produced increased levels of primary 'assertive' anger, as compared with the treatment as usual, whereas no effect was found for 'rejecting' secondary anger. Most importantly, we showed that changes in assertive anger mediated the reported symptom reduction, in particular in patient's social roles. We discuss these results in the context of underlying mechanisms of change in DBT skills group treatments, in particular towards developing more productive forms of anger in this patient population. Copyright © 2015 John Wiley & Sons, Ltd. KEY PRACTITIONER MESSAGE: A 20-session dialectical behaviour therapy (DBT)-informed skills training is a promising adjunct intervention for patients with borderline personality disorder, in particular for reducing problems related to social role. Increases in assertive anger mediate the effects of DBT-informed skills training, whereas rejecting anger remains unchanged over the course of treatment. Short-term objectives for intervention might involve the specific increase of assertive anger in BPD, by using DBT-informed skills training; long-term objectives for intervention might involve a specific decrease of rejecting anger in 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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0190.001

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.

Opus teacher head0.095
GPT teacher head0.483
Teacher spread0.388 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations84
Published2015
Admission routes1
Has abstractyes

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