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Record W2778835416 · doi:10.1002/cpp.2160

The role of shame and self‐compassion in psychotherapy for narcissistic personality disorder: An exploratory study

2017· article· en· W2778835416 on OpenAlexaff
Uëli Kramer, Antonio Pascual‐Leone, Kristina Rohde, Rainer Sachse

Bibliographic record

VenueClinical Psychology & Psychotherapy · 2017
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsShamePsychologySelf-compassionNarcissistic personality disorderPsychological interventionPsychotherapistClinical psychologyExploratory researchPersonalityPersonality disordersMindfulnessSocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

This process-outcome study aims at exploring the role of shame, self-compassion, and specific therapeutic interventions in psychotherapy for patients with narcissistic personality disorder (NPD). This exploratory study included a total of N = 17 patients with NPD undergoing long-term clarification-oriented psychotherapy. Their mean age was 39 years, and 10 were male. On average, treatments were 64 sessions long (range between 45 and 99). Sessions 25 and 36 were rated using the Classification of Affective Meaning States and the Process-Content-Relationship Scale. Outcome was assessed using the Symptom Check List-90 and Beck Depression Inventory-II. Between Sessions 25 and 36, a small decrease in the frequency of shame was found (d = .30). In Session 36, the presence of self-compassion was linked with a set of specific therapist interventions (process-guidance and treatment of behaviour-underlying assumptions; 51% of variance explained and adjusted). This study points to the possible central role of shame in the therapeutic process of patients with NPD. Hypothetically, one way of resolving shame is, for the patient, to access underlying self-compassion.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.108
GPT teacher head0.489
Teacher spread0.381 · 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 designObservational
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

Citations45
Published2017
Admission routes1
Has abstractyes

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