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Record W2902061878 · doi:10.1097/nmd.0000000000000905

Change in Emotional and Theory of Mind Processing in Borderline Personality Disorder

2018· article· en· W2902061878 on OpenAlexaff
Uëli Kramer, Stéphane Kolly, Pauline Maillard, Antonio Pascual‐Leone, Andrea C. Samson, Ruth Schmitt, Adriano Bernini, Gilles Allenbach, Patrick Charbon, Yves de Roten, Philippe Conus, Jean‐Nicolas Despland, Bogdan Draganski

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2018
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversity of Windsor
FundersUniversité de LausanneUniversität HeidelbergCentre Hospitalier Universitaire VaudoisSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsBorderline personality disorderPsychologyArousalFunctional magnetic resonance imagingTheory of mindPersonalityMoodClinical psychologyPsychotherapistCognitionPsychiatryNeurosciencePsychoanalysis

Abstract

fetched live from OpenAlex

Changes in emotional processing (EP) and in theory of mind (TOM) are central across treatment approaches for patients with borderline personality disorder (BPD). Although the assessment of EP relies on the observation of a patient's self-criticism in a two-chair dialogue, an individual's TOM assessments is made based on responses to humorous stimuli based on false beliefs. For this pilot study, we assessed eight patients with BPD before and after a 3-month-long psychiatric treatment, using functional magnetic resonance imaging and behavioral tasks. We observed arousal increase within the session of the two-chair dialogue (d = 0.36), paralleled by arousal decrease between sessions (d = 0.80). We found treatment-associated trends for neural activity reduction in brain areas central for EP and TOM. Our exploratory findings using an integrative assessment procedure of changes in EP and TOM point toward evidence for treatment effects at the brain systems level related to behavioral modulation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.241
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.342
Teacher spread0.307 · 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 teacher head, 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

Citations22
Published2018
Admission routes1
Has abstractyes

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