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Record W2110039171 · doi:10.1521/pedi.2011.25.4.448

Psychopathology, Childhood Trauma, and Personality Traits in Patients with Borderline Personality Disorder and Their Sisters

2011· article· en· W2110039171 on OpenAlexaff
Lise Laporte, Joel Paris, Herta A. Guttman, J A Russell

Bibliographic record

VenueJournal of Personality Disorders · 2011
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsCentre Jeunesse de QuebecMcGill University Health CentreMcGill University
Fundersnot available
KeywordsPsychopathologyPsychologyBorderline personality disorderDysfunctional familyPersonalityImpulsivityClinical psychologySexual abuseChild abusePsychiatryPoison controlInjury preventionMedicine

Abstract

fetched live from OpenAlex

The aim of this study was to document and compare adverse childhood experiences, and personality profiles in women with borderline personality disorder (BPD) and their sisters, and to determine how these factors impact current psychopathology. Fifty-six patients with BPD and their sisters were compared on measures assessing psychopathology, personality traits, and childhood adversities. Most sisters showed little evidence of psychopathology. Both groups reported dysfunctional parent-child relationships and a high prevalence of childhood trauma. Subjects with BPD reported experiencing more emotional abuse and intrafamilial sexual abuse, but more similarities than differences between probands and sisters were found. In multilevel analyses, personality traits of affective instability and impulsivity predicted DIB-R scores and SCL-90-R scores, above and beyond trauma. There were few relationships between childhood adversities and other measures of psychopathology. Sensitivity to adverse experiences, as reflected in the development of psychopathology, appears to be influenced by personality trait profiles.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.017
GPT teacher head0.262
Teacher spread0.245 · 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

Citations90
Published2011
Admission routes1
Has abstractyes

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