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Record W1996438274 · doi:10.1080/00223891.2010.513287

Affect Dysregulation in Individuals With Borderline Personality Disorder: Persistence and Interpersonal Triggers

2010· article· en· W1996438274 on OpenAlexaff
Gentiana Sadikaj, Jennifer J. Russell, D. S. Moskowitz, Joel Paris

Bibliographic record

VenueJournal of Personality Assessment · 2010
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsPsychologyAffect (linguistics)Borderline personality disorderInterpersonal communicationPersistence (discontinuity)PersonalityInterpersonal relationshipEmotional dysregulationDevelopmental psychologyPerceptionClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

We hypothesized that affect dysregulation among individuals with borderline personality disorder (BPD) would involve greater persistence of negative affect between interpersonal events and heightened reactivity to stimuli indicating risk of rejection or disapproval, specifically perceptions of others' communal (agreeable-quarrelsome) behaviors. A total of 38 participants with BPD and 31 controls collected information about affect and perceptions of the interaction partner's behavior during interpersonal events for a 20-day period. Negative and positive affect persisted more across interpersonal events for individuals with BPD than for controls. In addition, individuals with BPD reported a greater increase in negative affect when they perceived less communal behavior and a smaller increase in positive affect when they perceived more communal behavior in others. Findings indicate the importance of interpersonal perceptions in the affect dysregulation of individuals with 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)0.000
metaresearch head score (Gemma)0.003
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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.023
GPT teacher head0.349
Teacher spread0.326 · 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

Citations134
Published2010
Admission routes1
Has abstractyes

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