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Record W2228314675 · doi:10.1037/per0000156

A laboratory examination of emotion regulation skill strengthening in borderline personality disorder.

2015· article· en· W2228314675 on OpenAlexaff
Rebecca Metcalfe, Skye Fitzpatrick, Janice R. Kuo

Bibliographic record

VenuePersonality Disorders Theory Research and Treatment · 2015
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDistractionBorderline personality disorderPsychologyPsycINFOEmotional regulationPersonalityClinical psychologyNegativity effectDevelopmental psychologyCognitive psychologySocial psychologyMEDLINE

Abstract

fetched live from OpenAlex

This study examined whether individuals with borderline personality disorder (BPD; N = 25) exhibit deficits in their ability to strengthen their emotion regulation skills over time compared with healthy controls (HCs; N = 30). Participants were instructed to implement 1 of 2 different emotion regulation strategies (i.e., distraction and mindful awareness of the emotion) or to either react naturally (i.e., nonregulation condition) in response to BPD-relevant stimuli across multiple trials. Self-reported negativity and positivity, and physiological indices of emotion were collected throughout. Self-report results indicated that both groups displayed strengthening of distraction, but not mindful awareness, compared with the nonregulation condition over time. When comparing the 2 emotion regulation strategies to each other, heart rate data suggested that the rate of skill strengthening varied by group. Specifically, the BPD group evidenced strengthening of mindful awareness, but not distraction, over time whereas the HCs exhibited the opposite pattern. These findings suggest that individuals with BPD generally do not show deficits in their ability to strengthen emotion regulation skills and exhibit greater strengthening of mindful awareness than distraction over time. (PsycINFO Database Record

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.071
GPT teacher head0.386
Teacher spread0.315 · 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.

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

Citations10
Published2015
Admission routes1
Has abstractyes

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