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Record W4298326287 · doi:10.1521/pedi.2022.36.5.606

Relations Between Anxiety Sensitivity and Attachment in Outpatients With Borderline Personality Disorder

2022· article· en· W4298326287 on OpenAlexaff
Jessie N. Doyle, Margo C. Watt, Jacqueline N. Cohen, Marie‐Eve Couture, MacGillivray M. Smith

Bibliographic record

VenueJournal of Personality Disorders · 2022
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsNova Scotia HospitalNova Scotia Health AuthoritySt. Francis Xavier UniversityDalhousie UniversityUniversity of New Brunswick
Fundersnot available
KeywordsBorderline personality disorderPsychologyImpulsivityAnxiety sensitivityClinical psychologyAnxietySocial anxietyEmotional dysregulationArousalPersonalityPsychiatry

Abstract

fetched live from OpenAlex

Borderline personality disorder (BPD) is characterized by dysregulated emotion, interpersonal relationships, and impulsivity, and is putatively linked to a known transdiagnostic risk factor, anxiety sensitivity (AS). AS is a dispositional fear of the physical, cognitive, and/or social consequences of arousal-related somatic sensations. Gratz et al. (2008) demonstrated significantly higher AS in outpatients with BPD and a predictive value of AS over and above emotion dysregulation and impulsivity. The present study sought to extend these findings with a larger sample of outpatients with BPD by investigating predictive value of AS dimensions; relations between AS and attachment style; and impact of BPD treatment on AS. Participants completed measures at three time points: pretreatment and 6 and 12 months posttreatment. AS social was the best predictor; attachment anxiety correlated positively with AS global and AS physical. AS levels significantly decreased from pretreatment to 6 months posttreatment. Clinical implications discussed include targeting AS in BPD treatment.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.311
Teacher spread0.293 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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