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Record W2093063499 · doi:10.1002/pmh.89

The clinical significance of co‐morbid post‐traumatic stress disorder and borderline personality disorder: Case study and literature review

2009· article· en· W2093063499 on OpenAlexaff
Biruthvie Vignarajah, Paul S. Links

Bibliographic record

VenuePersonality and Mental Health · 2009
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBorderline personality disorderPsychologyPsychopathologyAngerAnxietyClinical psychologyPsychiatryPersonalityClinical significancePsychotherapistMedicinePsychoanalysis

Abstract

fetched live from OpenAlex

Abstract The purpose of this study is to determine the clinical significance of co‐morbid borderline personality disorder (BPD) and post‐traumatic stress disorder (PTSD), and the effect of this co‐morbidity on suicidal behaviour and response to treatment. Review of the evidence from past studies revealed that, although an additional diagnosis of PTSD did not exacerbate the BPD condition (or vice versa), certain symptoms were accentuated. These symptoms included anger, anxiety and avoidant behaviours as well as suicide proneness. The case analysed for the purposes of this study also highlights these findings from the literature review (i.e. certain symptoms of both PTSD and BPD were exacerbated in the patient, but there was no increase in overall psychopathology). The literature review further shows that despite promising results of alleviation of certain BPD features when treating for PTSD, treatment of such a co‐morbid condition must proceed with caution as treatment of PTSD without treatment of BPD and the related suicidal behaviour may be detrimental to the patient. Copyright © 2009 John Wiley & Sons, Ltd.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.049
GPT teacher head0.440
Teacher spread0.391 · 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 designCase report
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

Citations8
Published2009
Admission routes1
Has abstractyes

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