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Record W2621951504 · doi:10.1521/pedi_2017_31_302

High Prevalence of Physical Pain Among Treatment-Seeking Individuals With Borderline Personality Disorder

2017· article· en· W2621951504 on OpenAlexaffabout
Laura M. Heath, Joel Paris, Lise Laporte, Kathryn Gill

Bibliographic record

VenueJournal of Personality Disorders · 2017
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsBorderline personality disorderPsychiatryPsychologyCoping (psychology)Pain catastrophizingClinical psychologyChronic painPain disorderMcGill Pain QuestionnaireOutpatient clinicPhysical therapyMedicineInternal medicineVisual analogue scale

Abstract

fetched live from OpenAlex

Research has demonstrated that about 30% of chronic pain patients suffer from borderline personality disorder (BPD), yet pain is not often discussed in research on the treatment of BPD. Sixty-five patients entering outpatient treatment for BPD were assessed at baseline for the prevalence of DSM-IV lifetime pain disorder, current medical problems, and the experience of current pain as measured by the McGill Pain Questionnaire. DSM-IV lifetime pain disorder diagnosis was present in 65% of patients. Current pain was experienced by 89% of participants, with intensity ranging from mild (19%) to excruciating (2%). Some individuals (21.5%) also reported experiencing daily medical problems in the past month prior to entering treatment. Physical pain is highly prevalent among treatment-seeking individuals with BPD. This pain phenomenon should be considered during treatment to help prevent a lifetime of functional impairment, including the possibility of abusing substances as a maladaptive coping mechanism.

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)0.002
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 score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.021
GPT teacher head0.324
Teacher spread0.303 · 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

Citations21
Published2017
Admission routes2
Has abstractyes

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