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Record W2160246509 · doi:10.1177/070674370505000407

Major Depression in Patients with Borderline Personality Disorder: A Clinical Investigation

2005· article· en· W2160246509 on OpenAlexvenueno aff
Silvio Bellino, Luca Patria, Erika Paradiso, Rossella Di Lorenzo, Caterina Zanon, Monica Zizza, Filippo Bogetto

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2005
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsnot available
Fundersnot available
KeywordsBorderline personality disorderComorbidityDepression (economics)Clinical psychologyPsychologyPsychiatryPersonality disordersMajor depressive disorderMoodAnxietyHamilton Rating Scale for DepressionMood disordersPersonality

Abstract

fetched live from OpenAlex

OBJECTIVE: Borderline personality disorder (BPD) is characterized by a high frequency of comorbidity with major depressive disorder (MDD). This study aimed to compare the clinical characteristics of 2 groups of patients with MDD: those with concomitant BPD and those with other concomitant personality disorders. METHODS: We assessed 119 outpatients, using a semistructured interview for demographic and clinical features, the Structured Clinical Interview for DSM-IV, Hamilton anxiety and depression scales, the Zung Self-Rating Depression Scale (ZSDS), the Social and Occupational Functioning Assessment Scale (SOFAS), the Sheehan Disability Scale, and the Revised Childhood Experiences Questionnaire. We performed a regression analysis, using the number of criteria for BPD as the dependent variable. RESULTS: Severity of BPD was positively related to the ZSDS score, to self-mutilating behaviours, and to the occurrence of mood disorders in first-degree relatives; it was negatively related to the SOFAS score and age at onset of MDD. CONCLUSIONS: Patients with comorbid MDD and BPD present differential characteristics that indicate a more serious and impairing condition with a stronger familial link with mood disorders than is shown by depression patients with other Axis II codiagnoses.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.756
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.301
Teacher spread0.283 · 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.

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

Citations55
Published2005
Admission routes1
Has abstractyes

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