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Record W2069002533 · doi:10.1159/000339530

Axis II Comorbidity of Borderline Personality Disorder in Adolescents

2012· article· en· W2069002533 on OpenAlexaff
Gwenolé Loas, Alexandra Pham‐Scottez, Lionel Cailhol, Fernando Pérez-Díaz, Maurice Corcos, Mario Speranza

Bibliographic record

VenuePsychopathology · 2012
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsSte. Anne's Hospital
Fundersnot available
KeywordsComorbidityBorderline personality disorderPsychologyPersonality disordersPersonalityPsychiatryClinical psychology

Abstract

fetched live from OpenAlex

AIMS: The objective of the present study was to explore the comorbidity of borderline personality disorder (BPD) with other personality disorders in adolescents and compare these comorbidities in male and female subjects. METHODS: The sample was drawn from a European research project investigating the phenomenology of BPD in adolescence (EURNET BPD). A total of 85 BPD patients (11 boys and 74 girls) with a mean age of 16.3 years were included in the study. RESULTS: According to the results of the Structured Interview for DSM-IV Disorders of Personality, obsessive-compulsive (35.3%), antisocial (22.4%), avoidant (21.2%), dependent (11.8%) and paranoid (9.4%) personality disorders had significant co-occurrences with BPD. Although none of the gender differences was statistically significant, we observed a trend towards higher rates of antisocial personality disorders in men (45.5%) than in women (19%). CONCLUSION: The study results confirmed the frequency of Axis II comorbidity in adolescents with BPD and, for the first time, evidenced a differential pattern of comorbidity in males and females. This differential pattern must be taken into account when developing treatment strategies for adolescents with BPD.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.033
GPT teacher head0.344
Teacher spread0.311 · 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 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

Citations17
Published2012
Admission routes1
Has abstractyes

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