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Psychometric Properties of the French Version of the Borderline Personality Features Scale for Children and Adolescents

2019· article· en· W2971755579 on OpenAlexaff
Karin Ensink, Michaël Bégin, Judith Kotiuga, Carla Sharp, Lina Normandin

Bibliographic record

VenueAdolescent Psychiatry · 2019
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCBCLPsychologyBorderline personality disorderChild Behavior ChecklistClinical psychologyPersonalityInternal consistencyScale (ratio)PsychometricsConvergent validityDevelopmental psychologySocial psychology

Abstract

fetched live from OpenAlex

Background: The Borderline Personality Feature Scale for Children (BPFS-C) is currently the only dimensional measure of child and adolescent borderline features and the English version has been shown to have good psychometric properties. To extend the use of this measure with French speaking adolescents, it is essential to examine the reliability and validity of the French BPFS-C. Objective: The present study sought to assess the psychometric properties of the French BPFS-C. Methods: A community sample of 394 adolescents and young adults completed the Borderline Personality Features Scale for Children (BPFS-C), as well as the Million Adolescent Clinical Inventory (MACI) borderline tendency subscale, the Child Behavior Checklist- Youth Self-Report (CBCL-YSR) and the Beck Youth Inventories (BYI). Results: The findings show that both the long and short French BPFS-C have good internal consistency and convergent validity. Affect regulation, identity, relationship difficulties and self-harm were found to be closely inter-connected rather than distinct factors. Conclusion: The findings indicate that both long and short versions of French BPFS-C have good psychometric properties and provide preliminary evidence that the total scores are reliable and valid indicators of borderline personality features in adolescents and young adults.

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)0.000
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 score0.022
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.256
Teacher spread0.246 · 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

Citations10
Published2019
Admission routes1
Has abstractyes

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