Psychometric Properties of the French Version of the Borderline Personality Features Scale for Children and Adolescents
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".