A (Re)-Evaluation of the Symptom Structure of Borderline Personality Disorder
Bibliographic record
Abstract
OBJECTIVE: Despite evidence of significant symptom heterogeneity and excessive diagnostic comorbidity, many contend that borderline personality disorder (BPD) is unidimensional, an assumption that rests primarily on results from factor analytic investigations of BPD symptom criteria. We note several limitations in the literature and argue that the symptom structure of BPD can be best clarified by using both factor analytic techniques and examining the BPD symptom dimensions in relation to external criteria (that is, personality traits). Our goals were to: examine if the symptoms of BPD are best conceptualized as unidimensional or multidimensional, and determine the extent to which personality traits account for any symptom dimensions that underlie BPD. METHOD: All published structural models of the BPD symptom criteria were identified and tested for statistical fit using confirmatory factor analysis in a sample of 373 patients who had completed the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders-Axis II Personality Questionnaire BPD scale. Dimensions from the best fitting model were examined in relation to traits from the Five-Factor Model (FFM) and the Personality Psychopathology Five (PSY-5) using correlational and regression analyses. RESULTS: Sanislow's 3-factor model, containing affect dysregulation, behavioural dysregulation, and disturbed relations symptom dimensions, provided the best fit; the unidimensional model produced the worst. The symptom dimensions of the 3-factor model were differentiable from one another and had unique associations with the FFM and PSY-5 personality traits. CONCLUSION: BPD is a multidimensional construct.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".