Borderline personality disorder traits and sexuality: Bridging a gap in the literature
Bibliographic record
Abstract
Extant research connecting borderline personality disorder (BPD) to sexuality is sparse. The current study aimed to expand the limited body of research on borderline personality traits and human sexuality, and to shed light on the personality features that contribute specifically to sexual sensation seeking, sexual compulsivity, and sexual risk-taking behaviours. Undergraduate students (n=955) completed an online questionnaire containing scales assessing BPD symptoms (affective instability, identity disturbance, negative relationships, and self-harm), sexual sensation seeking, sexual compulsivity, and sexual risk-taking. Multiple linear regression analyses were conducted and revealed no significant gender X symptom interaction predictors. Results did indicate links between specific BPD symptoms and specific sexuality variables. Total sexual compulsivity and compulsive sexual control behaviours were positively predicted by all four BPD symptoms, whereas compulsive sexual violence was predicted by all symptoms except for identity disturbance. Sexual sensation seeking was positively predicted by negative relationships and self-harm. Sexual risk taking was not significantly predicted by any BPD symptoms. These findings improve our understanding of how individuals with borderline personality traits experience romantic and sexual relationships, and may inform the future development of therapeutic interventions.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".