Predicting Borderline Personality Disorder Symptoms Based on Childhood Trauma and Alexithymia With the Mediating Role of Mentalization in University Students
Bibliographic record
Abstract
The present study aimed to predict borderline personality disorder (BPD) based on childhood trauma and alexithymia, with the mediating role of mentalization in university students. This study employed a descriptive correlational design. The statistical population included male and female students from three branches of the Islamic Azad University: Tehran Central (Sardar Soleimani Complex, Faculty of Psychology and Educational Sciences), Tehran West (Payambar Azam Complex, Faculty of Architecture and Art), and Shahre Qods (Faculty of Engineering). These branches were selected from among all branches of the Islamic Azad University in Tehran during the 2024–2025 academic year. The sample size was determined to be 300 participants based on the method proposed by Kline (1990), and they were selected through a non-random convenience sampling method. Data were collected using the Jackson and Claridge Borderline Personality Scale (1991), the Childhood Trauma Questionnaire by Bernstein and Fink (2003), the Toronto Alexithymia Scale (1985), and the Mentalization Scale by Fonagy et al. (2016). Statistical analyses were performed using SPSS version 28 and AMOS version 24. The results of data analysis showed that childhood trauma had a standardized coefficient of 0.175 on borderline personality disorder and the direction of the effect was positive. Additionally, alexithymia had a standardized coefficient of 0.334 on borderline personality disorder and the direction of the effect was positive. Furthermore, childhood trauma had no significant effect on borderline personality disorder through the mediating role of mentalization (p = 0.358). However, alexithymia had a significant effect on borderline personality disorder through the mediating role of mentalization (p = 0.016). Finally, the empirical model demonstrated acceptable and appropriate fit, and the overall model was confirmed. Childhood trauma and alexithymia play important roles in the emergence of borderline personality disorder symptoms, and mentalization served as a mediator only in the relationship between alexithymia and borderline personality disorder. These findings highlight the necessity of incorporating emotion regulation training and strengthening mentalization skills in preventive and 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".