Childhood maltreatment, attachment, and borderline personality–related symptoms: Gender-specific structural equation models.
Bibliographic record
Abstract
OBJECTIVES: Survivors of early interpersonal trauma may experience relational problems, anger, impulsive and self-destructive behaviors, identity disturbance, and other difficulties that are associated with borderline personality disorder. Insecure attachment also has been documented in survivors and may be related to borderline personality-related symptoms (BPRS). The goal of the current study was to examine an integrative model of maternal and paternal childhood maltreatment and insecure attachment as they predict BPRS. METHOD: The sample was composed of 954 participants who completed self-report measures of parental maltreatment during childhood, attachment security, and trauma-related symptoms. RESULTS: Structural equation modeling suggested differential impacts of maternal and paternal maltreatment on male and female participants. Both maternal and paternal maltreatment were directly associated with BPRS in women, whereas in men, only paternal maltreatment was directly related to BPRS. In women, paternal maltreatment was indirectly associated with BPRS through attachment anxiety but not through attachment avoidance. In men, maternal maltreatment was indirectly associated with BPRS through attachment anxiety but not through attachment avoidance. CONCLUSION: These findings have implications for the understanding of gender-specific etiologies of borderline personality symptoms and underscore attachment security as an important intervention target. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".