Difficulties regulating emotions mediates the associations of parental psychological control and emotion invalidation with borderline personality features.
Bibliographic record
Abstract
Extant research has supported a connection between socialization in childhood and difficulties regulating emotions. The biosocial theory of borderline personality disorder (BPD; Crowell, Beauchaine, & Linehan, 2009; Linehan, 1993) suggests that emotion dysregulation is a core mechanism underlying the extreme behaviors, mood instability, identity disturbance, and relationship instability observed in BPD. The present study investigated the impact of socialization factors related to emotions, parental autonomy support, parental psychological control, and childhood trauma on BPD features in a nonclinical young adult sample (N = 357). Relationships between socialization factors and BPD features were evaluated using structural equation modeling, to test integrative hypotheses informed by biosocial theory and self-determination theory. We found that recalled experiences of childhood trauma, emotional magnification of negative emotions, neglect of negative emotions, and parental psychological control were positively associated with BPD features. Difficulties regulating emotions mediated the relationships of childhood emotion socialization factors and psychological control with BPD features. Implications for future research, resiliency, and intervention are discussed. (PsycINFO Database Record (c) 2019 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 | 0.001 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".