Dimensional model of adolescent personality pathology, reflective functioning, and emotional maltreatment
Bibliographic record
Abstract
Introduction: Childhood emotional abuse (CEA) is a recognized risk factor for adolescent mentalizing challenges. However, there's limited understanding about how CEA might influence personality development and elevate the risk of adolescent personality pathology. A deeper grasp of these pathways is crucial, given that adolescence is a pivotal developmental phase for identity integration, personality consolidation, and the emergence of personality disorders. As the emphasis shifts to dimensional perspectives on adolescent personality pathology, the spotlight is increasingly on adolescents' evolving personality organization (PO). Within this framework, personality disorder manifestations stem from inherent vulnerabilities in PO. A comprehensive understanding of how CEA leads to these inherent vulnerabilities in PO can inform enhanced interventions for at-risk adolescents. Nonetheless, our comprehension lacks insight into potential pathways to PO, especially those involving external factors like maltreatment and individual traits like mentalizing. This study sought to bridge these gaps by employing latent factor analysis and structural equation modeling to explore connections between emotional maltreatment, adolescent mentalizing, and PO. Methods: A community-based cohort of 193 adolescents (aged 12-17) took part in self-report assessments: the Childhood Experience of Care and Abuse Questionnaire (CECA.Q), the Reflective Functioning Questionnaire for Youth (RFQ-Y), and the Inventory for Personality Organization for Adolescents (IPO-A). Results: The structural equation model revealed a significant direct influence of CEA on both RFQ-Confusion and PO, and a noteworthy direct effect of RFQ-Confusion on PO. Remarkably, the model accounted for 76.9% of the PO variance. CEA exhibited a significant indirect impact on PO through RFQ-Confusion, which was accountable for 52.3% of the CEA effect on PO, signifying a partial mediation by mentalizing. Discussion: These insights carry substantial clinical implications, especially for devising integrated, trauma-informed strategies for adolescents with personality pathologies. This is particularly relevant for enhancing mentalizing and bolstering personality consolidation among adolescent CEA survivors.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".