Resolving trauma: The unique contribution of trauma-specific mentalization to maternal insightfulness
Bibliographic record
Abstract
Resolving trauma may contribute to mental health and parenting in mother with histories of childhood maltreatment. The concept of trauma-specific reflective functioning (T-RF) was developed to assess the complexity of thought processes regarding trauma. The study aimed to validate the T-RF scale applied to the Trauma Meaning-Making Interview by examining its psychometric properties, associations with measures of trauma-processing strategies, maternal reflective functioning and mental health (depression and post-traumatic stress disorder [PTSD]), as well as evaluating whether T-RF offered a unique contribution to maternal insightfulness. Good construct validity of the T-RF scale was confirmed in a sample of 112 mothers with histories of childhood maltreatment using an independent coding system of trauma-processing. Better mentalization of trauma was prospectively associated with higher parental reflective functioning and mothers with high T-RF were much more likely to be insightful regarding the child's mental states than non-reflective mothers and mothers with limited T-RF. The association between T-RF and insightfulness was observed even when controlling for maternal reflective functioning, trauma-processing strategies, maternal education and sociodemographic risk. T-RF was associated neither with depression, PTSD nor the characteristics of trauma. Findings suggest that mentalizing trauma would be an important protective factor in the intergenerational trajectories of trauma.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".