Characterizing the heterogeneity of disruptions in the resolution of trauma among women exposed to childhood maltreatment
Bibliographic record
Abstract
Abstract The previously observed heterogeneity in developmental and intergenerational trajectories of childhood trauma may root from interindividual differences in the way trauma-exposed individuals have resolved these experiences. The current study explored whether distinctive patterns of impaired mentalization in relation to trauma could be identified in a sample of 825 pregnant women who experienced childhood maltreatment and whether these heterogeneous patterns were marked by significant differences in internalized and externalized problems during pregnancy, intimate partner violence, personality dysfunctions, and antenatal attachment. A latent profile analysis applied to the seven subscales of the Failure to Mentalize Trauma Questionnaire unraveled interindividual variability in mentalizing impairments among pregnant women exposed to childhood maltreatment by identifying five distinctive types of psychological responses to trauma, each being associated in cross-sectional analyses with a specific set of symptoms and dysfunctions. Overall, the study highlights the need for tailored interventions based on the individuals’ specific impairments in mentalizing trauma and calls for future developmental research exploring the longitudinal correlates of the five documented profiles of trauma processing.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".