Supplementary Material for: From Childhood Trauma to Adult Dissociation: The Role of PTSD and Alexithymia
Bibliographic record
Abstract
Background: The mechanism of how childhood trauma leads to increased risk for adult dissociation is not sufficiently understood. We sought to investigate the predicting effects and the putatively mediating roles of PTSD and alexithymia on the path from childhood trauma to adult dissociation. Methods: A total of 666 day-clinic outpatients were administered the Childhood Trauma Questionnaire (CTQ), the Toronto Alexithymia Scale (TAS-20), the Posttraumatic Diagnostic Scale (PDS), and the Dissociative Experiences Scale (DES) and controlled for sex, age, and the Global Symptom Index (GSI). Linear regression analyses and mediation analyses were applied. Results: Independent predictive effects on dissociation were found for childhood trauma, alexithymia and PDS, even after adjusting for GSI. Effects of childhood neglect on dissociation were slightly stronger than of abuse. Alexithymia did not mediate the path from childhood trauma to dissociation. Mediation by PDS was specific for childhood abuse, with all PTSD symptom clusters being significantly involved. Conclusions: Childhood abuse and neglect are important predictors of dissociation. While the effects of abuse are mediated by PTSD, the mechanism of how neglect leads to dissociation remains unclear. The results further support the predictive value of alexithymia for adult dissociation above and beyond the effects of childhood trauma, PTSD, and GSI scores.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.894 | 0.361 |
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".