Dissociative Experiences, childhood trauma and alexithymia among mothers of children with autism spectrum disorder
Bibliographic record
Abstract
Dissociative Experiences, childhood trauma and alexithymia among mothers of children with autism spectrum disorder Objective: Previous studies have consistently pointed out that parents of children with autism spectrum disorder (ASD) had worse mental health relative to parents of normally developing children. In this study, it was aimed to investigate differences in dissociative experiences, childhood trauma and alexithymia between mothers of children with and without ASD. Methods: Thirty-one mothers whose children had a principal diagnosis of ASD and thirty mothers whose had any current psychiatric diagnosis or a history of psychiatric disorder included in the study. The Dissociative Experiences Scale (DES), Toronto Alexithymia Scale (TAS-20), Childhood Trauma Scale (CTQ-28) and Somatoform Dissociation Scale (SDQ) were used as data collection tools. Results: In our study, mothers of children with ASD had more severe dissociative symptomatology, greater depersonalization / derealization, more frequent childhood sexual abuse and physical neglect compared to mothers in control group. However, there was no significant difference in alexithymia levels between two groups. Discussion: The results of our study showed that dissociative symptomatology and childhood traumas should be considered among mothers of children with ASD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".