Dissociative symptoms are associated with reduced neuropsychological performance in patients with recurrent depression and a history of trauma exposure
Bibliographic record
Abstract
BACKGROUND: Although preliminary work suggests that dissociative symptoms may impact neuropsychological performance in trauma-exposed populations, the relation between dissociation and cognitive performance has not been explored in patients with depression. OBJECTIVE: The present study examined dissociative symptoms in relation to neuropsychological performance in participants with a primary diagnosis of recurrent major depressive disorder (MDD) and a history of trauma exposure. METHOD: Twenty-three participants with MDD and 20 healthy controls who did not differ in age, sex, education, or IQ were assessed. In addition to a standardized neuropsychological battery assessing frontotemporally mediated cognitive processes, participants completed clinical measures assessing dissociative symptoms, illness severity, and past history of trauma exposure. RESULTS: Among participants with MDD, greater severity of derealization was associated with reduced performance on measures of delayed visuospatial recall and recognition on a task of verbal memory recognition. In addition, more severe depersonalization was associated with slower processing speed and a response style lending itself toward better performance in a less active environment. CONCLUSIONS: These findings point toward dissociative symptoms as a transdiagnostic factor associated with neuropsychological dysfunction in patients with depression and a history of trauma. Limitations and recommendations for future research are discussed.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".