Parental bonding and neuropsychological performance are associated with episodic simulation of future events in trauma‐exposed patients with major depressive disorder
Bibliographic record
Abstract
INTRODUCTION: Major depressive disorder (MDD) and trauma-related disorders are associated with deficits in remembering the past and imagining the future (i.e., episodic simulation). We examined parental bonding and neuropsychological performance in relation to episodic simulation in trauma-exposed patients with recurrent MDD. METHODS: Trauma-exposed patients with MDD (n = 21) and matched controls (n = 20) completed a future-oriented Autobiographical Interview, the Parental Bonding Instrument, and a standardized neuropsychological battery. RESULTS: Patients with major depressive disorder generated fewer episodic details for future neutral events compared to controls. Although higher reported levels of maternal care were associated with increased specificity of negative future events among the patient group, higher maternal overprotection was related to decreased specificity of negative and positive future events. Higher levels of performance on measures of intelligence, verbal memory, executive functioning, and sustained attention were associated with increased specificity of future events. CONCLUSIONS: Maternal relations during childhood and neuropsychological performance are related to the specificity of episodic simulation in adult patients with MDD. Childhood experience continues to influence memory performance into adulthood.
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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".