Disturbed dreaming, posttraumatic stress disorder, and affect distress: A review and neurocognitive model.
Bibliographic record
Abstract
Nightmares are common, occurring weekly in 4%-10% of the population, and are associated with female gender, younger age, increased stress, psychopathology, and dispositional traits. Nightmare pathogenesis remains unexplained, as do differences between nontraumatic and posttraumatic nightmares (for those with or without posttraumatic stress disorder) and relations with waking functioning. No models adequately explain nightmares nor have they been reconciled with recent developments in cognitive neuroscience, fear acquisition, and emotional memory. The authors review the recent literature and propose a conceptual framework for understanding a spectrum of dysphoric dreaming. Central to this is the notion that variations in nightmare prevalence, frequency, severity, and psychopathological comorbidity reflect the influence of both affect load, a consequence of daily variations in emotional pressure, and affect distress, a disposition to experience events with distressing, highly reactive emotions. In a cross-state, multilevel model of dream function and nightmare production, the authors integrate findings on emotional memory structures and the brain correlates of emotion.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".