Aetiology and treatment of nightmare disorder: State of the art and future perspectives
Bibliographic record
Abstract
This consensus paper provides an overview of the state of the art in research on the aetiology and treatment of nightmare disorder and outlines further perspectives on these issues. It presents a definition of nightmares and nightmare disorder followed by epidemiological findings, and then explains existing models of nightmare aetiology in traumatized and non-traumatized individuals. Chronic nightmares develop through the interaction of elevated hyperarousal and impaired fear extinction. This interplay is assumed to be facilitated by trait affect distress elicited by traumatic experiences, early childhood adversity and trait susceptibility, as well as by elevated thought suppression and potentially sleep-disordered breathing. Accordingly, different treatment options for nightmares focus on their meaning, on the chronic repetition of the nightmare or on maladaptive beliefs. Clinically, knowledge of healthcare providers about nightmare disorder and the delivery of evidence-based interventions in the healthcare system is discussed. Based on these findings, we highlight some future perspectives and potential further developments of nightmare treatments and research into nightmare aetiology.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".