Endorsement of: “Position paper for the treatment of nightmare disorder in adults: An American Academy of Sleep Medicine position paper” by the World Sleep Society
Bibliographic record
Abstract
According to the ICSD-3TR, nightmare disorder is characterized by extended, extremely dysphoric, and well-remembered dreams that usually involve threats to survival, security, or physical integrity. The dream experience causes clinically significant distress or impairment in social, occupational, or other important areas of functioning. Nightmare disorder occurs in 2–6% of adults. Nightmares are present in 88 % of patients with post-traumatic stress disorder (PTSD), in 31 % of active-duty military populations and war veterans, and in 93 % of patients with isolated REM sleep behavior disorder (RBD). Nightmares can also occur in the setting of other sleep disorders including severe obstructive sleep apnea, periodic limb movement disorder, non-REM parasomnias and narcolepsy. However, for many available treatment options for nightmare disorder, direct evidence is limited, and numerous research questions remain unanswered. Concerns in therapeutic studies include the etiology and definition of nightmares, their assessment methodologies, the high comorbidities of nightmares with other sleep disorders (especially insomnia, RBD, narcolepsy, and obstructive sleep apnea) and PTSD, outcome measures to assess improvement, the heterogeneous subpopulations (adults, children, military veterans and refugees), and the integration of nightmare treatments into different healthcare systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.040 | 0.021 |
| Insufficient payload (model declined to judge) | 0.059 | 0.039 |
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".