Sleep Disturbance in Adults With Posttraumatic Stress Disorder
Bibliographic record
Abstract
OBJECTIVE: To present a critical review of the literature and research on sleep difficulties in adults with posttraumatic stress disorder (PTSD), more specifically the existing treatment options, and to formulate recommendations regarding future treatment approaches and research related to sleep and PTSD. DATA SOURCES: The following databases were consulted: PsycInfo (1872-2006) and MEDLINE (1966-2006). The search was conducted using the following key terms: PTSD and sleep, PTSD and nightmares, PTSD and dreams, PTSD and insomnia, PTSD and periodic limb movement disorder, and PTSD and sleep disordered breathing. Only studies examining sleep disturbance among adults with PTSD were included, and only articles written in English were consulted. STUDY SELECTION: Studies and reviews related to the prevalence, causes, and treatments of sleep disturbance among adults with PTSD, as well as those examining the relationship between sleep and PTSD, were selected. CONCLUSIONS: Promising treatment options are available for treating sleep difficulties among adults with PTSD. In particular, cognitive-behavioral therapy including a component for nightmares (imagery rehearsal therapy) and insomnia has been found to significantly improve sleep disturbance among these individuals. It is proposed that with the inclusion of other components, such as a screening for other sleep disorders, relaxation exercises, positive self-talk, imagery rehearsal related to recurring images before bed, and a daytime nap, sleep-related symptoms may improve to a greater degree, which may then lead to a significant decrease in other PTSD symptoms and overall PTSD severity. The inclusion of sleep medicine specialists should also be considered for sleep medicine treatment of individuals with PTSD. Collaboration between mental health professionals and sleep medicine specialists is therefore recommended for treatment of sleep-related difficulties among individuals with PTSD.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".