Moving Beyond Average Values: Assessing the Night-To-Night Instability of Sleep and Arousal in DSM-IV-TR Insomnia Subtypes
Bibliographic record
Abstract
STUDY OBJECTIVES: We explored differences between individuals with DSM-IV-TR diagnoses of primary insomnia (PI) and insomnia related to a mental disorder (IMD) by using serial measurements of self-reported sleep variables (sleep onset latency, SOL; wake after sleep onset, WASO; total sleep time, TST; sleep efficiency, SE), and visual analogue scale ratings of 2 forms of bedtime arousal (cognitive and emotional). Furthermore, we sought to examine the relationship between sleep and arousal within each diagnostic subgroup. DESIGN: Between-group and within-group comparisons. SETTING: Duke and Rush University Medical Centers, USA. PARTICIPANTS: One hundred eighty-seven insomnia sufferers (126 women, average age 47.15 years) diagnosed by sleep specialists at 2 sleep centers as PI patients (n=126) and IMD patients (n=61). INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: Multilevel models for sleep measures indicated that IMD displayed significantly more instability across nights in their TST (i.e., larger changes) than did PI patients. With respect to pre-sleep arousal, IMD patients exhibited higher mean levels of emotional arousal, as well as more instability on the nightly ratings of this measure. Within the PI group, correlational analyses revealed a moderate relationship between the 2 arousal variables and SOL (r values 0.29 and 0.26), whereas the corresponding correlations were negligible and statistically nonsignificant in the IMD group. CONCLUSIONS: We found a number of differences on nighttime variables between those diagnosed with primary insomnia and those diagnosed with insomnia related to a mental disorder. These differences imply different perpetuating mechanisms involved in their ongoing sleep difficulties. Additionally, they support the categorical distinctiveness and the concurrent validity of these insomnia subtypes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 teacher head, 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".