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.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".