Self-Reported Clinical Correlates of Insomnia
Bibliographic record
Abstract
Objective: to examine clinical correlates of post-accident insomnia.Background and Aims: survivors of motor vehicle accidents (MVAs) usually report impaired sleep and other symptoms such as persistent pain, depressive symptoms, anxiety, anger, and post-MVA neurological symptoms.We examined how these variables correlate with insomnia.Materials and Methods: 101 patients (mean age 42.6, SD=14.1, 39 males, 62 females) undergoing psychological assessment after an MVA completed the Insomnia Severity Index, the Rivermead Post-Concussion Symptoms Questionnaire, and the Brief Pain Inventory.We also assessed post-MVA neurological symptoms other than concussion (e.g., hand tremor, tingling, numbness, impaired muscular control over limbs), the current mood (anxiety, depression, anger).We also interviewed our patients about the immediate symptoms of concussion (loss of consciousness, or feeling dazed, stunned, confused, disoriented, or dizzy). Results:The Insomnia Severity Index (ISI) in our sample ranged from 2 to 28 (mean 22.3, SD=5.3).The psychometric properties of ISI in our sample are satisfactory (Cronbach's alpha=.88).The insomnia scores correlated moderately with depressive mood (r=.64) and also with the post-concussion syndrome even after the item dealing with impaired sleep was removed from the Rivermead (r=.66).The insomnia also correlated with measures of MVA related pain (r=.41), anxiety (r=.48), and anger (r=.39), post-MVA neurological symptoms other than concussion (r=.36), and with diagnosis of PTSD (r=.50), but not with age and gender (p>.05). Conclusions:The post-MVA insomnia (as represented by ISI scores) is moderately correlated with the postconcussion syndrome and with depressed mood.
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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 | 0.000 | 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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".