1042 Sleep Problems are Associated with Depression, Pain and Fatigue in Adults with Spinal Cord Injury
Bibliographic record
Abstract
People with Spinal Cord Injury (SCI) report significantly more sleep disturbance than the general population, which has significant implications for function, rehabilitation outcomes and quality of life. This study examined the relationship between sleep problems, depression, pain and fatigue in adults with SCI. Six hundred and twenty adults with SCI in a longitudinal survey of self-reported health completed the Medical Outcomes Study Sleep Scale (MOS-SS); Patient Health Questionnaire-9 (PHQ-9 (depression)); Brief Pain Inventory-7 (BPI-7); and Fatigue Severity Scale (FSS). The majority of participants were community dwelling, with 1.5% institutionalized. Pearson’s correlations between the MOS-SS summary measure (Sleep Problems Index II), MOS-SS subscales (sleep disturbance, snoring, shortness of breath, sleep quantity, sleep adequacy, and daytime somnolence) and depression, pain and fatigue were examined. Hierarchical multiple regression analysis examined the relationship between sleep problems (dependent variable) and depression, pain and fatigue (independent variables) controlling for age, sex, level of injury, and completeness of injury. Most correlations were statistically significant (p ≤ 0.05); the exceptions were snoring in relation to sleep adequacy, sleep quantity, depression and pain. The overall model explained 46.2% of the variance in sleep problems (P < 0.001). Additionally, depression (β=.393), pain (β=.269), and fatigue (β=.098) all made unique statistically significant contributions (P < 0.05). This study found that depression, pain and fatigue, are significantly related to sleep problems in people with SCI. Although the cross-sectional nature of this analysis does not permit conclusions about causality, these findings are consistent with results of studies in the general population that found poor sleep is associated with more depression, pain, and fatigue. The strong association of each of these symptoms with poor sleep following SCI highlights the critical importance of routinely screening people with SCI for sleep problems in order to inform treatment decisions and better manage conditions co-morbid with SCI. DOE (NIDRR H133B031129, H133B080025); NIH (NIAMS 5U01AR05217, NICHD K01HD076183).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".