Familial Contributions to Self-Reported Sleep and Pain in Female Twins
Bibliographic record
Abstract
OBJECTIVE: The relationship between sleep quality and pain has been studied in populations with chronic pain and in nonclinical populations using experimental paradigms. Little is known about the familial contributions to this relationship. This study examines self-reported sleep quality and pain in a nonclinical sample and to explore familial (i.e., shared genetic and common family environment) confounding in those relationships. DESIGN: Cross-sectional. SUBJECTS: Ninety nine community-based female twin pairs (N = 198) with a mean age of 29 years; 72% monozygotic. METHODS: The short form McGill Pain Questionnaire (McGill), a visual analog scale (VAS), a body map, and the Pittsburgh Sleep Quality Index (PSQI) measured self-reported pain and sleep quality. Mixed model regression adjusted for age was used to examine relationships between the pain indices and PSQI in overall and within-pair models. RESULTS: Higher PSQI total scores were significantly associated with higher scores across the McGill sensory (B = 0.37, p < 0.001), affective (B = 0.16, p < 0.001), total scores (B = 0.54, p < 0.001), the VAS (B = 2.41, p < 0.001), and number of sites with any pain on the body map (B = 0.42, p = 0.001). All of these associations were diminished and rendered nonsignificant in within-pair analyses that accounted for genetic and familial factors (all p's ≥ 0.01; Bonferroni α = 0.01). CONCLUSIONS: These findings support an association between poor sleep quality and pain and suggest that this relationship may be confounded by shared genetic and environmental factors, which could elucidate biological mechanisms that underlie the development and maintenance of pain and sleep problems.
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 | 0.005 | 0.003 |
| 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) | 0.000 | 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".