Determinants of sleep problems in patients with spondyloarthropathy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To characterize sleep complaints and identify biopsychosocial factors associated with sleep problems in patients with spondyloarthropathy (SpA). METHODS: The sample comprised 125 patients with SpA. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Participants completed standardized questionnaires assessing depressed mood, perceived stress, leisure time physical activity, functional disability and disease activity. A series of hierarchical multiple regressions were computed to examine the determinants of the following sleep parameters: quality, latency, duration and efficiency. RESULTS: The mean global PSQI score was 8.7 (SD = 5.0), with 69% of the sample classified as poor sleepers (PSQI global score >5). Worse functional status was associated with poorer sleep quality (p = 0.006), longer sleep latency (p = 0.004), shorter sleep duration (p = 0.001) and poorer sleep efficiency (p = 0.004). Higher depressed mood scores emerged in the multivariate analyses as a significant determinant of poorer sleep quality (p = 0.010), shorter sleep duration (p = 0.007) and poorer sleep efficiency (p = 0.006). Higher perceived stress was an independent contributor of poorer sleep quality (p = 0.033). The relationships between worse functional status and poorer sleep quality and shorter sleep duration were more pronounced for participants who completed the questionnaires in the English language. CONCLUSIONS: Sleep problems are prevalent among patients with SpA. Our findings suggest that multiple factors are associated with sleep complaints in persons with SpA with functional status, depressed mood and stress differentially contributing to specific sleep parameters. Multimodal interventions, which include non-pharmacological methods targeting these biopsychosocial factors, require evaluation to optimize the management of sleep disruptions in SpA.
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.
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 | 0.000 |
| 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 it