Sleep disturbances in fibromyalgia syndrome: Relationship to pain and depression
Bibliographic record
Abstract
OBJECTIVE: This study is an examination of sleep, pain, depression, and physical functioning at baseline and 1-year followup among patients with fibromyalgia syndrome (FMS). Although it is clear that these symptoms are prevalent among FMS patients and that they are related, the direction of the relationship is unclear. We sought to identify and report sleep problems in this population and to examine their relationship to pain, depression, and physical functioning. METHODS: Patients diagnosed with fibromyalgia were recruited from a Southern California health maintenance organization and evaluated according to American College of Rheumatology criteria in the research laboratory. Six hundred patients completed the baseline assessment and 492 completed the 1-year assessment. Measures included the Center for Epidemiologic Studies Depression Scale, the McGill Pain Questionnaire, the Pittsburgh Sleep Quality Index, and the Fibromyalgia Impact Questionnaire. RESULTS: The majority of the sample (96% at baseline and 94.7% at 1 year) scored within the range of problem sleepers. Path analyses examined the impact of baseline values on 1-year values for each of the 4 variables. No variable of interest predicted sleep, sleep predicted pain (beta = 0.13), pain predicted physical functioning (beta = -0.13), and physical functioning predicted depression (beta = -0.10). CONCLUSION: These findings highlight the high prevalence of sleep problems in this population and suggest that they play a critical role in exacerbating FMS symptoms. Furthermore, they support limited existing findings that sleep predicts subsequent pain in this population, but also extend the literature, suggesting that sleep may be related to depression through pain and physical functioning.
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 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 | 0.001 | 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) | 0.002 | 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".