Feasibility and Efficacy of Craniosacral Therapy on Sleep Quality in Fibromyalgia Syndrome: a Pre-Post Pilot Trial
Bibliographic record
Abstract
Background: Sleep disturbance is one of the key symptoms of fibromyalgia syndrome (FMS), which negatively affects the participants’ quality of life. Craniosacral therapy (CST) is a gentle manual technique found to have significant effects on pain and function in chronic pain participants. However, limited evidence exists on its effectiveness on sleep quality in FMS participants. Purpose: To evaluate the feasibility and effectiveness of CST on sleep quality in FMS participants. Setting: Outpatient physiotherapy department of a hospital in Bangalore. Participants: Participants diagnosed with FMS. Research Design: A pre/post pilot trial. Intervention: Once weekly, 45-minute sessions of CST for 12 weeks. The participants continued the standard medical care prescribed by the physician. Main Outcome Measure: The sleep quality was evaluated using Pittsburgh Sleep Quality Index (PSQI) at baseline and 12 weeks. The data analysis was carried out using paired t test. Results: 9 out of 10 included par-ticipants completed the treatment and were included for analysis. The results of the paired t test showed significant improvement in the global PSQI score (p = .001, mean difference = 5.44±3.28, 95% CI = 2.92-7.97), as well as the 5 components of PSQI (p < .05). Conclusion: CST was feasible to deliver with high retention, acceptability, and minimal adverse events. It significantly improved sleep quality in FMS participants along with standard medical care. However, future studies with larger sample sizes and appropriate control groups are required to confirm the findings.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".