Evaluation of the Impacts of Reiki Touch Therapy on Patients Diagnosed With Fibromyalgia Who Are Followed in the Pain Clinic
Bibliographic record
Abstract
The aim of this study is to investigate the effects of Reiki application on pain, anxiety, and quality of life in patients with fibromyalgia. The study was completed with a total of 50 patients: 25 in the experimental group and 25 in the control group. Reiki was applied to the experimental group and sham Reiki to the control group once a week for 4 weeks. Data were collected from the participants using the Information Form, Visual Analog Scale, McGill-Melzack Pain Questionnaire, State-Trait Anxiety Inventory, and Short Form-36. There was a significant difference between the mean Visual Analog Scale pain scores during and before the first week (P = .012), second week (P = .002), and fourth week (P = .020) measurements of the individuals in the experimental and control groups, after application. In addition, at the end of the 4-week period, the State Anxiety Inventory (P = .005) and the Trait Anxiety Inventory (P = .003) were significantly decreased in the Reiki group compared with the control group. Physical function (P = .000), energy (P = .009), mental health (P = .018), and pain (P = .029) subdimension scores of quality of life in the Reiki group increased significantly compared with the control group. Reiki application to patients with fibromyalgia may have positive effects on reducing pain, improving quality of life, and reducing state and trait anxiety levels.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".