Physical Activity in the Treatment and Management of Fibromyalgia
Bibliographic record
Abstract
Fibromyalgia (FMS) is a whole-body disease that is associated with pain and discomfort. Approximately 2 to 5% of the population is afflicted with FMS and up to 90% of individuals diagnosed are women. There is no known cure for FMS, only suggested treatments designed to manage FMS symptoms. Treatment modalities, including both pharmacologic and nonpharmacologic interventions, are often co-prescribed and vary widely in order to address the unique experience faced by FMS sufferers. A substantial number of studies have investigated how physical activity is related to the symptoms associated with FMS. The purpose of the present review is to provide a holistic picture of the exercise-FMS relationship by addressing the following questions: (1) Do differences exist between individuals with FMS and healthy individuals in physiological responses to acute exercise or adaptation to exercise training? (2) What type(s) of physical activity is (are) best for individuals afflicted with FMS? (3) Do different exercise modalities lead to the reprieve of different symptoms? (4) What specific symptoms are alleviated through exercise participation? (5) What conclusions have been drawn by other researchers reviewing exercise-related interventions for FMS? (6) Does gender moderate the optimal exercise modality or treatment effectiveness? (7) What current therapeutic approaches to FMS are most successful and do they include exercise? (8) If exercise is currently being used as an effective treatment, what current exercise prescriptions exist for people with FMS? In response to these questions, comparisons are made between FMS and healthy individuals with regard to physiological responses to exercise and training. In addition, a review of the exercise-related FMS research is presented. Gender differences in exercise-related indices of health and physical functioning are considered. Treatment options for managing FMS are reviewed, and exercise prescriptions for effective treatments are provided. It is concluded that a regular exercise program tailored toward an individual's specific needs and symptom challenges will ultimately increase their psychological and physical functioning, decrease their pain experiences, help alleviate other FMS symptoms, and improve their overall quality of life by improving their physical ability to perform activities of daily living.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".