Using Wii Fit to reduce fatigue among African American women with systemic lupus erythematosus: A pilot study
Bibliographic record
Abstract
Fatigue and physical deconditioning are common, difficult to treat conditions among patients with systemic lupus erythematosus (SLE). The aim of this pilot study was to evaluate the effectiveness of a home-based exercise program using the Wii Fit system in patients with SLE. Fifteen sedentary African American women with SLE experiencing moderate to severe fatigue participated in a home exercise program using the Wii Fit 3 days a week for 30 minutes each for 10 weeks. A one-group pretest-post test design was used to evaluate the effectiveness of this program. Primary outcome measure was severity of fatigue. Secondary outcome measures were body weight, waist circumference, fatigue-related symptoms of distress, activity level, and physical fitness. At the completion of the 10-week Wii Fit exercise program, participants perceived fatigue severity as measured by the Fatigue Severity Scale to be significantly decreased (p = 0.002), and body weight and waist circumference were significantly reduced (p = 0.01). In addition, anxiety level, as measured by Hospital Anxiety and Depression Scale, and overall intensity of total pain experience, as measured by Short-form of the McGill Pain Questionnaire, were also significantly reduced (p < 0.05). Findings provide preliminary evidence that the Wii Fit motivates this population to exercise, which leads to alleviation of fatigue and reduced body weight, waist circumference, anxiety level, and overall intensity of total pain experience.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".