Applicability, Validity, and Reliability of the Piper Fatigue Scale in Postpolio Patients
Bibliographic record
Abstract
OBJECTIVE: To identify a scale that is potentially applicable for measuring the fatigue in postpolio patients and to evaluate its validity and reliability in this population. DESIGN: Interview survey of 64 individuals with postpolio syndrome and 25 healthy controls of similar age range, with retest in a subset of postpolio patients. The sample was recruited from a postpolio support group, a postpolio clinic, and the general community. Subjects completed the Piper Fatigue Scale, the Beck Depression Inventory, and the Chalder Fatigue Questionnaire during the interview. RESULTS: Face and content validity of the Piper Fatigue Scale was established by a team of experts and by a group of postpolio patients. The postpolio subjects had significantly higher Piper Fatigue Scale scores than the healthy control subjects (P < 0.001), demonstrating extreme groups validity. Convergent validity was shown with a strong positive correlation between Piper Fatigue Scale scores and Chalder Fatigue Questionnaire scores (r = 0.80). Reliability was also demonstrated with the Piper Fatigue Scale's high internal consistency (alpha = 0.98) and strong test-retest agreement (intraclass correlation coefficient = 0.98). CONCLUSIONS: The Piper Fatigue Scale is a valid and reliable tool for measuring postpolio fatigue. This scale may be useful in other studies of postpolio fatigue, including those gauging the effectiveness of various treatments for this fatigue.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".