The VISA-A questionnaire: a valid and reliable index of the clinical severity of Achilles tendinopathy
Bibliographic record
Abstract
BACKGROUND: There is no disease specific, reliable, and valid clinical measure of Achilles tendinopathy. OBJECTIVE: To develop and test a questionnaire based instrument that would serve as an index of severity of Achilles tendinopathy. METHODS: Item generation, item reduction, item scaling, and pretesting were used to develop a questionnaire to assess the severity of Achilles tendinopathy. The final version consisted of eight questions that measured the domains of pain, function in daily living, and sporting activity. Results range from 0 to 100, where 100 represents the perfect score. Its validity and reliability were then tested in a population of non-surgical patients with Achilles tendinopathy (n = 45), presurgical patients with Achilles tendinopathy (n = 14), and two normal control populations (total n = 87). RESULTS: The VISA-A questionnaire had good test-retest (r = 0.93), intrarater (three tests, r = 0.90), and interrater (r = 0.90) reliability as well as good stability when compared one week apart (r = 0.81). The mean (95% confidence interval) VISA-A score in the non-surgical patients was 64 (59-69), in presurgical patients 44 (28-60), and in control subjects it exceeded 96 (94-99). Thus the VISA-A score was higher in non-surgical than presurgical patients (p = 0.02) and higher in control subjects than in both patient populations (p<0.001). CONCLUSIONS: The VISA-A questionnaire is reliable and displayed construct validity when means were compared in patients with a range of severity of Achilles tendinopathy and control subjects. The continuous numerical result of the VISA-A questionnaire has the potential to provide utility in both the clinical setting and research. The test is not designed to be diagnostic. Further studies are needed to determine whether the VISA-A score predicts prognosis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".