Performance-based and patient-reported outcome measures for custom ankle-foot orthosis users: reliability, validity, and sensitivity evidence
Bibliographic record
Abstract
PURPOSE: To evaluate the psychometric properties of performance and patient-reported outcome measures (PROMs) for custom ankle-foot orthosis (AFOs) users. MATERIALS AND METHODS: Current AFO users completed two assessments one week apart; new AFO users completed an assessment before device delivery and at one- and two-months post-delivery. RESULTS: Seventy current and 31 new users consented and provided data. We found evidence of minimal floor and ceiling effects for most PROMs; the exceptions were measures of service satisfaction. The Orthotics and Prosthetics Users' Survey (OPUS) Lower Extremity Functional Status (LEFS) measure demonstrated excellent test-retest reliability; the 5-level EuroQol (EQ-5D-5L), OPUS Health-Related Quality of Life, Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0), and PROMIS Physical Function measures demonstrated good reliability. Evidence of known-groups validity is provided by associations between obesity and walking speed. PROMs measuring physical function (LEFS, Rivermead Mobility Index (RMI), PROMIS Physical Function) correlated at least moderately with performance instruments. We observed moderate to large correlations between PROM and performance instrument changes for the EQ-5D-5L, LEFS, RMI, and PROMIS Physical Function. CONCLUSIONS: Results provide evidence of test-retest reliability, construct validity, and sensitivity to change for some PROMs. PROMs and performance instruments provide overlapping but complementary evidence regarding the benefits of custom AFOs.
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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 | 0.037 | 0.111 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".