Study protocol for the validation of a new pictorial functional scale in patients with knee osteoarthritis: the functional activity scoring tool (FAST)
Bibliographic record
Abstract
BACKGROUND: Patient-reported outcome measures (PROMs) are required for patient-centred care. There are limited PROMs with good psychometric properties, and limitations to any language-based scale are often constrained by the written words or numerals used. Therefore, we developed the Functional Activity Scoring Tool (FAST), a self-reporting pictorial scale. FAST measures the impact of knee osteoarthritis on essential activities of daily living (ADL) and the significant changes in the self-perceived functional status over time. OBJECTIVES: This study aims to (1) develop FAST with adaptation from the Wong-Baker FACES pain rating scale, (2) validate FAST against the Patient-Specific Functional Scale (PSFS) and Knee Injury and Osteoarthritis Outcome Score (KOOS) and (3) establish the reliability, validity and responsiveness of FAST in individuals with knee osteoarthritis. METHODS AND ANALYSIS: The prospective study protocol investigates the validity, responsiveness and reliability of FAST. The PSFS and KOOS will be gold standard comparisons. Participant recruitment will occur at four public polyclinics that offer physiotherapy outpatient services in Singapore. Onsite physiotherapists familiar with the study eligibilities will refer potential participants to the investigators after the routine physiotherapy assessment. After providing written consent, eligible participants will complete outcome measurements with FAST, the PSFS and KOOS during baseline and follow-up assessments. The Global Rating of Change (GROC) scale will determine how the participant's knee status was changed compared with the beginning of the physiotherapy intervention. ETHICS AND DISSEMINATION: SingHealth Centralised Institutional Review Board approved the study (CIRB reference number: 2022/2602). The final results will be published via scientific publication. FAST will benefit the evaluation and management of those who suffer knee osteoarthritis regardless of English proficiency or language barriers. TRIAL REGISTRATION NUMBER: NCT05590663.
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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 | 0.044 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.074 | 0.018 |
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".