Influence of Standardized Procedures on the Reliability of Hip Clinical Assessment
Bibliographic record
Abstract
Objective This study evaluated a standardized and personalized approach to verify the effects of conditions on intrarater and interrater reliability, standard error of measurement, and minimal detectable difference for provocative tests and range-of-motion (ROM) tests used in hip pain assessment: flexion-adduction-internal rotation (FADIR), flexion-abduction-external rotation-extension (FABER), and hip internal rotation with 90° of hip flexion (hip IR). Methods Nineteen participants (mean [± SD] age = 24 ± 2 years; 10 women and 9 men) without lower limb or back pain were recruited. Three raters evaluated each participant during 2 testing sessions, 1 day apart. Raters performed the 3 tests in 4 conditions: classic (C), controlled pressure duration (CPD), subject-specific position (SSP), and mixed (M = CPD + SSP). Results For intrarater reliability, the CPD condition showed the highest intraclass correlation coefficients (ICCs; mean and 95% confidence interval [CI]) for hip IR ROM (0.83; 95% CI, 0.53-0.94) and FADIR ROM (0.75; 95% CI, 0.60-0.89). The SSP condition showed the highest ICCs for FABER height (0.71; 95% CI, 0.42-0.87) and FABER ROM (0.62; 95% CI, 0.27-0.83). Concerning interrater reliability, the classic condition presented the highest ICCs for FABER variables (height: 0.54; 95% CI, 0.28-0.76; ROM: 0.58; 95% CI, 0.32-0.79) and hip IR ROM (0.72; 95% CI, 0.51-0.87). The CPD condition showed the highest ICC for FADIR ROM (0.57; 95% CI, 0.32-0.78). Conclusion In the conditions of this study, CPD showed the highest ICCs for hip IR ROM and FADIR ROM , and SSP showed the highest ICCs for FABER height and FABER ROM .
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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 | 0.184 | 0.338 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".