The Development and Validation of a Self‐Administered Quality‐of‐Life Outcome Measure for Young, Active Patients With Symptomatic Hip Disease: The International Hip Outcome Tool (iHOT‐33)
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to develop a self-administered evaluative tool to measure health-related quality of life in young, active patients with hip disorders. METHODS: This outcome measure was developed for active patients (aged 18 to 60 years, Tegner activity level ≥ 4) presenting with a variety of symptomatic hip conditions. This multicenter study recruited patients from international hip arthroscopy and arthroplasty surgeon practices. The outcome was created using a process of item generation (51 patients), item reduction (150 patients), and pretesting (31 patients). The questionnaire was tested for test-retest reliability (123 patients); face, content, and construct validity (51 patients); and responsiveness over a 6-month period in post-arthroscopy patients (27 patients). RESULTS: Initially, 146 items were identified. This number was reduced to 60 through item reduction, and the items were categorized into 4 domains: (1) symptoms and functional limitations; (2) sports and recreational physical activities; (3) job-related concerns; and (4) social, emotional, and lifestyle concerns. The items were then formatted using a visual analog scale. Test-retest reliability showed Pearson correlations greater than 0.80 for 33 of the 60 questions. The intraclass correlation statistic was 0.78, and the Cronbach α was .99. Face validity and content validity were ensured during development, and construct validity was shown with a correlation of 0.81 to the Non-Arthritic Hip Score. Responsiveness was shown with a paired t test (P ≤ .01), effect size of 2.0, standardized response mean of 1.7, responsiveness ratio of 6.7, and minimal clinically important difference of 6 points. CONCLUSIONS: We have developed a new quality-of-life patient-reported outcome measure, the 33-item International Hip Outcome Tool (iHOT-33). This questionnaire uses a visual analog scale response format designed for computer self-administration by young, active patients with hip pathology. Its development has followed the most rigorous methodology involving a very large number of patients. The iHOT-33 has been shown to be reliable; shows face, content, and construct validity; and is highly responsive to clinical change. In our opinion the iHOT-33 can be used as a primary outcome measure for prospective patient evaluation and randomized clinical trials.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".