Providing evidence for content validity of the most frequently used hip specific recovery outcome measures in hip fracture studies: an International Classification of Functioning approach
Bibliographic record
Abstract
PURPOSE: We established the most commonly used clinician and patient-reported hip fracture outcome measures as of 2022, assessed their content validity using an International Classification of Functioning, Disability and Health (ICF) framework, and operationalized these results to contribute to an updated hip fracture core set. MATERIALS AND METHODS: A literature search was conducted to identify articles utilizing outcome measures related to hip fracture. A total of five outcome measures were identified, linked to the ICF, and assessed for content validity via bandwidth percent, content density, and content diversity. RESULTS: Outcome measures were linked to 191 ICF codes, most of which were associated with Activities and Participation. Notably, no outcome measure contained concepts linked to Personal Factors and Environmental Factors were underrepresented across all outcome measures. The modified Harris Hip Score had the highest content diversity (0.67), the Hip Disability and Osteoarthritis Outcome Score had the highest bandwidth of ICF content coverage (2.48), and the Oxford Hip Score had the highest content density (2.92). CONCLUSIONS: These results clarify the clinical applicability of outcome measures and guide development of hip fracture outcomes that allow providers to assess the complex role of social, environmental, and personal factors in patient rehabilitation.IMPLICATIONS FOR REHABILITATIONHip fracture is a complex and disabling pathology predominantly affecting older adults and represents a public health problem.There are a variety of outcome measures used to assess a patient's recovery following a hip fracture, each with distinctive objectives and modes of administration.Content validity metrics associated with the Harris Hip Score suggest it would be a suitable outcome measure during early-stage recovery, whereas the modified Harris Hip Score may be more suitable for tracking long-term recovery tracking.Choosing an outcome measure most appropriate for a hip fracture patient is an individualized decision that must consider aspects such as age, activity level, needs, and environmental factors.
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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 | 0.282 | 0.562 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.065 | 0.052 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".