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Record W4413269910 · doi:10.1186/s12891-025-09009-9

Adaptation and psychometric evaluation of the Chinese version of the hip disability and osteoarthritis outcome Score–Physical function Short-form (HOOS-PS)

2025· article· en· W4413269910 on OpenAlexaboutno aff
Mengyuan He, Benjing Song, Haiyan Hu, Dongfa Liao, Lin Cui, Li Yin, Lin Wu, Amuyida, Shihong Li, Yingchao Tang, Jianxiang Long, Qingyun Xie, Wei Wang

Bibliographic record

VenueBMC Musculoskeletal Disorders · 2025
Typearticle
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsnot available
FundersSichuan Province Science and Technology Support Program
KeywordsMedicinePhysical therapySports medicineOsteoarthritisRehabilitationPhysical medicine and rehabilitationAdaptation (eye)Orthopedic surgeryRheumatologyInternal medicineAlternative medicineSurgeryPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Chronic hip joint disease has a high prevalence in China, and the primary scale currently used to assess functional recovery after total hip arthroplasty (THA) is the Hip disability and Osteoarthritis Outcome Score - Physical Function Short-form (HOOS-PS). Therefore, our objective was to translate the HOOS-PS scale into Simplified Chinese and evaluate its reliability, validity, and responsiveness in THA patients. METHODS: First, we followed the widely accepted cross-cultural translation process to translate the original HOOS-PS into the Chinese version of HOOS-PS (CHOOS-PS). Then, we recruited patients with chronic hip joint disease who were scheduled to undergo THA to complete the Western Ontario and McMaster Universities Arthritis Index (WOMAC), the Oxford Hip Score (OHS), Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) and CHOOS-PS scales. Subsequently, we calculated the standardized response mean (SRM), effect size (ES), Spearman correlation coefficient (rs), standard error of measurement (SEM), intraclass correlation coefficient (ICC), Cronbach’s alpha coefficient, and confirmatory factor analysis (CFA) based on the scale scores. RESULT: Ultimately, 142, 138, and 109 patients completed the scale assessments at three stages. The results showed that CHOOS-PS has excellent test-retest reliability (ICC = 0.848–0.919) and good internal consistency (Cronbach’s alpha = 0.892). The CHOOS-PS questionnaire demonstrated excellent correlation with the OHS scale (rs = 0.874), good correlation with all three subscales of the WOMAC (rs = 0.638–0.764), moderate to good correlation with the physical dimensions of the SF-36 (rs = 0.424–0.693), and poor to fair correlation with the mental dimensions of the SF-36 (rs = 0.165–0.319). The CFA results showed a good fit (root mean square error of approximation (RMSEA) = 0.050, the comparative fit index (CFI) = 0.995, and the Tucher-Lewis Index (TLI) value = 0.991). These results indicate that the HOOS-PS scale has good construct validity. Additionally, CHOOS-PS showed good responsiveness (ES = 1.93, SRM = 1.88). CONCLUSION: The CHOOS-PS scale is a reliable tool for evaluating the functional outcomes of Chinese patients with chronic hip joint disease after THA.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.023
GPT teacher head0.318
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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