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Record W4412583682 · doi:10.3389/fmed.2025.1613589

Cross-cultural adaptation and validation of the Chinese version of the 25-question Geriatric Locomotive Function Scale in patients undergoing total knee arthroplasty

2025· article· en· W4412583682 on OpenAlexaboutno aff
Zhipeng Tai, Dongping Wan, Shuxin Yao, Shaohua Miao, Qiang Zan, Yanchen Tan, Jianbing Ma, Chao Xu

Bibliographic record

VenueFrontiers in Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
FundersKey Research and Development Projects of Shaanxi ProvinceYakult Bio-Science FoundationHonghui Hospital
KeywordsMedicinePhysical therapyWOMACCronbach's alphaExploratory factor analysisPsychosocialReliability (semiconductor)Scale (ratio)ArthroplastyOsteoarthritisPsychometricsPhysical medicine and rehabilitationClinical psychologySurgeryAlternative medicine

Abstract

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Background: Knee osteoarthritis (KOA) is prevalent among the elderly, often necessitating total knee arthroplasty (TKA) for severe cases. However, traditional assessment tools primarily focus on pain and physical function, neglecting the psychosocial aspects that influence postoperative satisfaction. The 25-question Geriatric Locomotive Function Scale (GLFS-25) is a comprehensive measure of locomotor function, however, it has limited validation within populations in Mainland China. Objectives: This study aimed to translate, cross-culturally adapt, and validate the Chinese version of the GLFS-25 (GLFS-25CV) for evaluating postoperative outcomes in TKA patients with KOA. Methods: Following established guidelines, the English GLFS-25 was both forward- and back-translated, subjected to expert review, and pretested in 30 patients. End-stage KOA patients scheduled for primary unilateral TKA were then recruited, with a subset completing the GLFS-25CV twice, one week apart, to assess test-retest reliability. Exploratory factor analysis (EFA) was conducted to evaluate structural validity, while convergent validity was assessed through Pearson correlations with the Oxford Knee Score (OKS), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and the 5-Level EuroQol Five-Dimensional Questionnaire (EQ-5D-5L). Internal consistency was evaluated using Cronbach's α, and standard deviations (SD) were calculated. Additionally, floor and ceiling effects were analyzed based on score distributions. Results: A total of 295 participants completed the study. Both the four-factor model identified by EFA, which explained 58% of the total variance, and the strong correlations with the OKS (rho = 0.85), the WOMAC (rho = 0.77), and the EQ-5D-5L (rho = 0.66) collectively confirm the excellent validity of the GLFS-25CV. Internal consistency was excellent (Cronbach's α = 0.94, SD > 0.85), and test-retest reliability (ICC = 0.94-0.97) was also strong, confirming its overall reliability. Neither floor nor ceiling effects were significant, and no participants reported difficulty completing the instrument. Conclusion: The GLFS-25CV is a reliable, valid, and user-friendly tool for assessing knee function in individuals in mainland China undergoing TKA for KOA. By incorporating both physical and psychosocial domains, it offers a comprehensive evaluation that is well-suited for both clinical practice and research applications.

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)0.011
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 score0.007
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.005
GPT teacher head0.248
Teacher spread0.243 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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