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Record W4414968604 · doi:10.1186/s13018-025-06301-1

Cross-cultural adaptation and validation of the 12-item short forms of the knee injury and osteoarthritis outcome score (KOOS-12) to Persian language

2025· article· en· W4414968604 on OpenAlexaboutno aff
Fereshteh Kazemi Pakdel, Ahmad Kazemi Pakdel, Ali Asghar Norasteh

Bibliographic record

VenueJournal of Orthopaedic Surgery and Research · 2025
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsPersianOsteoarthritisAdaptation (eye)Orthopedic surgeryInternal consistencyOutcome (game theory)Consistency (knowledge bases)Perspective (graphical)

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of this study was to translate, culturally adapt, and validate the 12-item short form of the knee injury and osteoarthritis outcome score (KOOS-12) for use in the Persian language. METHODS: This study employed a cross-sectional design involving 105 participants with moderate to severe knee osteoarthritis (OA). The Persian version of the KOOS-12 was administered to assess its test-retest reliability, internal consistency, and construct validity. Test-retest reliability was evaluated using the intraclass correlation coefficient (ICC), with values above 0.75 indicating excellent reliability. Internal consistency was assessed using Cronbach's alpha, where values between 0.70 and 0.90 indicate good to excellent consistency. Construct validity was examined through Pearson correlation coefficients, comparing KOOS-12 scores with established measures such as the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), cincinnati knee rating system (CKRS), Oxford knee score (OKS), and knee society knee scoring system (KSS). Additionally, the standard error of measurement (SEM) and minimal detectable change (MDC) were calculated to provide insights into the measurement's precision and responsiveness, with SEM calculated as SD × √(1-R) and MDC as 1.96 × √2 × SEM. RESULTS: The Persian version of the KOOS-12 was administered to assess its construct validity, test-retest reliability, and internal consistency. Construct validity was evaluated through Pearson correlation coefficients, revealing strong correlations with the KOOS (r = 0.81), moderate correlation with the CKRS (r = 0.56), and strong negative correlation with the WOMAC (r = - 0.77), along with strong correlations with the OKS (r = 0.71) and the KSS (r = 0.73). Test-retest reliability was assessed using the ICC, with values above 0.75 indicating excellent reliability. Internal consistency was measured using Cronbach's alpha, where values between 0.70 and 0.90 indicate good to excellent consistency. CONCLUSION: The analysis of the Persian KOOS-12 questionnaire confirms its excellent reliability, validity, and suitability for clinical use, supported by excellent internal consistency and excellent test-retest reliability. These findings underscore the importance of culturally adapted instruments and indicate the need for future research to evaluate the KOOS-12's responsiveness to clinical changes over time.

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)0.011
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.061
GPT teacher head0.367
Teacher spread0.306 · 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 designBench or experimental
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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Citations1
Published2025
Admission routes1
Has abstractyes

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