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Record W2609041782 · doi:10.21315/mjms2017.24.2.8

Reliability and Validity of the Cross-Culturally Adapted Thai Version of the Tampa Scale for Kinesiophobia in Knee Osteoarthritis Patients

2017· article· en· W2609041782 on OpenAlexaboutno aff
Pattanasin Areeudomwong, Vitsarut Buttagat

Bibliographic record

VenueMalaysian Journal of Medical Sciences · 2017
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsOsteoarthritisConvergent validityReliability (semiconductor)Physical therapyPsychologyScale (ratio)Visual analogue scaleDiscriminant validityTest (biology)ValidityClinical psychologyInternal consistencyPsychometricsMedicineAlternative medicine

Abstract

fetched live from OpenAlex

PURPOSE: The aim of this study was to develop a cross-culturally adapted Thai version of the Tampa Scale for Kinesiophobia (TSK) and investigate its reliability and validity among patients with knee osteoarthritis. METHODS: The TSK was translated into Thai language and culturally adapted in line with the international standards. The Thai TSK questionnaire was then tested for internal consistency, test-retest reliability, and convergent validity by comparing it with the visual analogue scale, Western Ontario and McMaster Universities Osteoarthritis Index, State-Trait Anxiety Inventory, and Timed Up and Go Test. RESULTS: = 0.741, 0.856, and 0.817, respectively). However, there was no significant correlation between the Thai version of the TSK scores and the Timed Up and Go Test results. CONCLUSION: The Thai version of the TSK has satisfactory reliability and validity for the evaluation of pain-related fear of movement/(re)injury in patients with knee osteoarthritis.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.012
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.296
Teacher spread0.273 · 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 teacher head, 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

Citations29
Published2017
Admission routes1
Has abstractyes

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