Cross-cultural adaptation, reliability, and validity of the Northern Thai version of the Tampa scale of kinesiophobia-17 in community-dwelling individuals with knee osteoarthritis
Bibliographic record
Abstract
This study was designed to determine the validity and reliability of the northern Thai version of the TSK-17 in community-dwelling people with knee osteoarthritis (KOA). Participants with knee osteoarthritis living in Chiang Rai province were invited to participate in this study and were asked to complete the northern Thai version of the questionnaire. TSK-17 northern Thai version was administered twice with a seven-day interval, as was the Thai version of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Furthermore, the participants completed the Thai version of the medical outcomes study short-form survey version 2.0 (SF-36V2) and a timed-up and go test (TUGT). The findings revealed that 50 people took part in this study and completed the northern Thai version of the TSK-17 in five minutes. The TSK-17 northern Thai version demonstrated high internal consistency (α = 0.80) and test-retest reliability (ICC2,1 = 0.84). Convergent validity demonstrated a strong correlation with the Thai version of WOMAC (r = 0.70) and a weak correlation with the TUGT (r = 0.45). According to the findings of this study, the northern Thai version of the TSK-17 has acceptable validity and reliability for evaluating fear of movement in community-dwelling individuals with KOA.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".