A Higher-Order Analysis Supports Use of the 11-Item Version of the Tampa Scale for Kinesiophobia in People With Neck Pain
Bibliographic record
Abstract
BACKGROUND: Despite increasing clinical and research use of the 11-item version of the Tampa Scale for Kinesiophobia (TSK-11) in people with neck pain, little is known about its measurement properties in this population. OBJECTIVE: The purpose of this study was to rigorously evaluate the measurement properties of the TSK-11 when used in people with mechanical neck pain. DESIGN: This study was a secondary analysis of 2 independent databases (N=235) of people with mechanical neck pain of primarily traumatic origin. METHODS: The TSK-11 was subjected to Rasch analysis and subsequent evaluation of concurrent associations with the Neck Disability Index and a numeric rating scale for pain intensity. RESULTS: The TSK-11 conformed well to the Rasch model for interval-level measurement, but less so for acute or nontraumatic etiologies. A transformation matrix suggested that small changes at the extremes of the scale are more meaningful than in the middle. Cross-sectional convergent validity testing suggested relationships of expected magnitude and direction compared with pain intensity and neck-related disability. The use of the linearly transformed TSK-11 led to potentially important differences in distribution of data compared with use of the raw scores. LIMITATIONS: The sample size was slightly smaller than desired for Rasch analysis. The 2 databases were similar in terms of symptom duration, but differed in pain intensity and age. CONCLUSIONS: The TSK-11 can be considered an interval-level measure when used in people with neck pain. It provides potentially important information regarding the nature of neck-related disability. Clinically important difference may not be consistent across the range of the scale.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".