Pain-Related Fear in Adults Living With Chronic Pain: Development and Psychometric Validation of a Brief Form of the Tampa Scale of Kinesiophobia.
Bibliographic record
Abstract
OBJECTIVE: To develop and validate a brief version of the Tampa Scale of Kinesiophobia (TSK) while preserving content validity in a mixed chronic pain population. DESIGN: Cross-sectional study. SETTING: Tertiary care interdisciplinary chronic pain clinic. PARTICIPANTS: Adults with chronic pain (N=933; mean age, 53.5±15.7 years; 63% women). INTERVENTION: Not applicable. MAIN OUTCOME MEASURE: TSK-11 measured at intake. Self-reported data from a patient registry were extracted from November 2017 to October 2019. RESULTS: An exploratory factor analysis identified a 2-factor structure from the TSK-11 and item reduction resulted in a 7-item TSK (TSK-7) with 61.2% explained variance and Cronbach's alphas of 0.76 and 0.70 for each of the 2 factors. To maximally reduce the number of items without affecting internal consistency, a 5-item TSK (TSK-5) with 72% explained variance was also explored. Strong correlations were found between the newly developed brief TSK versions and TSK-11 (r>0.93), suggesting good concurrent validity. TSK-11, TSK-7, and TSK-5 had similar convergent validity with moderate correlations for pain catastrophizing (r=0.57, 0.58, 0.54), depression (r=0.45, 0.46, 0.42), pain interference (r=0.43, 0.44, 0.40), and pain acceptance (r=-0.57, -0.59, -0.55). CONCLUSIONS: These 2 brief versions of the TSK may help to simplify questionnaires across chronic pain centers where multiple outcome measures are used for a complete biopsychosocial assessment of patients.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".