Intra and Inter-Rater Reliability and Convergent Validity of FIT-HaNSA in Individuals with Grade П Whiplash Associated Disorder
Bibliographic record
Abstract
BACKGROUND: Whiplash-Associated Disorders (WAD) are common following a motor vehicle accident. The Functional Impairment Test - Hand, and Neck/Shoulder/Arm (FIT-HaNSA) assesses upper extremity physical performance. It has been validated in patients with shoulder pathology but not in those with WAD. OBJECTIVES: Establish the Intra and inter-rater reliability and the known-group and construct validity of the FIT-HaNSA in patients with Grade II WAD (WAD2). METHODS: Twenty-five patients with WAD2 and 41 healthy controls were recruited. Numeric Pain Rating Scale (NPRS), Neck Disability Index (NDI), Disabilities of the Arm, Shoulder and Hand (DASH), cervical range of motion (CROM), and FIT-HaNSA were completed at two sessions conducted 2 to 7 days apart by two raters. Intraclass correlation coefficients (ICC) were used to describe Intra and inter-rater reliability. Spearman rank correlation coefficients (ρ) were used to quantify the associations between scores of the FIT-HaNSA and other measures in the WAD2 group (convergent construct validity). RESULTS: The Intra and inter-ICCs for the FIT-HaNSA scores ranged from 0.88 to 0.89 in the control group and 0.78 to 0.85 in the WAD2 group. Statistically significant differences in FIT-HaNSA performance between the two groups suggested known group construct validity (P < 0.001). The correlations between the NPRS, NDI, DASH, CROM and FIT-HaNSA were generally poor (ρ < 0.4). CONCLUSION: The study results indicate that the total FIT-HaNSA score has good Intra and inter-rater reliability and the construct validity in WAD2 and healthy controls.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".