Validation of a new test that assesses functional performance of the upper extremity and neck (FIT-HaNSA) in patients with shoulder pathology
Bibliographic record
Abstract
BACKGROUND: There is a lack of standardized tests that assess functional performance for sustained upper extremity activity. This study describes development of a new test for measuring functional performance of the upper extremity and neck and assesses reliability and concurrent validity in patients with shoulder pathology. METHODS: A series of developmental tests were conducted to develop a protocol for assessing upper extremity tasks that required multi-level movement and sustained elevation. Kinematics of movement were investigated to inform subtask structure. Tasks and test composition were refined to fit clinical applicability criteria and pilot tested on 5 patients awaiting surgery for shoulder impingement and age-sex matched controls. Test-retest reliability was assessed on 10 subjects. Then a cohort of patients with mild to moderate (n = 17) shoulder pathology and 19 controls (17 were age-sex matched to patients) were tested to further validate the Functional Impairment Test-Hand, and Neck/Shoulder/Arm (FIT-HaNSA) by comparing it to self-reported function and measured strength. The FIT-HaNSA, DASH and SPADI were tested on a single occasion. Impairments in isometric strength were measured using hand-held dynamometry. Discriminative validity was determined by comparing scores to those of age-sex matched controls (n = 34), using ANOVA. Pearson correlations between outcome measures (n = 41) were examined to establish criterion and convergent validity. RESULTS: A test protocol based on three five-minute subtasks, each either comprised of moving objects to waist-height shelves, eye-level shelves, or sustained manipulation of overhead nuts/bolts, was developed. Test scores for the latter 2 subtasks (or total scores) were different between controls as compared to either surgical-list patients with shoulder impingement or a variety of milder shoulder pathologies (p < 0.01). Test 1 correlated the highest with the DASH (r = -0.83), whereas Test 2 correlated highest with the SPADI (r = -0.76). CONCLUSION: Initial data suggest the FIT-HaNSA provides valid assessment of impaired functional performance in patients with shoulder pathology. It discriminates between patients and controls, is related to self-reported function, and yet provides distinct information. Longitudinal testing is warranted.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".