Active movement measurements of the shoulder girdle in healthy subjects with goniometer and tape measure techniques: A study on reliability and validity
Bibliographic record
Abstract
In response to the current need to develop objective measurement techniques for active movements of the shoulder girdle, this study had two goals: 1) to evaluate the reliability of the active range of motion (AROM) of shoulder girdle in elevation, protraction, and retraction with use of a goniometer and a tape measure and 2) to present the criterion-related validity of the reliable movements. Thirty healthy subjects performed two trials of each shoulder girdle AROM. They were assessed by two physical therapists, who used both evaluation techniques on two occasions. The generalizability theory was used to compute intratester (test-retest) and intertester reliability using dependability coefficients (phi) and standard errors of measurement (SEMs). The shoulder girdle movements were then evaluated with a movement analysis system (Optotrak 3020). The Pearson product-moment correlation coefficient (r) and paired t-tests were used to compare the results of clinical measurements with those of the movement analysis system. Overall, the reliability with the tape measure was good (phi = 0.78-0.91; SEM's = 0.7-1.1 cm) for the elevation motion. The goniometer was only reliable for intratester measures (phi = 0.78-0.79; SEM = 2.7 degrees) for the elevation motion. Retraction was reliable with the tape measure alone (phi = 0.76-0.84; SEM's = 0.5-0.7 cm). The criterion-related validity analysis revealed that measuring shoulder girdle elevation with the tape measure and goniometer, and retraction with the tape measure were not valid when evaluated against a gold standard, thus, both techniques have limitations in assessing true elevation and retraction measurements.
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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 | 0.013 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".