Repeatability of joint proprioception and muscle torque assessment in healthy children and in children diagnosed with hypermobility syndrome
Bibliographic record
Abstract
BACKGROUND: Impairment of joint proprioception in patients with hypermobility syndrome (HMS) has been well documented. Both joint proprioception and muscle torque are commonly assessed in patients with musculoskeletal complaints. It is unknown, however, if these measures change significantly on repeated application in healthy children and in children with HMS. AIM: To investigate the between-days repeatability of joint proprioception and muscle torque in these groups. METHODS: Twenty children (10 healthy and 10 with HMS), aged eight to 15 years, were assessed on two separate occasions (one week apart) for joint kinaesthesia (JK), joint position sense (JPS), and the extensor and knee flexor muscle torque of the knee. JK was measured using threshold to detection of passive movement. JPS was measured using the absolute angular error (AAE; the absolute difference between the target and perceived angles). Knee extensor and flexor muscle torque was normalized to body weight. RESULTS: Intra-class correlation coefficients (ICC) for JK, extensor and flexor muscle torque were excellent in both groups (range 0.83 to 0.98). However, ICC values for JPS tests were poor to moderate in the two groups (range 0.18 to 0.56). 95% limits of agreement (LOA) were narrow in both cohorts for JK and muscle torque (indicating low systematic error) but wide for the JPS tests. 95% LOA also demonstrated that the measuring instruments used in this study had low between-days systematic error. CONCLUSIONS: Based on ICC and 95% LOA, the repeatability of JK and muscle torque measurements was excellent in both healthy children and those with HMS. The JPS test can only be assessed with poor to moderate repeatability. The use of the JPS test in these children should be undertaken with caution.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| 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".