The Reliability and Validity of Handheld Dynamometry for the Measurement of Lower-Extremity Muscle Strength in Older Adults
Bibliographic record
Abstract
Lower-extremity muscle strength is important in predicting fall risk in older adults. Handheld dynamometry (HHD) is a tool used to measure isometric muscle strength in the older adult, but few studies have evaluated the utility of HHD for muscle groups beyond knee extension. The purpose of this study was to evaluate the reliability of HHD at the hip, knee, and ankle and to compare HHD strength values to other isometric dynamometry (ID) and to balance and recovery in older adults. This was a repeated measures study design of 18 men and women, age 65 to 92 years of age, who had HHD strength testing 3 to 7 days apart by the same examiner and repeat testing on the same day using 2 independent examiners. ID strength, balance, step length, and reaction time were measured once. HHD demonstrated good intrarater and interrater reliability for isometric strength at the hip and knee but was not a reliable measure for ankle strength. The HHD was a valid measure of isometric strength at the hip and knee, demonstrating moderate to high correlation values when compared to ID strength measures (r = 0.57-0.86; p < 0.05). Hip and knee strength was positively associated to step length and reaction time but not to balance (r = 0.40-0.71; p < 0.05). In conclusion, HHD is a reliable and valid assessment tool for measuring strength at the hip and knee in older adults, and greater strength in these muscles is associated with longer step length and decreased reaction time, which are important components of balance recovery in older adults. HHD can be used as an effective strength measurement tool for the older adult population.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".