Age Differences in Energy Absorption in the Upper Extremity During a Descent Movement: Implications for Arresting a Fall
Bibliographic record
Abstract
BACKGROUND: Falls are the number one cause of unintentional injury in older adults. The protective response of "breaking the fall" with the outstretched hand is often essential for avoiding injury to the hip and head. In this study, we compared the ability of young and older women to absorb the impact energy of a fall in the outstretched arms. METHODS: Twenty young (mean age = 21 years) and 20 older (M = 78 years) women were instructed to slowly lower their body weight, similar to the descent phase of a push-up, from body lean angles ranging from 15 degrees to 90 degrees . Measures were acquired of peak upper extremity energy absorption, arm deflection, and hand contact force. RESULTS: On average, older women were able to absorb 45% less energy in the dominant arm than young women (1.7 +/- 0.5% vs 3.1 +/- 0.4% of their body weight x body height; p < .001). These results suggest that, even when both arms participate equally, the average energy content of a forward fall exceeds by 5-fold the average energy that our older participants could absorb and exceeds by 2.7-fold the average energy that young participants could absorb. CONCLUSIONS: During a descent movement that simulates fall arrest, the energy-absorbing capacity of the upper extremities in older women is nearly half that of young women. Absorbing the full energy of a fall in the upper extremities is a challenging task even for healthy young women. Strengthening of upper extremity muscles should enhance this ability and presumably reduce the risk for injury to the hip and head during a fall.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".