Implications of Walking Aid Selection for Nonweightbearing Ambulation on Stance Limb Plantar Force, Walking Speed, Perceived Exertion, and Device Preference in Healthy Adults 50 Years of Age and Older
Bibliographic record
Abstract
Background: Young adults often tolerate the increased energy expenditure, coordination, and stance limb discomfort associated with walking aids for nonweightbearing ambulation. Adults aged ≥50 years may not have the same tolerance. Therefore, the objective of this study was to determine how walking aid selection affects stance limb plantar force, walking speed, perceived exertion, and device preference in adults aged ≥50 years. Methods: A prospective randomized crossover study was performed using healthy adults, aged ≥50 years, with no use of walking aids within 5 years. Participants walked 200 m in 4 randomized conditions: single nonweightbearing ambulation using crutches, a walker, a wheeled knee walker, and unaided walking. An in-shoe sensor measured stance limb plantar force, a stopwatch timed each walk, perceived exertion was reported using the BORG CR-10 scale, and device preference was identified. Results: Twenty-one participants (7 male; age: 56 ± 5 years; BMI: 26.6 ±1.9) showed stance limb plantar force was lowest when using a wheeled knee walker ( P < .001). Walking speed was similar in unaided and wheeled knee walker conditions (1.41 and 1.31 m/s), but slower with crutches or a walker (42%-68%, P < .001). Perceived exertion was similar in unaided and wheeled knee walker conditions (1.6 and 2.8), but higher with crutches or a walker (5.7 and 6.1, P < .001). Most (20/21) participants preferred the wheeled knee walker. Conclusions: Using a wheeled knee walker for nonweightbearing ambulation reduced stance limb plantar force, maintained unaided walking speed and perceived exertion, and was preferred to crutches or a walker. Level of Evidence: Level II, comparative study.
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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 | 0.001 | 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) | 0.001 | 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".