Efficacy and Feasibility of Functional Upper Extremity Task-Specific Training for Older Adults With and Without Cognitive Impairment
Bibliographic record
Abstract
BACKGROUND: Although functional task-specific training is a viable approach for upper extremity neurorehabilitation, its appropriateness for older populations is unclear. If task-specific training is to be prescribed to older adults, it must be efficacious and feasible, even in patients with cognitive decline due to advancing age. OBJECTIVE: This cross-sectional study tested the efficacy and feasibility of upper extremity task-specific training in older adults, including those with lower cognitive scores. METHODS: Fifty older adults (age 65-89 years) without any confounding neuromuscular impairment were randomly assigned to a training group or no-training group. The training group completed 3 days (dosage = 2250 repetitions) of a functional upper extremity motor task (simulated feeding) with their nondominant hand; the no-training group completed no form of training at all. Both groups' task performance (measured as trial time) was tested at pre- and posttest, and the training group was retested 1 month later. Efficacy was determined by rate, amount, and retention of training-related improvement, and compared across levels of cognitive status. Feasibility was determined by participants' tolerance of the prescribed training dose. RESULTS: The training group was able to complete the training dose without adverse responses and showed a significant rate, amount, and retention of improvement compared with the no-training group. Cognitive status did not alter results, although participants with lower scores on the Montreal Cognitive Assessment were slower overall. CONCLUSIONS: Task-specific training may be appropriate for improving upper extremity function in older adults, yet future work in older patients with specific neurological conditions is needed.
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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 | 0.004 |
| 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".