Dual-task training is as effective as functional training on the functional fitness of older women: a randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: The interest in approaches that improve older individuals' functional fitness and autonomy is increasing. However, the effects of dual-task training on older women's functional fitness and the comparison with the functional training approach are unclear. Therefore, we compared dual-task and functional training on the functional fitness of older women and the effects of three months of detraining. METHODS: Sixty-one women performed 16 weeks of dual-task training or functional training. The functional fitness was measured pre-, post-training, and post-detraining, based on the ability to put on and take off a t-shirt, evaluating the mobility of the upper limb, standing-up from the prone position measuring the global functionality, five times sit-to-stand test to assess the lower limbs muscle power, timed up and go to measure the dynamic balance and agility, gallon-jug shelf-transfer to evaluate the global functionality emphasizing the upper limbs and 10 m walk test to analyze the gait ability. RESULTS: Dual-task training and functional training generally provided significant small to moderate magnitude performance increases in the put on and take off a t-shirt (dual-task training: d = 0.35 / functional training: d = 0.49), five times sit-to-stand test (dual-task training: d = 0.41 / functional training: d = 0.77), timed up and go (dual-task training: d = 0.34 / functional training: d = 0.78), and gallon-jug shelf-transfer (dual-task training: d = 0.76 / functional training: d = 0.82). Only the functional training improved the 10 m walk test (d = 0.32; p = 0.013), and both groups did not change the standing-up from the prone position performance. After the detraining period, both groups kept the adaptations for the gallon-jug shelf-transfer and five times sit-to-stand test. At the same time, only the dual-task training maintained the adaptations for the put on and take off a t-shirt and the functional training for the timed up and go. CONCLUSION: Sixteen weeks of dual-task and functional training are similarly effective in improving older women's functional fitness, maintaining their benefits even after three months of detraining. TRIAL REGISTRATION: RBR-10ny848z ( https://ensaiosclinicos.gov.br/rg/RBR-10ny848z ).
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".