Feasibility and effectiveness of a 6-month, home-based, resistance exercise delivered by a remote technological solution in healthy older adults
Bibliographic record
Abstract
BACKGROUND: Aging is characterized by a physiological decline in physical function, muscle mass, strength, and power. Home-based resistance training interventions have gained increasing attention from scientists and healthcare system operators, but their efficacy is yet to be fully determined. AIMS: to verify the safety, feasibility, and efficacy of a home-based resistance training program delivered by innovative technological solution in healthy older adults. METHODS: 73 participants (36 females) were randomly allocated to either a control (C) or an intervention (I) group consisting of a 6-months home-based resistance training program delivered through an innovative technological solution, which included a wearable inertial sensor and a dedicated tablet. The safety and feasibility of the intervention were assessed by recording training-related adverse events and training adherence. Body composition, standing static balance, 10-meter walking, and loaded 5 sit-to-stand tests were monitored to quantify efficacy. RESULTS: No adverse events were recorded. Adherence to the training program was relatively high (61 % of participants performed the target 3 sessions) in the first trimester, significantly dropping during the second one. The intervention positively affected walking parameters (p < 0.05) and maximal force (p = 0.009) while no effect was recorded on body composition, balance, and muscle power. CONCLUSIONS: The home-based device-supported intervention was safe and feasible, positively affecting walking parameters and lower limbs' maximal force. This approach should be incentivized when barriers to participation in traditional resistance exercise programs are present.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".