Effects of Explosive vs. Strength Resistance Training on Plantar Flexor Neuromuscular and Functional Capacities in Institutionalized Older Adults: A Randomized Controlled Trial
Bibliographic record
Abstract
Objectives: To compare the effects of explosive and strength resistance training on neuromuscular and functional parameters in older adults and to analyze the relationship between changes in walking speed and improvements in plantar flexor (PF) neuromuscular parameters following interventions. Methods: In total, 40 participants were randomly assigned to either an explosive resistance training group (EXG, n = 18; age = 80.41 ± 10.12 years; body mass index = 22.89 ± 2.77 kg/m2) or a strength resistance training group (STG, n = 22; age = 82.89 ± 5.32 years; body mass index = 23.81 ± 3.45 kg/m2). Both groups participated in the same PF resistance training regimen (three sessions per week for 12 weeks), engaging in identical exercises. However, EXG performed three to five sets of 12 to 14 repetitions at 40% to 45% of one-maximal repetition with a rapid concentric phase and a 3 s eccentric phase, while the STG performed three to four sets of 6 to 7 repetitions at 80% to 85% of one-maximal repetition, with both phases lasting approximately 3 s. Before and after the interventions, gait speed (m/s) was assessed using a 10 m walking test, and relative maximal force (Relative Fmax, N/kg) was evaluated during maximal voluntary isometric contraction of PF. From the force–time curve, early (0–50 ms) and late (100–200 ms) rates of force development (RFD) were extracted from the linear slopes (Δ force/Δ time). Results: Gait speed significantly improved in both groups (p < 0.05). However, the improvement was more pronounced in the EXG compared to the STG (p < 0.05). Relative Fmax showed a more significant increase in the STG than in the EXG (p < 0.05). Moreover, a significant 10% increase in early RFD in the STG and a 20.1% increase in the EXG were observed (p < 0.05). The improvement in early RFD was greater in the EXG (p < 0.05). Additionally, late RFD improved significantly only in the EXG (+20.4%, p < 0.05). Conclusion: Explosive resistance training appears particularly effective in improving the ability to rapidly generate force, which is essential for many daily activities requiring explosive movements and quick responses.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| 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 | 0.002 | 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".