The Influence of Verbal Instruction on Measurement Reliability and Explosive Neuromuscular Performance of the Knee Extensors
Bibliographic record
Abstract
Abstract The current study aimed to examine the effect of verbal instruction on explosive force production and between-session measurement reliability during maximal voluntary contractions of knee extensors. Following familiarization, 20 healthy males performed 3 maximal contractions with a “hard-and-fast” instruction and 3 maximal contractions with a “fast” instruction during 2 test-retest sessions. Knee extension maximal voluntary force (Fmax) and the maximal rate of force development (RFDmax) were measured. Maximal electromechanical delay (EMDmax), and the maximal rate of muscle activation (RMAmax) of quadriceps muscles were determined. No significant effect of instruction was observed on Fmax (p > 0.05). The RFDmax and RMAmax were significantly higher with the “fast” compared to the “hard-and-fast” instruction (36.07%, ES = 1.99 and 37.24%, ES = 0.92, respectively), whereas EMDmax was significantly lower with the “fast” instruction compared to the “hard-and-fast” instruction (-3.79%, ES = - 0.29). No significant differences between test and retest measurements were found (p < 0.05). However, the reliability of the RFDmax was higher with the fast instruction compared to the hard-and-fast instruction (CV: 7.3 vs. 16.2%; ICC: 0.84 vs. 0.56). Besides, the RFDmax was associated with the RMAmax and EMDmax with a significant effect of instruction. Data showed that the instruction given prior contracting muscle affected explosive force production and associated neuromuscular variables. As a result, the “fast” instruction may be preferred in the assessment of explosive force capacity of skeletal muscle during maximal efforts.
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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 | 0.007 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".