Are Caffeine’s Effects on Resistance Exercise and Jumping Performance Moderated by Training Status?
Bibliographic record
Abstract
This study aimed to explore if the effects of caffeine intake on resistance exercise and jumping performance are moderated by training status. We included ten resistance-trained and ten recreationally active males in a randomized, double-blind, crossover study. Participants were categorized into groups according to their resistance to training experience and muscular strength levels. Exercise performance outcomes included weight lifted and mean velocity during a one-repetition maximum (1RM) bench press and squat; repetitions were performed to muscular failure in the same exercises with 70% of 1RM and countermovement jump (CMJ) height. Exercise performance was evaluated on three occasions, following no substance ingestion (control), caffeine (6 mg/kg), and placebo. There was a main effect on the condition for all the performance outcomes (all p ≤ 0.02), except for the 1RM squat mean velocity (p = 0.157) and 1RM bench press mean velocity (p = 0.719). For weight lifted in the 1RM bench press, there was a significant difference when comparing the caffeine vs. control, caffeine vs. placebo, and placebo vs. control. For weight lifted in the 1RM squat, a significant difference was found when comparing the caffeine vs. control. For muscular endurance outcomes and jump height, a significant difference was found when caffeine was compared to the control or placebo. Effect sizes were trivial for muscular strength (Hedges’ g: 0.04–0.12), small for the jump height (Hedges’ g: 0.43–0.46), and large for muscular endurance (Hedges’ g: 0.89–1.41). Despite these ergogenic effects, there was no significant training status × caffeine interaction in any of the analyzed outcomes. In summary, caffeine ingestion is ergogenic for muscular strength, endurance, and jump height. These effects are likely to be of a similar magnitude in resistance-trained and recreationally active men.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".