Do Cheaters Prosper? Effect of Externally Supplied Momentum During Resistance Training on Measures of Upper Body Muscle Hypertrophy
Bibliographic record
Abstract
Exercise technique, defined as the controlled execution of bodily movements to ensure an exercise effectively targets specific muscle groups while minimizing the risk of injury, is a resistance training (RT) variable frequently highlighted as critical to successful RT program outcomes, with proper technique suggested to play a role in maximizing muscle development. This study examined the effects of externally applied momentum on RT-induced muscular adaptations in the upper extremities. Thirty young adults were recruited to participate in a within-participant design, with one limb randomly allocated to perform biceps curls and triceps pushdowns using strict form (STRICT) and the other using external momentum (CHEAT). Participants completed four sets of each exercise with 8-12 repetitions until momentary muscular failure, twice a week for eight weeks. We obtained pre-post proximal and distal measures of muscle thickness for the elbow flexors and extensors, and assessed circumference changes in the upper arms. Data were analyzed in a Bayesian framework including both univariate and multivariate mixed effect models with random effects. Differences between conditions were estimated as average treatment effects, with inferences based on posterior distributions and Bayes Factors (BFs). Results showed similar between-conditions increases for all muscle thickness sites as well as circumference measures, generating consistent support for the null hypothesis (BF = 0.06 to 0.61). Volume load was markedly greater for CHEAT compared to STRICT across each week of the intervention. In conclusion, the use of external momentum during single-joint RT of the upper extremities neither helped nor hindered hypertrophy of the target muscles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".