Discussing Conflicting Explanatory Approaches in Flexibility Training Under Consideration of Physiology: A Narrative Review
Bibliographic record
Abstract
The mechanisms underlying range of motion enhancements via flexibility training discussed in the literature show high heterogeneity in research methodology and study findings. In addition, scientific conclusions are mostly based on functional observations while studies considering the underlying physiology are less common. However, understanding the underlying mechanisms that contribute to an improved range of motion through stretching is crucial for conducting comparable studies with sound designs, optimising training routines and accurately interpreting resulting outcomes. While there seems to be no evidence to attribute acute range of motion increases as well as changes in muscle and tendon stiffness and pain perception specifically to stretching or foam rolling, the role of general warm-up effects is discussed in this paper. Additionally, the role of mechanical tension applied to greater muscle lengths for range of motion improvement will be discussed. Thus, it is suggested that physical training stressors can be seen as external stimuli that control gene expression via the targeted stimulation of transcription factors, leading to structural adaptations due to enhanced protein synthesis. Hence, the possible role of serial sarcomerogenesis in altering pain perception, reducing muscle stiffness and passive torque, or changes in the optimal joint angle for force development is considered as well as alternative interventions with a potential impact on anabolic pathways. As there are limited possibilities to directly measure serial sarcomere number, longitudinal muscle hypertrophy remains without direct evidence. The available literature does not demonstrate the necessity of only using specific flexibility training routines such as stretching to enhance acute or chronic range of motion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".