Effects of massage on the mechanical behaviour of muscles in adolescents with spastic diplegia: a pilot study
Bibliographic record
Abstract
Calf muscles of five adolescents aged 12 to 15 years (three males, two females) with spastic diplegia were massaged for 14 minutes twice a week for 5 weeks in a controlled sequence, stretching the muscles transversely rather than longitudinally, without eliciting pain. Slow, passive test stretches were applied before and after massage. After massage, the range of movement was not consistently increased but, on average, greater force was needed to stretch the muscle than before massage. However, after massage the resting ankle angle sometimes changed so that the calf muscles were either shorter or longer. We suggest that these phenomena could be explained if massage resets sarcomere lengths which corrects for thixotropic effects (i.e. previous use modifies a muscle's mechanical behaviour). A redistribution on sarcomere lengths within muscles could also have reset proprioceptive feedback. The incidence of abnormal stretch reflexes during test stretches fell from 40 to 22%, comparing the first five sessions with the last five sessions. The amplitude of voluntary alternating ankle rotation increased in three participants. Motor skills were assessed with the Gross Motor Function Measure-66 (GMFM-66) 1 week before the test period, during the 5th week, and 12 weeks later. Our participants in Gross Motor Function Classification System (GMFCS) Levels I and II made sustained improvements in GMFM-66 scores (6.4% at 5 weeks falling to 5.5% at 17 weeks), one increase being significant. One participant in GMFCS Level III improved significantly only after massage of all leg muscles for 30 weeks.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".