Effect of muscle training in adolescents and young adults with down syndrome: a systematic review and meta-analysis
Bibliographic record
Abstract
Purpose This study aims to synthesize existing evidence and assess the effectiveness of muscle training on limb strength in adolescents and young adults with Down syndrome.Materials and methods Randomized clinical trials up to November 2024 comparing progressive force exercise with daily activities were identified from PubMed, CINAHL, Cochrane Library, MEDLINE, Scopus, and PEDro. Two reviewers independently selected studies, extracted data and assessed quality. A random-effects model was used.Results Eight studies, including 266 adolescents and young adults with Down syndrome, were incorporated into the systematic review and meta-analysis. Muscle training showed a moderate positive effect on strength (Standardized Mean Difference (SMD) = 0.67), with greater effects in the lower limbs (SMD = 0.75). The most effective intervention was an Isokinetic training program + conventional physical therapy program (SMD = 1.24). The duration of training did not affect the outcome, but longer programs had no heterogeneity (I2 = 0%).Conclusions Muscle training seems to moderately improve strength in adolescents and young adults with Down syndrome, particularly in the lower limbs. Although training duration is not decisive, longer programs provide more consistent improvements. Further large-scale studies with standardized assessments are needed, particularly in young adults facing premature aging.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.023 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".