Schroth Physiotherapeutic Scoliosis-Specific Exercise (PSSE) Trials—Systematic Review of Methods and Recommendations for Future Research
Bibliographic record
Abstract
The Schroth method is a non-operative treatment for scoliosis and kyphosis, used standalone or as an adjunct to bracing. While supporting evidence for its effectiveness is emerging, methodologic standardization and rigor are equivocal. Thus, we aimed to systematically review methods of published Schroth physiotherapeutic scoliosis-specific exercise (PSSE) trials and provide guidance for future research. We searched six databases for randomized controlled trials (RCT) and non-randomized studies of interventions (NRSIs) investigating the effect of Schroth in children and adults with scoliosis or kyphosis. General characteristics, methodological approaches, treatment protocols, and outcomes reporting were analyzed. Risk of bias (RoB) was assessed using an adapted Cochrane RoB2 tool for RCTs and ROBINS-I for NRSI. Eligible studies (n = 7) were conducted in six countries and included patients with Scheuermann’s kyphosis (n = 1) and adolescent idiopathic scoliosis (n = 6). Though all seven studies used the term Schroth to describe their interventions, the Schroth method was used in four of seven studies, of which only one used Schroth classification, three used Schroth therapists, and none prospectively registered the study protocol. Overall, methodological rigor was suboptimal, potentially invalidating evidence synthesis. Authors should follow minimum standards for reporting, including prospectively registering detailed protocols; using appropriate exercise labeling, Schroth classification and certified therapists; naming and describing exercises per classification; and providing therapy dosages, prescription methods, and adherence.
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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 | 0.108 | 0.261 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.019 | 0.019 |
| Bibliometrics | 0.018 | 0.017 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".