Generalizability of Results from Randomized Controlled Trials in Post-Stroke Physiotherapy
Bibliographic record
Abstract
Purpose: The randomized controlled trial (RCT) is considered a reliable experimental design, able to detect the effect of an intervention. However, a criticism frequently levelled at RCTs by clinicians is their lack of generalizability. This study aimed to evaluate the generalizability of findings from RCTs of physiotherapy interventions for individuals with stroke. Method: A sample of RCTs of physiotherapy interventions after stroke indexed in the PEDro database was selected, and the reported inclusion and exclusion criteria were analyzed. Results: We reviewed 100 articles, which included 7,366 participants (41.6% women, with a mean weighted age of 65.5 years). The most frequent criteria for exclusion were comorbidity (83%), cognitive impairments (69%), communication skills (55%), recurrent stroke (53%), low functional level (47%) and being elderly (25%). Conclusions: A variety of cohorts of individuals who have had a stroke are excluded from RCTs published in the field of physiotherapy. Because they represent a substantial proportion of the real-world population with stroke, and consequently treated in clinical practice, more vulnerable cohorts of participants should be included in RCTs.
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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 | 0.668 | 0.869 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.022 |
| Bibliometrics | 0.016 | 0.013 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".