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Record W3012113470 · doi:10.3138/ptc-2018-0117

Generalizability of Results from Randomized Controlled Trials in Post-Stroke Physiotherapy

2020· article· en· W3012113470 on OpenAlexvenueno aff
Matteo Paci, Claudia Prestera, Francesco Ferrarello

Bibliographic record

VenuePhysiotherapy Canada · 2020
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsGeneralizability theoryMedicineRandomized controlled trialStroke (engine)Physical therapyPsychological interventionInclusion and exclusion criteriaComorbidityPopulationPsychologySurgeryInternal medicinePsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.018
GPT teacher head0.307
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2020
Admission routes1
Has abstractyes

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