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Record W3045400550 · doi:10.3233/nre-203168

Differences in stroke rehabilitation motor and cognitive randomized controlled trials by world region: Number, sample size, and methodological quality

2020· article· en· W3045400550 on OpenAlexaff
Amanda McIntyre, Shannon Janzen, Jerome Iruthayarajah, Marcus Saikaley, Dan Sequeira, Robert Teasell

Bibliographic record

VenueNeurorehabilitation · 2020
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsSt Joseph's Health CareWestern UniversityParkwood Institute
Fundersnot available
KeywordsRehabilitationRandomized controlled trialStroke (engine)CognitionSample size determinationPhysical medicine and rehabilitationMedicinePhysical therapySample (material)Quality (philosophy)PsychologyPsychiatryInternal medicineStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: Stroke rehabilitation research is important for informing clinical practice and directing health care resources. OBJECTIVE: To examine how motor- and cognitive-based stroke rehabilitation randomized controlled trials (RCTs) vary by world region, overall and over time, with respect to 1) publication volume, 2) sample size, and 3) methodological quality. METHODS: Using the Evidence-Based Review of Stroke Rehabilitation (EBRSR), all motor- and cognitive-based stroke rehabilitation RCTs were identified. The following data were extracted: first author, year of publication, country of origin, and sample size. Countries were categorized into seven regions, as defined by the World Bank. RESULTS: In total 1410 motor-based RCTs and 293 cognitive-based RCTs were published between 1972-2018. For motor RCTs, the East Asia/Pacific region accounted for the largest volume of RCTs (n = 530; 37.6%), followed closely by the Europe/Central Asia region (n = 445; 31.6%). Conversely, the largest producer for cognitive RCTs was Europe/Central Asia (n = 167; 57.0%), followed by East Asia/Pacific (n = 62; 21.2%). For both motor and cognitive RCTs, there was no significant difference between world regions with respect to mean sample size or methodological quality. CONCLUSIONS: Efforts should be directed towards improving methodological quality and increasing sample sizes of stroke rehabilitation-related studies.

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)0.008
metaresearch head score (Gemma)0.434
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.434
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.119
GPT teacher head0.396
Teacher spread0.277 · 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.

Study designObservational
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

Citations8
Published2020
Admission routes1
Has abstractyes

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