A Systematic Review of Female Participation in Randomized Controlled Trials of Post-Stroke Upper Extremity Rehabilitation in Low- to Middle-Income Countries and High-Income Countries and Regions
Bibliographic record
Abstract
INTRODUCTION: Female participation is lower than males in both acute stroke and stroke rehabilitation trials. However, less is known about how female participation differs across countries and regions. This study aimed to assess the percentage of female participants in randomized controlled trials (RCTs) of post-stroke rehabilitation of upper extremity (UE) motor disorders in low-middle-income (LMICs) and high-income countries (HICs) as well as different high-income world regions. METHODS: CINAHL, Embase, PubMed, Scopus, and Web of Science were searched from 1960 to April 1, 2021. Studies were eligible for inclusion if they (1) were RCTs or crossovers published in English; (2) ≥50% of participants were diagnosed with stroke; 3) included adults ≥18 years old; and (4) applied an intervention to the hemiparetic UE as the primary objective of the study. Countries were divided into HICs and LMICs based on their growth national incomes. The HICs were further divided into the three high-income regions of North America, Europe, and Asia and Oceania. Data analysis was performed using SPSS and RStudio v.4.3.1. RESULTS: A total of 1,276 RCTs met inclusion criteria. Of them, 298 RCTs were in LMICs and 978 were in HICs. The percentage of female participants was significantly higher in HICs (39.5%) than LMICs (36.9%). Comparing high-income regions, there was a significant difference in the overall female percentages in favor of RCTs in Europe compared to LMICs but not North America or Asia and Oceania. There was no significant change in the percentage of female participants in all countries and regions over the last 2 decades, with no differences in trends between the groups. CONCLUSIONS: Sufficient female representation in clinical trials is required for the generalizability of results. Despite differences in overall percentage of female participation between countries and regions, females have been underrepresented in both HICs and LMICs with no considerable change over 2 decades.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.020 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".