A Comparison of Stroke Risk Factors Between Men and Women with Disabilities
Bibliographic record
Abstract
There are many adults with disabilities currently in the United States, yet little is known about how gender differences affect stroke risk factors in this population. This article presents a descriptive study that was designed to determine whether males and females living with disabilities differ in self-reported rates of stroke risk factors. Data were collected at conferences and meetings targeted for people living with disabilities. There were 146 participants; 54% were female; and the mean age was 58 years. The primary instrument was the Stroke Risk Screening tool. Stroke risk factors that differed significantly by gender include the incidence of hypertension (48% of men versus 32% of women), current smoking (30% men versus 4% women), history of heart disease (13% men versus 1% women), daily consumption of alcohol (10% men versus 1% women), and use of illicit drugs (10% men versus 0% women). Rehabilitation nurses should focus on earlier assessment of stroke risk factors and appropriate interventions, especially with men living with disabilities.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".