Cardiovascular Diseases’ Awareness Among Women in Northern Jordan
Bibliographic record
Abstract
BACKGROUND: Women’s awareness of chronic diseases, including cardiovascular diseases, is the cornerstone in promoting women’s health. Objectives: To examine the relationship of awareness levels about cardiovascular diseases and their related risk factors with demographic information of Jordanian women. METHODS: A cross-sectional study of 18 years and older women. Scores of awareness were computed for each individual and were divided into 4 quartiles. Logistic regression analysis was used to examine the association of demographic information of participants with mean scores of quartiles. ANOVA analysis was used to compare the mean scores of quartiles. RESULTS: A total of 514 women completed the questionnaire, with a mean age of 35.46 (±12.53). Current smokers were 6.2%, and 34.6% had a family history of heart disease. The proportion of diabetes, hypertension, hypercholesterolemia, and overweight/obesity were 15.6%, 19.3%, 14.4%, & 21.6% respectively. The mean score for awareness was 12.87 (+ 3.26). Women who had lower income and who were at younger age were more likely to score low in awareness. CONCLUSION: Women illustrated a fair level of awareness of CVD and its related risk factors. Increasing women awareness of CVD through educational programs, targeted toward women at risk, assists in disease prevention and help to improve treatment plans.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".