Effect of Community Education Program on Stroke Symptoms and Treatment on School and College Students from South India: A Longitudinal Observational Study
Bibliographic record
Abstract
Community awareness regarding stroke signs, risk factors, and actions that help reduce the risk and complications of stroke is poorly addressed, as it is thought to be the best approach to control and prevent stroke. Aim: To establish the awareness of stroke and its management among high school and college students using an educational intervention. A questionnaire was administered to students from five high schools and four colleges with different areas of focus, (arts, science and commerce), types (public, semi-public and private), and economic locations before and after an educational lecture on stroke. The lecture covered the following elements: stroke definition, signs, risk factors, actions, time window for thrombolytic therapy, and types of rehabilitation interventions. This study included 1036 participants, of whom 36.3% were male and 56.4% were high school students, and the mean age was 17.15 ± 1.29 (15-22) years. Before the lecture, 147 participants were unaware of a single sign of stroke, and 124 did not know the risk factors. After the intervention, 439 participants knew four signs of stroke, and 196 knew 12 risk factors. Female students had better knowledge about stroke signs (odds ratio (OR), 3.08; 95% confidence interval (95% CI), 2.15-4.43). Hypertension (52.7%) and weakness (59.85%) were the most known signs and risk factors. The proportion of students who selected traditional medicine as the mode of treatment decreased from 34.75% to 8.59% after the lecture. Other rehabilitation methods (e.g., physical therapy, occupational therapy, speech therapy and counseling) were chosen by more than 80% of the students. The results of the current study showed that the awareness on stroke risk factors and management among the school and college students can be significantly improved with regular educational interventions, and therefore stroke can be prevented to some extent.
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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".