Effect of the Preparatory School FAST Stroke Educational Program
Bibliographic record
Abstract
ABSTRACT: BACKGROUND: The aim of this study was to assess the effectiveness of FAST stroke educational program among all preparatory school students in the state of Qatar. METHODS: The pretest-posttest experimental research design was used to evaluate the effectiveness of the FAST educational program in Qatar. A 30-minute audiovisual presentation was given to improve knowledge of stroke. We included grade 7 to 9 students during the academic year 2018-2019. The FAST program consisted of a pretest, an educational intervention, and immediate and long-term posttests at 2 months. RESULTS: A sample of 1244 students completed presurvey and immediate postsurvey, with an average age of 13.5 (1.12) years (range, 11-18 years) and 655 (53%) females. Students had significantly ( P < .01) greater knowledge of stroke signs, symptoms, and risk factors at intermediate posttest (5.9 [2.6] and 6.2 [2.4]) and at 2 months posttest (5.6 [2.8] and 5.6 [2.7]) compared with pretest (4.8 [2.6] and 4.9 [2.6], respectively). Students also had a higher self-efficacy to seek assistance, which was sustained from pretest to long-term posttest. CONCLUSION: The FAST program improved stroke knowledge that was retained at 2 months.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".