Video-based educational intervention associated with improved stroke literacy, self-efficacy, and patient satisfaction
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Interventions are needed to improve stroke literacy among recent stroke survivors. We developed an educational video for patients hospitalized with acute ischemic stroke (AIS) and intracerebral hemorrhage (ICH). METHODS: A 5-minute stroke education video was shown to our AIS and ICH patients admitted from March to June 2015. Demographics and a 5-minute protocol Montreal Cognitive Assessment were also collected. Questions related to stroke knowledge, self-efficacy, and patient satisfaction were answered before, immediately after, and 30 days after the video. RESULTS: Among 250 screened, 102 patients consented, and 93 completed the video intervention. There was a significant difference between pre-video median knowledge score of 6 (IQR 4-7) and the post-video score of 7 (IQR 6-8; p<0.001) and between pre-video and the 30 day score of 7 (IQR 5-8; p = 0.04). There was a significant difference between the proportion of patients who were very certain in recognizing symptoms of a stroke pre- and post-video, which was maintained at 30-days (35.5% vs. 53.5%, p = 0.01; 35.5% vs. 54.4%, p = 0.02). The proportion who were "very satisfied" with their education post-video (74.2%) was significantly higher than pre-video (49.5%, p<0.01), and this was maintained at 30 days (75.4%, p<0.01). There was no association between MoCA scores and stroke knowledge acquisition or retention. There was no association between stroke knowledge acquisition and rates of home blood pressure monitoring or primary care provider follow-up. CONCLUSIONS: An educational video was associated with improved stroke knowledge, self-efficacy in recognizing stroke symptoms, and satisfaction with education in hospitalized stroke patients, which was maintained at 30 days after discharge.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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".