Examining Stroke Symptom Messages Implemented Globally: A Need for Contextually Relevant Stroke Symptom Messaging
Bibliographic record
Abstract
BACKGROUND: Stroke is a global health concern. A timely response to a stroke can help reduce morbidity and mortality. However, barriers to timely response include poor recognition of stroke symptoms. Stroke symptom messages are designed to increase stroke recognition and encourage individuals to seek urgent medical assistance. The Face, Arm, Speech, Time (FAST) and Balance, Eyes, Face, Arm, Speech, Time (BE FAST) are commonly used stroke symptom messages shown to improve stroke symptom recognition and response. However, cultural factors and language differences may limit the effectiveness of stroke symptom messages and their acceptability in different countries and contexts. There has not been a comprehensive examination of the stroke symptom messages used worldwide and how these messages have been adapted in various settings. AIMS: We explored what stroke response messages are being used globally, and the contextual factors that influence the adoption of a stroke response mnemonic in different settings. METHODS: A 14-item survey was disseminated by the World Stroke Organization to its networks. The survey contained open- and closed-ended questions and allowed uploading relevant stroke symptom campaign materials. The survey was analyzed using descriptive statistics and a content analysis. RESULTS: All except one survey respondent used a stroke symptom message. Fifteen respondents (27%) reported they did not translate their stroke awareness messaging. Of these 15 respondents, they used the English versions of FAST (n = 8), BE FAST (n = 4), and both FAST and BE FAST (n = 3). Forty respondents (71%) reported that they/their organization used an acronym to raise public awareness of the signs/symptoms of stroke that was different from FAST or BE FAST (English), many of which were direct or indirect translations or influenced by FAST and BE FAST. Survey responses shared insights and recommendations related to the content, tailoring and dissemination of stroke symptom messages. CONCLUSIONS: Study findings highlight the global use of stroke symptom messages and their contextual adaptations to fit diverse settings and contexts. The challenges in applying universal or commonly used stroke symptom messages to different contexts were highlighted. CLINICAL RELEVANCE: Nurses could have a key role in raising awareness of stroke symptoms and the development of locally adapted stroke symptom messages.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.038 | 0.091 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".