Abstract Number ‐ 31: No Mercy on Stroke Campaign: The Use of Pop Culture Icons to Raise Stroke Awareness
Notice bibliographique
Résumé
Introduction About 24–46% of acute ischemic strokes are due to large vessel occlusions1, however only a small fraction2,3 of thrombectomy eligible patients undergo emergent clot retrieval. Despite advances in thrombolytics and endovascular interventions, many patients are not candidates for emergent therapies due to delay in patient presentation, prehospital delay, triage delay and limited access to care. No Mercy on Stroke (NMOS) campaign aims to raise public stroke awareness by increasing social media footprint. Thereby enabling the general population with tools for earlier symptom detection, seeking rapid medical attention and fighting for legislature to improve prehospital networks. Methods Society of Vascular and Interventional Neurology (SVIN) launched NMOS campaign just prior to World Stroke Day (WSD) on October 25th, 2021 via Twitter. Pop culture icon and martialist Martin Kove launched the campaign as Sensei Kreese from the movie Cobra Kai in a video encouraging viewers to “strike fast and strike hard” when treating stroke. SVIN and Kove urged followers to spread the fight against stroke by sharing karate poses with hashtag #NoMercyOnStroke. Metrics such as social media reach, impact, location and others were extracted via Tweepsmap and Tweetbinder from October 25th, 2021 to August 20th, 2022. Results #NoMercyOnStroke was tweeted 716 times by 211 contributors4 across 19 countries and 77 cities5 for a potential reach of 374,200 people and potential impact of 2,051,908 people4. Tweet breakdown consisted of 126 original tweets and 590 retweets4. Engagements were primarily likes recorded at 2437, and followed by 97 replies and 55 quotes. Activity timeline was highest during week of WSD and accounted for majority exposure, however, there was another small peak in activity one month later. Top 3 countries involved were USA, Canada and India although USA accounted for 90.4% of all activity. Other countries include Mexico, Colombia, Spain, Egypt, Croatia, UK, Saudi Arabia, Kenya, Libya, Vietnam, Italy, Cuba, France, Peru, Chile and Venezuela5. Top associated hash tags were #worldstrokeday, #WSD and #alz0212465. Conclusions Use of pop culture icon as an advocate for stroke awareness greatly increased reach and impression of the NMOS campaign by touching nearly two million followers. Compared to raw data across three social media platforms for a similar campaign by Mission Thrombectomy called #BEFASTChallenge, #NoMercyOnStroke had exponentially more engagement with almost double the original posts and triple the retweets. Still, activity was concentrated around initial launch with minimal tail in the activity timeline. The overall impact of such campaigns on the end‐goal of decreasing the ratio of eligible thrombectomies to number of thrombectomies performed is yet to be uncovered. However, it is clear that larger campaigns involving celebrity influencers and community outreach are imperative to keeping the momentum of raising stroke awareness.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,024 | 0,007 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».