The impact of social media for shoulder surgeons: a prevalence and correlation study with online and academic presence
Notice bibliographique
Résumé
Background: Social media use has grown exponentially in the past decade and has become a powerful tool for physicians. A strong online presence can play a vital role for surgeons in patient recruitment and education and in promoting new literature. This study examines the influence of social media use on patient-reported online ratings and academic productivity among shoulder and elbow and sports medicine fellowship-trained orthopedic shoulder surgeons. Methods: The American Shoulder and Elbow Surgeons directory was queried for all active members who completed either a shoulder and elbow or sports medicine fellowship in the United States. Each name was searched on Twitter/X, Instagram, LinkedIn, ResearchGate, Facebook, TikTok, and YouTube for professional accounts, and the number of followers was recorded for each. The presence of a practice group or personal website was also recorded. Average ratings, number of reviews, and number of comments were collected from Healthgrades, Google Reviews, and Vitals. H-index was searched on Scopus. A summated social media presence score was calculated to identify the top 15% of social media users in each cohort. Results: 134 shoulder and elbow and 97 sports medicine fellowship-trained orthopedic shoulder surgeons were included in this review. The top 15% of social media users consisted of 35 shoulder surgeons: 16 with a shoulder and elbow fellowship and 19 with a sports medicine fellowship. The top 15% of users completed fewer years of practice on average since fellowship compared to the bottom 85%. On Healthgrades, the top 15% possessed higher mean ratings, number of ratings, and number of comments compared to the rest of the cohort. Active Instagram users had higher mean ratings on Google Reviews compared to those without an active profile. Across all social media platforms, those with profiles were found to have either similar or higher patient engagement on Healthgrades, Google Reviews, and Vitals. Among sports medicine surgeons, active Twitter/X and Instagram usage was also associated with a higher h-index compared to nonusers. Discussion: Social media involvement and overall online presence is positively associated with surgeon ratings and number of reviews and comments on physician rating websites, including Healthgrades, Google Reviews, and Vitals. Increased activity on Twitter/X and Instagram is also associated with an increased h-index. Social media involvement using web-based marketing tools continues to emerge in shoulder surgery by offering surgeons an outlet to reach patients and promote literature.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».