Health Researchers’ Use of Social Media: Scoping Review
Notice bibliographique
Résumé
BACKGROUND: Health researchers are increasingly using social media in a professional capacity, and the applications of social media for health researchers are vast. However, there is currently no published evidence synthesis of the ways in which health researchers use social media professionally, and uncertainty remains as to how best to harness its potential. OBJECTIVE: This scoping review aimed to explore how social media is used by health researchers professionally, as reported in the literature. METHODS: The scoping review methodology guided by Arksey and O'Malley and Levac et al was used. Comprehensive searches based on the concepts of health research and social media were conducted in MEDLINE, EMBASE, CINAHL, PsycINFO, ERIC, and Web of Science databases, with no limitations applied. Articles were screened at the title and abstract level and at full text by two reviewers. One reviewer extracted data that were analyzed descriptively to map the available evidence. RESULTS: A total of 8359 articles were screened at the title and abstract level, of which 719 were also assessed at full text for eligibility. The 414 articles identified for inclusion were published in 278 different journals. Studies originated from 31 different countries, with the most prevalent being the United States (52.7% [218/414]). The health discipline of the first authors varied, with medicine (33.3% [138/414]) being the most common. A third of the articles covered health generally, with 61 health-specific topics. Papers used a range of social media platforms (mean 1.33 [SD 0.7]). A quarter of the articles screened reported on social media use for participant recruitment (25.1% [104/414]), followed by practical ways to use social media (15.5% [64/414]), and use of social media for content analysis research (13.3% [55/414]). Articles were categorized as celebratory (ie, opportunities for engagement, 72.2% [299/414]), contingent (ie, opportunities and possible limitations, 22.7% [94/414]) and concerned (ie, potentially harmful, 5.1% [21/414]). CONCLUSIONS: Health researchers are increasingly publishing on their use of social media for a range of professional purposes. Although most of the sentiment around the use of social media in health research was celebratory, the uses of social media varied widely. Future research is needed to support health researchers to optimize their social media use.
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 | 0,054 | 0,138 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».