Bridging Learning in Medicine and Citizenship During the COVID-19 Pandemic: A Telehealth-Based Case Study
Notice bibliographique
Résumé
BACKGROUND: COVID-19 presented great challenges for not only those in the field of health care but also those undergoing medical training. The burden on health care services worldwide has limited the educational opportunities available for medical students due to social distancing requirements. OBJECTIVE: In this paper, we describe a strategy that combines telehealth and medical training to mitigate the adverse effects of the COVID-19 pandemic. METHODS: A toll-free telescreening service, Telecoronavirus, began operations in March 2020. This service was operated remotely by supervised medical students and was offered across all 417 municipalities (14.8 million inhabitants) in the Brazilian state of Bahia. Students recorded clinical and sociodemographic data by using a web-based application that was simultaneously accessed by medical volunteers for supervision purposes, as well as by state health authorities who conducted epidemiological surveillance and health management efforts. In parallel, students received up-to-date scientific information about COVID-19 via short educational videos prepared by professors. A continuously updated triage algorithm was conceived to provide consistent service. RESULTS: The program operated for approximately 4 months, engaging 1396 medical students and 133 physicians. In total, 111,965 individuals residing in 343 municipalities used this service. Almost 70,000 individuals were advised to stay at home, and they received guidance to avoid disease transmission, potentially contributing to localized reductions in the spread of COVID-19. Additionally, the program promoted citizenship education for medical students, who were engaged in a real-life opportunity to fight the pandemic within their own communities. The objectives of the education, organization, and assistance domains of the Telecoronavirus program were successfully achieved according to the results of a web-based post-project survey that assessed physicians' and students' perceptions. CONCLUSIONS: In a prolonged pandemic scenario, a combination of remote tools and medical supervision via telehealth services may constitute a useful strategy for maintaining social distancing measures while preserving some practical aspects of medical education. A low-cost tool such as the Telecoronavirus program could be especially valuable in resource-limited health care scenarios, in addition to offering support for epidemiological surveillance actions.
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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 | 0,003 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,010 | 0,004 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,005 |
| Intégrité de la recherche | 0,006 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».