Teledentistry Implementation During the COVID-19 Pandemic: Scoping Review
Notice bibliographique
Résumé
BACKGROUND: COVID-19 spreads via aerosol droplets. The dental profession is at high risk of contracting the virus since their work includes treatment procedures that produce aerosols. Teledentistry offers an opportunity to mitigate the risk to dental personnel by allowing dentists to provide care without direct patient contact. OBJECTIVE: The purpose of this scoping review was to examine the implementation, challenges, strategies, and innovations related to teledentistry during the COVID-19 pandemic lockdown. METHODS: This scoping review evaluated teledentistry use during the pandemic by searching for articles in PubMed and Google Scholar using the search terms teledentistry, tele-dentistry, covid-19, coronavirus, telehealth, telemedicine, and dentistry. Inclusion criteria consisted of articles published in English from March 1, 2020, to April 1, 2022, that were relevant to dentistry and its specialties, and that included some discussion of teledentistry and COVID-19. Specifically, the review sought to explore teledentistry implementation, challenges, strategies to overcome challenges, and innovative ideas that emerged during the pandemic. It followed the 2020 Preferred Reporting Items for Systematic reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR). This approach is organized into 5 distinct steps: formulating a defined question, using the question to develop inclusion criteria to identify relevant studies, an approach to appraise the studies, summarizing the evidence using an explicit methodology, and interpreting the findings of the review. RESULTS: A total of 32 articles was included in this scoping review and summarized by article type, methodology and population, and key points about the aims; 9 articles were narrative review articles, 10 were opinion pieces, 4 were descriptive studies, 3 were surveys, 2 were integrative literature reviews, and there was 1 each of the following: observational study, systematic review, case report, and practice brief. Teledentistry was used both synchronously and asynchronously for virtual consultations, often employing commercial applications such as WhatsApp, Skype, and Zoom. Dental professionals most commonly used teledentistry for triage, to reduce in-person visits, and for scheduling and providing consultations remotely. Identified challenges included patient and clinician acceptance of teledentistry, having adequate infrastructure, reimbursement, and security concerns. Strategies to address these concerns included clinician and patient training and utilizing Health Insurance Portability and Accountability Act-compliant applications. Benefits from teledentistry included providing care for patients during the pandemic and extending care to areas lacking access to dental care. CONCLUSIONS: Pandemic lockdowns led to new teledentistry implementations, most commonly for triage but also for follow-up and nonprocedural care. Teledentistry reduced in-person visits and improved access to remote areas. Challenges such as technology infrastructure, provider skill level, billing issues, and privacy concerns remain.
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 | 0,022 | 0,103 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,007 |
| Bibliométrie | 0,015 | 0,015 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,004 | 0,002 |
| 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 ».