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Enregistrement W2793892569 · doi:10.2196/mhealth.9409

Using Google Glass in Surgical Settings: Systematic Review

2018· review· en· W2793892569 sur OpenAlexvenueno aff
Nancy Wei, B. Dougherty, Aundria Myers, Sherif M. Badawy

Notice bibliographique

RevueJMIR mhealth and uhealth · 2018
Typereview
Langueen
DomaineMedicine
ThématiqueSurgical site infection prevention
Établissements canadiensnon disponible
Organismes subventionnairesFeinberg School of MedicineAgency for Healthcare Research and QualityNorthwestern University
Mots-clésMedicineComputer science

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: In recent years, wearable devices have become increasingly attractive and the health care industry has been especially drawn to Google Glass because of its ability to serve as a head-mounted wearable device. The use of Google Glass in surgical settings is of particular interest due to the hands-free device potential to streamline workflow and maintain sterile conditions in an operating room environment. OBJECTIVE: The aim is to conduct a systematic evaluation of the literature on the feasibility and acceptability of using Google Glass in surgical settings and to assess the potential benefits and limitations of its application. METHODS: The literature was searched for articles published between January 2013 and May 2017. The search included the following databases: PubMed MEDLINE, Embase, Cumulative Index to Nursing and Allied Health Literature, PsycINFO (EBSCO), and IEEE Xplore. Two reviewers independently screened titles and abstracts and assessed full-text articles. Original research articles that evaluated the feasibility, usability, or acceptability of using Google Glass in surgical settings were included. This review was completed following the Preferred Reporting Results of Systematic Reviews and Meta-Analyses guidelines. RESULTS: Of the 520 records obtained, 31 met all predefined criteria and were included in this review. Google Glass was used in various surgical specialties. Most studies were in the United States (23/31, 74%) and all were conducted in hospital settings: 29 in adult hospitals (29/31, 94%) and two in children's hospitals (2/31, 7%). Sample sizes of participants who wore Google Glass ranged from 1 to 40. Of the 31 studies, 25 (81%) were conducted under real-time conditions or actual clinical care settings, whereas the other six (19%) were conducted under simulated environment. Twenty-six studies were pilot or feasibility studies (84%), three were case studies (10%), and two were randomized controlled trials (6%). The majority of studies examined the potential use of Google Glass as an intraoperative intervention (27/31, 87%), whereas others observed its potential use in preoperative (4/31, 13%) and postoperative settings (5/31, 16%). Google Glass was utilized as a videography and photography device (21/31, 68%), a vital sign monitor (6/31, 19%), a surgical navigation display (5/31, 16%), and as a videoconferencing tool to communicate with remote surgeons intraoperatively (5/31, 16%). Most studies reported moderate or high acceptability of using Google Glass in surgical settings. The main reported limitations of using Google Glass utilization were short battery life (8/31, 26%) and difficulty with hands-free features (5/31, 16%). CONCLUSIONS: There are promising feasibility and usability data of using Google Glass in surgical settings with particular benefits for surgical education and training. Despite existing technical limitations, Google Glass was generally well received and several studies in surgical settings acknowledged its potential for training, consultation, patient monitoring, and audiovisual recording.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,413
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0050,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,147
Tête enseignante GPT0,487
Écart entre enseignants0,339 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeRevue systématique
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations106
Publié2018
Routes d'admission1
Résumé présentoui

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