Communication and Contextual Factors in Robotic-Assisted Surgical Teams: Protocol for Developing a Taxonomy
Notice bibliographique
Résumé
BACKGROUND: Robotic-assisted surgery (RAS) has been rapidly integrated into surgical practice in the past few decades. The setup in the operating theater for RAS differs from that for open or laparoscopic surgery such that the operating surgeon sits at a console separate from the rest of the surgical team and the patient. Communication and team dynamics are altered due to this physical separation and visual barriers imposed by the robotic equipment. However, the factors that might comprise effective communication among members of RAS teams and the contextual factors that facilitate or inhibit effective communication in RAS remain unknown. OBJECTIVE: We aim to develop a taxonomy of communication behaviors and contextual factors that influence communication in RAS teams. We also aim to examine the patterns of communication behaviors based on gender. METHODS: We will first perform a scoping review on communication in RAS to develop a preliminary taxonomy of communication based on the existing literature. We will then conduct semistructured interviews with RAS team members, including the surgeon, assisting surgeon or trainee, bedside or first assistant, nurses, and anesthetists. Participants will represent different disciplines, including urology, general surgery, and gynecology, and have a range of experiences in RAS. We will use a reflexive thematic analysis to analyze the data and further refine the taxonomy. We will also observe live robotic surgeries at Royal College of Surgeons in Ireland (RCSI)-affiliated hospitals. We will observe varying lengths and conditions of RAS procedures to a capture a wide range of communication behaviors and contextual factors to help finalize the taxonomy. Although we anticipate conducting 30 interviews and 30 observations, we will collect data until we achieve data sufficiency. We will conduct data collection in parallel with data analysis such that if we identify a new behavior in an interview, we will follow up with questions related to that behavior in additional interviews and/or observations. RESULTS: The taxonomy from this project will include a list of actionable communication behaviors, contextual factors, their descriptions, and examples. As of May 2024, this project has been approved by the RCSI Research and Ethics Committee. Data collection started in June 2024 and will continue throughout the year. We plan to publish the findings as meaningful results emerge in our data analysis in 2024 and 2025. CONCLUSIONS: The results from this project will be used to observe and train surgical teams in a simulated environment to effectively communicate with each other and prevent communication breakdowns. The developed taxonomy will also add to the knowledge base on the role of gender in communication in RAS and produce recommendations that can be incorporated into training. Overall, this project will contribute to the improvement of communication skills of surgical teams and the quality and safety of patient care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/54910.
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 | 0,070 | 0,079 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,003 |
| Méta-épidémiologie (sens large) | 0,005 | 0,007 |
| Bibliométrie | 0,010 | 0,009 |
| Études des sciences et des technologies | 0,008 | 0,005 |
| Communication savante | 0,007 | 0,007 |
| Science ouverte | 0,005 | 0,009 |
| Intégrité de la recherche | 0,005 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,043 | 0,008 |
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 ».