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Enregistrement W4416947109 · doi:10.2196/78575

Facilitated Peer Discussion for Promoting Better Resident Wellness in Anesthesia Trainees: Qualitative Program Evaluation

2025· article· en· W4416947109 sur OpenAlexaffvenue
Miku Wake, Nicholas West, Jessica Luo, Nancy E. Wang, J. Taylor, Kyra Moura, Theresa Newlove, Zoë Brown

Notice bibliographique

RevueJMIR Perioperative Medicine · 2025
Typearticle
Langueen
DomaineHealth Professions
ThématiqueHealthcare professionals’ stress and burnout
Établissements canadiensProvincial Health Services AuthorityBC Children's HospitalUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésQualitative researchPeer reviewMEDLINEProgram evaluationPeer groupPeer support

Résumé

récupéré en direct d'OpenAlex

Background: Anesthesia residents experience nonroutine clinical events during perioperative patient care, including workplace stressors or adverse incidents that may cause physical and emotional stress. These events can lead to burnout and negative mental health outcomes. Burnout and depression rates are lower when residents have adequate support systems within their workplace. Better resident wellness (BREW) Rounds are a weekly 1-hour peer discussion for anesthesia residents, facilitated by a registered psychologist at our institution. Although shown to improve residents' well-being, a deeper understanding of the benefits of such programs may support their expansion to other residency programs. Objective: This study aimed to explore the benefits and most effective features of BREW Rounds to guide the development of similar programs at other institutions. Methods: Following research ethics board approval, we conducted a qualitative descriptive study based on semistructured interviews with anesthesia residents who had participated in one or more BREW sessions and with the main BREW Rounds facilitator. Topics of discussion included community building, belonging, mentorship, facilitation, discussion of nonclinical aspects, and removal of hierarchy. Interviews were conducted on videoconferencing software by researchers who were not involved in supervising or assessing the trainees. Audio recordings were auto-transcribed, deidentified, verified, and interpreted using thematic content analysis. Further perspectives on BREW Rounds were obtained from staff anesthesiologists through an anonymous online survey. Results: We interviewed 10 residents (6 junior, 3 senior, and 1 transition-to-practice) and 1 facilitator. Emerging themes included (1) access to a safe space free of judgment, allowing participants to be vulnerable about clinical or nonclinical aspects of their training, (2) building a sense of community in a fast-paced and often isolating environment, (3) providing opportunities for mentorship between junior and senior residents in a frequently changing colleague network, (4) the characteristics that create a "BREW culture", such as behavior norms during sessions and staff respect for protected time, (5) the importance of a good facilitator from outside the anesthesia department, especially during smaller sessions, (6) expanding BREW Rounds to other institutions, and (7) areas for improvement for the current program. Sixteen anesthesiology staff survey responses were available for analysis: 12/16 (75%) anesthesiologists supported residents leaving their clinical duties early for BREW Rounds and 12/16 (75%) believed BREW Rounds benefitted residents' well-being. Conclusions: This qualitative study confirms previous findings that BREW Rounds are beneficial to anesthesia training, improve the psychological wellness of residents, and may positively contribute to patient care. Program directors should recognize their potential positive impact on the learning environment, ensure that all staff and trainees understand the need to create protected time for this activity, consider partnering with wellness initiatives at the institutions in which residents are training, and endeavor to identify experienced and unbiased facilitators to moderate sessions.

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)0,008
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,282
Score d'incertitude au seuil0,837

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0080,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,125
Tête enseignante GPT0,560
Écart entre enseignants0,435 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

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

En bref

Citations0
Publié2025
Routes d'admission2
Résumé présentoui

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