The prevalence and solutions to burnout amongst surgical trainees
Notice bibliographique
Résumé
Background: Burnout is a syndrome of emotional exhaustion, reduced sense of personal accomplishment and loss of sense of self. Healthcare workers in the UK are known to suffer high psychological distress and burnout. Increasing attrition rates among surgical trainees have also been noted, particularly among female trainees. However, there are limited data on the factors contributing to burnout potentially leading to trainee attrition. Interventions to combat burnout and improve trainee well-being are still in their infancy. This review reports burnout prevalence and methods implemented to reduce burnout and improve surgical trainee well-being. Objective: To report the prevalence and factors contributing to burnout and suggest evidence-based methods that reduce burnout and improve well-being within this cohort. Methods: A literature search was conducted across five databases, identifying papers on burnout prevalence among surgical trainees and reported gender. Papers outlining interventions to reduce burnout were also included. Papers were screened against our inclusion and exclusion criteria. Quality was assessed using the modified Newcastle–Ottawa Scale and data were extracted and presented in this review. Results: Following screening, 22 of 456 identified papers were included in the review; 11 papers were examined for burnout prevalence and the remaining 11 papers focused on interventions. Trainees reporting discrimination, abuse or harassment at least once a month were significantly more likely to experience burnout regardless of gender. Conflicting results were found on burnout prevalence and training level. Interventions identified included mindfulness courses, mentorship programmes, Enhanced Stress Resilience Training (ESRT) and Self-Compassion for Healthcare Communities (SCHC) training. Dedicated faculty and wellness opportunities produced lower burnout rates (p=0.02). Two months of mindfulness training via the Headspace application also reduced burnout scores (p=0.01). ESRT reduced overall burnout by 38.9%. Similarly, increased self-compassion significantly predicted burnout reduction (p=0.018). No significant improvement was identified in residents at unionised programmes. Conclusions: While there was no significant difference in burnout between genders, female and junior trainees are more at risk of exposure to negative behaviours in the workplace. This can directly contribute to higher levels of burnout. Interventions like mentorship and mindfulness and resilience training may reduce burnout and improve surgical trainee well-being. However, more needs to be done to educate faculty and raise awareness amongst surgical peers.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 tête enseignante, 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 ».