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Enregistrement W3169192404 · doi:10.1093/neuros/nyab217

Letter: A Scoping Review of Burnout in Neurosurgery

2021· review· en· W3169192404 sur OpenAlexaboutno aff
Grazia Menna, Ismail Zaed, Giuseppe Maria Della Pepa

Notice bibliographique

RevueNeurosurgery · 2021
Typereview
Langueen
DomaineMedicine
ThématiqueSpine and Intervertebral Disc Pathology
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBurnoutContext (archaeology)SolidarityNeurosurgeryPsychologyPerspective (graphical)MedicinePolitical sciencePsychiatryHistoryClinical psychologyLawComputer sciencePolitics

Résumé

récupéré en direct d'OpenAlex

To the Editor: We read with great interest the paper by Mackel et al,1 “A Scoping Review of Burnout in Neurosurgery,” in which the authors published a comprehensive view of burnout among US neurosurgeons. Their analysis can be regarded as timely because all the studies included have been published in the last 10 yr, relevant both for the economic burden and for the compromised quality of care, and forthright given that it identifies in wellness programs emphasizing solidarity a way to counteract the problem.2 The strengths of their research lie in having analyzed studies conducted on both residents and attendings and having compared burnout rate in neurosurgery vs other US specialties. The topic is of great interest, and the possible implications involve different realities and neurosurgical contexts transversally. We believe it is important burnout in neurosurgery is not an absolute and fixed entity; on the contrary, it is strongly influenced by the broader cultural context in which it is embedded. Therefore, when looking from a global perspective, analyzing the way the phenomenon is addressed and its relevance would be of interest. This holds true for extra US realities especially. Focusing on Europe first, a difference to outline relates to the perception of burnout. The latter is much lower, as shown by the different rate of publications on the topic: Table 6 reported a total of 4 surveys on the topic conducted in Europe, of whom 2 were French. This means many countries, including Italy, have never produced literature on the topic. In contrast, North American studies are much more numerous and “ubiquitous.” Notwithstanding with this, intercontinental comparison revealed that the United States and Canada had the lowest proportion of neurosurgery trainees at risk for burnout (11.2%), whereas Europe had the highest (26.9%).3 A first, important consideration can be made: It seems a lower burnout state recognition, and, therefore, less incentive for initiatives to prevent it translates into a doubling of the risk. Further research is needed. Moving on to Asian reality, burnout is even less investigated than in Europe (3 studies). In addition, a Chinese study published by Yu et al1,3 found that academic neurosurgeons have a significantly lower rate of burnout compared to nonacademic neurosurgeons (P < .01) even if they must work a long hour; this could be explained by the high sense of personal accomplishment, and possibly by the high salaries (P < .01).4,5 Hence a second, important consideration: How much cultural diversity weighs on burnout risk? Heterogeneity could reveal itself as a potential issue in terms of populations included, scales used to measure burnout, and hypothetical ways out. Therefore, the future challenge will be to disentangle cultural and noncultural risk factors to make effective comparisons between different realities. In thanking the author for providing such an interesting food for thought, we wish future studies on burnout in neurosurgery would shade light in contexts yet insufficiently explored worldwide and inclusively analyze and compare relevant differences in the wider framework of sociocultural diversities. Funding This study did not receive any funding or financial support. Disclosures The authors have no personal, financial, or institutional interest in any of the drugs, materials, or devices described in this article.

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)0,001
score de la tête « metaresearch » (Gemma)0,002
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 enseignants0,332
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0060,002
Bibliométrie0,0010,001
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)0,0010,000

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 Opus0,090
Tête enseignante GPT0,388
Écart entre enseignants0,298 · 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

Citations6
Publié2021
Routes d'admission1
Résumé présentoui

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