Survey of World Federation of Societies of Anaesthesiologists Fellowship Graduates: Applying a Theory-Driven Framework to Assess Training Outcomes
Notice bibliographique
Résumé
BACKGROUND: For nearly 30 years, the World Federation of Societies of Anaesthesiologists (WFSA) has supported fellowship programs to develop subspecialty anesthesia leaders from low- and middle-income countries (LMICs). To date, no formal program evaluation has assessed the educational effectiveness, accountability, or impact of such interventions. This study is part of a mixed-methods evaluation and aimed to survey graduates from all WFSA-supported fellowship programs about program processes and consequences. METHODS: This survey is the second phase of an exploratory sequential mixed-methods study. All graduates from WFSA-supported fellowships from 1996 to 2024 were eligible for inclusion. Survey content was informed by Guskey's 5-level evaluation framework for evaluating training programs and findings from a prior qualitative phase. The instrument was pretested and piloted with anesthesiologists not eligible for inclusion and distributed electronically in English, Spanish, and French. RESULTS: We received 264 responses from 388 surveys distributed (response rate of 68.0%). Most respondents completed their fellowship in the past 10 years; fewer graduates were reported between 2020 and 2022 due to the coronavirus disease 2019 (COVID-19) pandemic. Over 90% of respondents reported consistent access to clinical learning, teaching, and mentorship, peer support, and financial support during their fellowships. Fewer than 5% expressed a lack of confidence in their ability to deliver subspecialty care upon returning home. However, nearly 25% reported being unable to provide clinical care to the same standard as during their fellowship, and almost one-third reported insufficient access to essential equipment required for their subspecialty practice. CONCLUSIONS: WFSA-supported fellowship programs were viewed favorably by graduates across all 5 levels of Guskey's framework. The most frequently cited challenge was the transfer of skills and knowledge to home institutions, often due to contextual disparities between well-resourced training centers and under-resourced home environments. These barriers were most pronounced among fellows returning to the most resource-constrained settings. Addressing these barriers-particularly for fellows from the most under-resourced settings should be a priority for further program investment. Despite these limitations, most participants reported contributing to improved clinical service delivery-often beyond their individual practice-supporting the program's goal of developing subspeciality leadership in anesthesiology.
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 | 0,026 | 0,047 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».