An International Expert Delphi Consensus to Develop Dedicated Geriatric Radiation Oncology Curriculum Learning Outcomes
Notice bibliographique
Résumé
PurposeThe management of older adults with cancer is rapidly becoming a significant challenge in radiation oncology (RO) practice. The education of future radiation oncologists in geriatric oncology is fundamental to ensuring that older adults receive high-quality care. Currently RO trainees receive little training and education in geriatric oncology. The objective of this study was to define core geriatric RO curriculum learning outcomes relevant to RO trainees worldwide.Methods and MaterialsA 2-stage modified Delphi consensus was conducted. Stage 1 involved the formation of an expert reference panel (ERP) of multiprofessional experts in geriatric oncology and/or RO and the compilation of a potential geriatric RO learning outcomes set. Stage 2 involved 3 iterative rounds: round 1 and round 2 (both online surveys), and an intervening ERP round. These aimed at identifying and refining ideal geriatric RO learning outcomes. Invited participants for round 1 and 2 included oncology health care professionals with expertise across RO, geriatric oncology, and/or education and consumers. Predefined Delphi consensus definitions were applied to the results of rounds 1 and 2.ResultsAn ERP of 11 experts in geriatric oncology and/or RO was formed. Seventy potential knowledge- and skill-based learning outcomes were identified. In round 1, 103 of 179 invited eligible Delphi participants completed the survey (58% response rate). The ERP round was conducted, resulting in the exclusion of 28 learning outcomes. In round 2, 54 of 103 completed the survey (52% response rate). This identified a final total of 33 geriatric RO learning outcomes.ConclusionsThe geriatric RO learning outcomes described in this study form an international consensus that can inform RO training bodies worldwide. This represents the first fundamental step in developing a global educational framework aimed at improving RO trainee knowledge and skills in geriatric oncology. The management of older adults with cancer is rapidly becoming a significant challenge in radiation oncology (RO) practice. The education of future radiation oncologists in geriatric oncology is fundamental to ensuring that older adults receive high-quality care. Currently RO trainees receive little training and education in geriatric oncology. The objective of this study was to define core geriatric RO curriculum learning outcomes relevant to RO trainees worldwide. A 2-stage modified Delphi consensus was conducted. Stage 1 involved the formation of an expert reference panel (ERP) of multiprofessional experts in geriatric oncology and/or RO and the compilation of a potential geriatric RO learning outcomes set. Stage 2 involved 3 iterative rounds: round 1 and round 2 (both online surveys), and an intervening ERP round. These aimed at identifying and refining ideal geriatric RO learning outcomes. Invited participants for round 1 and 2 included oncology health care professionals with expertise across RO, geriatric oncology, and/or education and consumers. Predefined Delphi consensus definitions were applied to the results of rounds 1 and 2. An ERP of 11 experts in geriatric oncology and/or RO was formed. Seventy potential knowledge- and skill-based learning outcomes were identified. In round 1, 103 of 179 invited eligible Delphi participants completed the survey (58% response rate). The ERP round was conducted, resulting in the exclusion of 28 learning outcomes. In round 2, 54 of 103 completed the survey (52% response rate). This identified a final total of 33 geriatric RO learning outcomes. The geriatric RO learning outcomes described in this study form an international consensus that can inform RO training bodies worldwide. This represents the first fundamental step in developing a global educational framework aimed at improving RO trainee knowledge and skills in geriatric oncology.
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 | 0,170 | 0,170 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,004 |
| Bibliométrie | 0,012 | 0,006 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,003 | 0,014 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,003 |
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 ».