An International Expert Delphi Consensus to Develop Dedicated Geriatric Radiation Oncology Curriculum Learning Outcomes
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.170 | 0.170 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.012 | 0.006 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".