Medical oncology trainees’ perceptions of their education and preparedness for independent practice.
Bibliographic record
Abstract
10536 Background: This original research assesses Canadian Medical Oncology (MO) residents’ perceptions and satisfaction with their education and preparedness for practice prior to initiation of Competency Based Medical Education (CBME). Methods: Digital surveys were sent to MO residents in Canadian training institutions yearly from 2014–2017. Because of lower than expected response rates, invitations were subsequently extended to recent graduates completing training between 2009–2014. Ethics and funding were granted by Queen’s University. Results: A total of 71 surveys were received with representation from 11 training programs. Preparedness for Practice: Current trainees and recent graduates ranked preparedness for practice similarly in all assessment domains except Medical Expert (trainee mean 3.50, graduate mean 4.45, p=0.004; 1=not prepared, 5=well prepared). Means for the combined cohort shown in table. Usefulness of teaching modalities: Participants ranked learning in a clinical setting as most useful (6.53/8, 1=least useful, 8=most useful) and educational sessions by residents (4.24/8) and Journal Club (3.74/8) as least useful. Most participants felt their training was a shared learner-teacher responsibility (56.1%) or was learner-centered (22.5%). Quality of teaching: Participants reported similar levels of satisfaction with teaching across domains except for Manager which scored lowest (3.46/5, 1=poor, 5=excellent). Self-assessment of skills: Participants were most satisfied by their ability to assess their own performance and competence at the end of training (7.16/10, 1=not satisfied, 10= very satisfied). The degree to which their programs set expectations about required knowledge, skills, or attitudes at various points in training (6.63/10) and participants abilities to self-assess these skills during their training (6.64/10) scored lower. Conclusions: Participants reported low satisfaction with their ability to self-assess during their training and their training programs’ ability to communicate expectations. Transition to CBME training may address these issues, and follow-up is required.[Table: see text]
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".