Oncology education for family medicine residents: a national needs assessment survey
Bibliographic record
Abstract
BACKGROUND: This study aimed to determine the current state of oncology education in Canadian family medicine postgraduate medical education programs (FM PGME) and examine opinions regarding optimal oncology education in these programs. METHODS: A survey was designed to evaluate ideal and current oncology teaching, educational topics, objectives, and competencies in FM PGMEs. The survey was sent to Canadian family medicine (FM) residents and program directors (PDs). RESULTS: In total, 150 residents and 17 PDs affiliated with 16 of 17 Canadian medical schools completed the survey. The majority indicated their programs do not have a mandatory clinical rotation in oncology (79% residents, 88% PDs). Low rates of residents (7%) and PDs (13%) reported FM residents being adequately prepared for their role in caring for cancer patients (p = 0.03). Residents and PDs believed the most optimal method of teaching oncology is through clinical exposure (65% residents, 80% PDs). Residents and PDs agreed the most important topics to learn (rated ≥4.7 on 5-point Likert scale) were: performing pap smears, cancer screening/prevention, breaking bad news, and approach to patient with increased cancer risk. According to residents, other important topics such as appropriate cancer patient referrals, managing cancer complications and post-treatment surveillance were only taught at frequencies of 52, 40 and 36%, respectively. CONCLUSIONS: Current FM PGME oncology education is suboptimal, although the degree differs in the opinion of residents and PDs. This study identified topics and methods of education which could be focussed upon to improve FM oncology education.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".