Childhood cancer survivorship educational resources in North American pediatric hematology/oncology fellowship training programs: A survey study
Bibliographic record
Abstract
BACKGROUND: Childhood cancer survivors require life-long care by clinicians with an understanding of the specific risks arising from the prior cancer and its therapy. We surveyed North American pediatric hematology/oncology training programs to evaluate their resources and capacity for educating medical trainees about survivorship. PROCEDURE: An Internet survey was sent to training program directors and long-term follow-up clinic (LTFU) directors at the 56 US and Canadian centers with pediatric hematology/oncology fellowship programs. Perceptions regarding barriers to and optimal methods of delivering survivorship education were compared among training program and LTFU clinic directors. RESULTS: Responses were received from 45/56 institutions of which 37/45 (82%) programs require that pediatric hematology/oncology fellows complete a mandatory rotation focused on survivorship. The rotation is 4 weeks or less in 21 programs. Most (36/45; 80%) offer didactic lectures on survivorship as part of their training curriculum, and these are considered mandatory for pediatric hematology/oncology fellows at 26/36 (72.2%). Only 10 programs (22%) provide training to medical specialty trainees other than pediatric hematology/oncology fellows. Respondents identified lack of time for trainees to spend learning about late effects as the most significant barrier to providing survivorship teaching. LTFU clinic directors were more likely than training program directors to identify lack of interest in survivorship among trainees and survivorship not being a formal or expected part of the fellowship training program as barriers. CONCLUSIONS: The results of this survey highlight the need to establish standard training requirements to promote the achievement of basic survivorship competencies by pediatric hematology/oncology fellows.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".