Radiation oncology directors of training survey 2016: Perspectives and challenges
Bibliographic record
Abstract
INTRODUCTION: This paper reports the key findings of the first survey of Australian and New Zealand Radiation Oncology Directors of Training (DoTs) dealing with their perspectives, experiences and challenges. METHODS: The survey was conducted in September 2016 using a 34-question instrument. It was emailed to all radiation oncology DoTs listed on the Royal Australian and New Zealand College of Radiologists (RANZCR) database. The questions related to demographics, protected time, weekly activities, support, the value of curriculum assessments, challenges and suggested improvements. Respondents were assured that their responses were anonymous. RESULTS: The response rate was 59.6% (31/52). The median age of respondents was in the 41 to 45 age bracket, but nearly one quarter were over 45 years of age. The median time respondents had been in the role was three to five years (range <0.5 to >10) with the median number of trainees supervised being four (range 1-8). Thirty-five percent had a co DoT. DoTs spent a median of three hours per week on the role (range <1 to >8) with most respondents (67.7%) requiring time during and out of work performing the role, but ten percent claimed it was done out of hours only. Nearly all DoTs were aware they should have protected time, but only just half received it. The educational aspects of training dominated weekly activities, but rostering, specific trainee issues and administration were also featured. Time issues were the greatest challenge for respondents with clinical assignments the most challenging assessment. However, more emphasis on contouring and planning was thought to be required. All DoTs found the dedicated DoT workshops useful, but felt future discussions on trainees in difficulty could be emphasized. The vast majority felt supported by their training site and the College. All respondents believed in the role with most having an interest in educational activities. The majority of respondents (85%) intended to continue in the role for the next 1 to 2 years, but this dropped to 45% when asked about continuing for 5 years. CONCLUSIONS: This survey of predominantly experienced DoTs, indicated that the role was deemed to be of value in delivering optimal training. The most significant challenges faced by DoTs were finding sufficient time to deal with the responsibilities of the role and dealing with underperforming trainees. Feedback on the currently employed work based assessments will be considered as FRO transitions into programmatic assessment. Furthermore, a desire for training in how to deal with trainees in difficulty, underperforming or unsuitable trainees is noted. Future work is planned following refinements of the survey instrument; and, will also explore stress and burnout in the DoT cohort.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".