Virtual Mentoring for Medical Physicists: Results of a Global Online Survey
Why this work is in the frame
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Bibliographic record
Abstract
Purpose: Medical physics professional development is limited in parts of the globe and can be aided by virtual mentoring. A global online perception survey was conducted to elucidate the characteristics of the preferred virtual mentoring program. Methods: Informed by a literature review and pilot testing by focus groups, the survey was electronically disseminated to multiple medical physics organizations, list servers, and professional contacts. It addressed issues including factors and barriers influencing successful mentoring; mentors'/mentees' matching preferences; frequency and length of meetings; importance of defining expectations; formal agreement; and assessment of the mentoring process. Descriptive statistics were used to characterize responses including comparisons by country income level. Results: The 396 responders (68% male and 32% female) were from 76 countries with 66% from high-income countries (HICs) and 34% from low- and middle-income countries (L&MICs). Data were provided on experience level as mentors (43% "little [occasional]", 38% "lot [regular or ongoing]") and mentees (53% "little [occasional]", and 23% "lot [regular or ongoing]"), and interest in participating in mentorship program (83% as mentor, mentee, or both). L&MIC responders were generally younger with less work experience (55% <10 years versus 28% for HIC responders). Differences between L&MIC and HIC responses occurred when considering the perceived limitations and barriers to virtual mentoring. Preferences were given to mentoring logistics (formal agreement, frequency, length, and format of meetings). Conclusions: Factors to consider in developing a virtual mentorship program are informed by the survey results and are applicable to both HIC and L&MIC contexts, to medical physicists, and to other related professions.
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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 | 0.002 | 0.003 |
| 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 | 0.000 |
| 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 it