Training General Practitioners in Oncology: A Needs Assessment Survey From Nepal
Bibliographic record
Abstract
PURPOSE: Nepal lacks enough cancer care providers to address the growing burden of cancer in the country. One way of addressing this issue is to train general practitioners (GPs) in oncology (GPOs) so that they can task-share and task-shift oncology care. However, limited information is available regarding the current level of oncology expertise of Nepali GPs and whether they perceive a need for, and have an interest in, such a GPO training program if available in Nepal. METHODS: A survey was distributed to GPs in Nepal to collect data on current oncology training and clinical practice and evaluate levels of interest and need for a GPO training program. The survey was distributed electronically from February to July 2021. RESULTS: The survey obtained 71 individual responses from GPs in Nepal. The majority of respondents were male (87%), and most worked as consultants or senior consultants (63%). Only 6% of respondents had a mandatory oncology rotation during their GP training, and only 15% indicated that their GP training had adequately prepared them to care for patients with cancer. Ninety-six percent of respondents perceived a need for a GPO training program in Nepal, with 94% indicating an interest in enrolling in such a program and 71% indicating that they were very interested. CONCLUSION: The findings indicate an urgent need for and an encouraging interest in establishing a GPO training program in Nepal. These findings will be used to guide the development and implementation of this type of program.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".