Development of a Curriculum for the Implementation of Stereotactic Radiation Therapy Programs in Middle-Income Countries
Bibliographic record
Abstract
PURPOSE: The aim of this work was to develop a curriculum to be used in the implementation of stereotactic radiation therapy programs in middle-income countries. The curriculum needed to be scalable and flexible to be easily adapted to local situations. METHODS: The curriculum was developed through a partnership between multidisciplinary teams from established clinics in both middle-income and high-income countries. The curriculum development followed a nonlinear progression, allowing greater flexibility throughout the process. A blended learning model was used, combining virtual and in-person interactions. RESULTS: The initial training plan was based on a needs assessment provided by the learners and on the experience of the facilitators with stereotactic radiotherapy. The needs assessment was refined during in-person site visits at each institution which highlighted aspects of the training, such as image guidance workflows and technical specifications, that were not previously emphasized in the curriculum. Both teams found that the in-person visits were important for training purposes, but aspects of the curriculum delivery such as treatment planning and patient selection were well suited to virtual platforms. The training addressed all aspects of the stereotactic program, from patient selection to treatment, and included a review of both technical and clinical workflows. CONCLUSION: The inclusion of contributions from both teams ensured that the curriculum covered the required elements of the stereotactic program implementation, met the needs of the learners, and was relevant to local practices. The nonlinear approach to the curriculum development allowed the flexibility to change the focus as the project progressed. The in-person visits were valuable in conducting a thorough needs assessment.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".