Empowering Tomorrow’s Cancer Specialists: Evaluating the Co-creation and Impact of Malawi’s First Surgical Oncology Summerschool
Bibliographic record
Abstract
Annually more than 1 million newly diagnosed cancer cases and 500,000 cancer-related deaths occur in Sub Saharan Africa (SSA). By 2030, the cancer burden in Africa is expected to double accompanied by low survival rates. Surgery remains the primary treatment for solid tumours especially where other treatment modalities are lacking. However, in SSA, surgical residents lack sufficient training in cancer treatment. In 2022, Malawian and Dutch specialists co-designed a training course focusing on oncologic diseases and potential treatment options tailored to the Malawian context. The aim of this study was to describe the co-creation process of a surgical oncology education activity in a low resource setting, at the same time attempting to evaluate the effectiveness of this training program. The course design was guided and evaluated conform Kirkpatrick's requirements for an effective training program. Pre-and post-course questionnaires were conducted to evaluate the effectiveness. Thirty-five surgical and gynaecological residents from Malawi participated in the course. Eighty-six percent of respondents (n = 24/28) were highly satisfied at the end of the course. After a 2-month follow-up, 84% (n = 16/19) frequently applied the newly acquired knowledge, and 74% (n = 14/19) reported to have changed their patient care. The course costs were approximately 119 EUR per attendee per day. This course generally received generally positively feedback, had high satisfaction rates, and enhanced knowledge and confidence in the surgical treatment of cancer. Its effectiveness should be further evaluated using the same co-creation model in different settings. Integrating oncology into the regular curriculum of surgical residents is recommended.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".