The Impact of a Small Private Online Course as a New Approach to Teaching Oncology: Development and Evaluation
Bibliographic record
Abstract
BACKGROUND: Oncology involves complex care and multidisciplinary management of patients; however, misinformation and ineffective communication remain problematic. OBJECTIVE: The educational objective of our study was to develop a new teaching method to improve cancer treatment and management by emphasizing the link between hospitals (inpatients) and their surrounding communities (outpatients). METHODS: A team of 22 professionals from public and private institutions developed a small private online course (SPOC). Each offering of the course lasted 6 weeks and covered 6 topics: individual health care plans, cancer surgery, ionizing radiation, cancer medicines, clinical research, and oncological supportive care. For participants in the course, we targeted people working in the cancer field. The SPOC used an active teaching method with collaborative and multidisciplinary learning. A final examination was offered in each session. We evaluated participants' satisfaction rate through a questionnaire and the success of the SPOC by participants' completion, success, and commitment rates. RESULTS: Of the total participants (N=1574), 446 completed the evaluation form. Most participants were aged 31 to 45 years. Participants included 56 nurses, 131 pharmacists, 80 from the medical field (including 26 physicians), 53 from patients' associations, 28 health teachers, and 13 students (medical and paramedical). Among the participants, 24.7% (90/446) had an independent medical practice, 38.5% (140/446) worked in a public institution, and 36.8% (134/446) worked in a private institution. After completing the SPOC sessions, 85.9% (384/446) thought they had learned new information, 90.8% (405/446) felt their expectations were met, and 90.4% (403/446) considered that the information had a positive impact on their professional practice. The completion rate was 35.51% (559/1574), the success rate was 71.47% (1025/1574), and the commitment rate was 64.67% (1018/1574). Concerning the cost effectiveness of SPOC compared with a traditional classroom of 25 students, online education became more effective when there were more than 950 participants. CONCLUSIONS: SPOCs improved the management of oncology patients. This new digital learning technique is an attractive concept to integrate into teaching practice. It offered optimal propagation of information and met the students' expectations.
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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 | 0.002 |
| 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) | 0.000 | 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".