Introduction of a patient communication course to postgraduate oncology training in Russia.
Bibliographic record
Abstract
11022 Background: Communication skills are an obligatory part of postgraduate oncology education in European and Western countries and its benefits for doctors, patients, and the healthcare system are well-known. However, teaching efficient patient communication is challenging in developing countries where the paternalistic model is still spread and medical professionals are unaware that these skills are lacking. We hypothesize that a short simulation-based course for oncology residents introduces communication skills and raises awareness about its value. Methods: A 2-day communication course based on the Calgary-Cambridge model was taught to a cohort of PGY2 oncology residents. Lectures, seminars, and clinical simulations emphasizing a patient-centered approach, including open questions, active listening, identifying patient concerns, empathy, summarizing, and bad news delivery were conducted by certified teacher. A simulation exam was administered to those who completed the communication course and those who did not complete the course. Scores (max. 130) from two clinical scenarios assessed by the examiner, actors, and participant were compared between groups. Results: Ten PGY2 residents completed the course and seven did not complete the course. Medians scores for the first scenario given by the examiner, actor and resident were 99 (IQR: 90 – 122), 125 (IQR: 122 – 127) and 102 (IQR: 91 – 108) for course participants and 15 (IQR: 7-35), 18 (IQR: 12-34) and 61 (IQR: 41-83) for non-participants, respectively. Medians scores for the second scenario were also higher in participant group: 113.5 (IQR: 100-117), 107 (IQR: 98-118) and 104 (IQR: 99-112) vs. 22 (IQR: 12-50), 18 (IQR: 10 - 44) and 66 (IQR: 43-81), respectively. Four (40%) course participants and seven (100%) non-participants evaluated themselves higher than the examiner and actor. Conclusions: A short patient communication course for young oncologists effectively improves communication skills and provider self-awareness in developing countries.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".