A National Multi-Disciplinary Integrative Oncology Training Program in Israel: Trainee Perspectives
Bibliographic record
Abstract
CONTEXT AND OBJECTIVES: Integrative oncology (IO) programs are being implemented in supportive and palliative cancer care services worldwide, though research on the design of IO training programs is limited. This paper explores perspectives of trainees undergoing a national, multi-disciplinary IO training program in Israel, through their pre- and post-training narratives. METHODS: Trainees underwent a 110-hour IO training program focused on symptom management, through online and in-person instruction. Qualitative analysis was performed on the written narratives of program trainees, addressing pretraining expectations and post-training outcomes. A digital questionnaire with open-ended questions was used, with free-text reflective narratives analyzed using ATLAS.Ti software for systematic coding. RESULTS: Of the 68 trainees participating in the program, 62 provided precourse assessment; and 44 completed training, of which 33 provided post-training narratives. Pretraining themes included an expectation for enhancing communication-related competencies, primarily with patients but also with other healthcare professionals. Post-training narratives highlighted themes which included forming a professional identity as IO providers; enhanced collaboration within multidisciplinary teams; acquisition of practical competencies across diverse IO modalities; sharing clinical strategies and knowledge; and experiences of both personal and professional growth. CONCLUSIONS: Trainees in this national multidisciplinary IO training program expressed pretraining expectations focused primarily on communication skills; and post-training reflections emphasizing professional development, team-based practice, and integration of IO into palliative care. These findings suggest that IO training supports the transition from theoretical learning to practical clinical competencies. Further research is warranted to evaluate long-term symptom management and communication-related outcomes of combined IO and palliative care programs.
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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 | 0.003 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".