Can assessment of psychosocial orientation assist continuing education program development in psychosocial oncology?
Bibliographic record
Abstract
BACKGROUND: A pilot study was designed to aid in the development of a formal, interdisciplinary curriculum in psychosocial oncology for front-line health care professionals. METHOD: A 190-item questionnaire was distributed to psychosocial (PP) and non-psychosocial (NPP) oncology professionals attending a psychosocial skills workshop. A 38-item attitudinal survey of psychosocial orientation was used in an attempt to identify unperceived needs of the learners. RESULTS: Of the 150 questionnaires distributed, 104 (69%) were completed and returned. Overall scores for satisfaction with the workshop were high, and significantly higher in the PP group. No interdisciplinary difference existed in the preferred learning formats for future events, and both groups preferred interactive, experiential forums for developing skills relevant to patient management. The two groups' perceived learning needs differed. NPPs wanted to focus on skills such as communication, counseling, crisis intervention, palliative care, and coping with life-threatening illness. The attitudinal survey results demonstrated a significant difference between the psychosocial orientations of PPs and NPPs and suggested that NPPs would benefit from: 1) information to correct misconceptions about patients' psychosocial needs and experiences, 2) demonstrations of how to overcome contextual barriers to the delivery of psychosocial care. CONCLUSIONS: Front-line oncology professionals in many disciplines are interested in continuing education in psychosocial oncology. The attitudinal survey provided insight into unperceived learning needs that can help in designing future curricula. Its value as a tool to measure impact of these programs is worthy of future study.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".