An evaluation of the Interdisciplinary Psychosocial Oncology Research Group and Laboratory: An initiative to enable intersectoral and interdisciplinary collaboration
Bibliographic record
Abstract
Background: Psychosocial oncology (PSO) is an interdisciplinary field that is often practised and researched in disciplinary silos. The Interdisciplinary PSO Research Group and Laboratory (IPSORGL) was developed in Ottawa (Ontario) to foster interdisciplinary collaboration and training amongst trainees, healthcare professionals (HCPs), and researchers. Methods: The research team conducted an implementation and outcome evaluation of the IPSORGL. Data were collected using sequential mixed methods, including surveys and interviews. Results: Eight trainees, six HCPs, and five researchers completed the survey. Six trainees and four HCPs participated in an interview. Benefits of the IPSORGL included establishing interdisciplinary connections and collaborations and obtaining unique training in a supportive environment. Challenges included members' differing preferences for meeting formats and content, and difficulties prioritizing the IPSORGL over other academic or clinical demands. Conclusions: The IPSORGL fosters essential interdisciplinary training and collaboration, which bolsters psychosocial oncology research and practice. The sustainability of such initiatives, however, requires formal institutional support.
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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 | 0.112 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".