The ACTION Centre as a Model for Patient Engagement and Knowledge Translation in Integrative Oncology Practice, Training, and Research
Bibliographic record
Abstract
Integrative Oncology (IO) programs are increasingly emerging at cancer centers and universities worldwide; often these include some combination of clinical service, research, and/or training. However, one gap that often occurs is in moving research results into practice, due to complexities and differences between research and service delivery models and priorities. We recently created the ACTION (Alberta Complementary Therapy and Integrative Oncology) Centre with the goal of partnering with the provincial public health service to promote and facilitate evidence-based integrative oncology care throughout Alberta. The Centre bridges the silos of academia and clinical care by embodying 3 core principles, to be (1) Patient-oriented, (2) Collaborative, and (3) Evidence-based. The ACTION Centre oversees the implementation of clinical research and academic training, and supports the development of clinical services, as well as patient and provider education. The ACTION Centre has five components which include: (1) Patient and healthcare provider education; (2) Individualized IO consultation and treatment planning; (3) Supporting access to complementary therapies; (4) Clinical trials of IO interventions, and; (5) Student training through the TRACTION (Training in Clinical Trials and Integrative Oncology) program. We offer this model of shareholder collaboration in the hopes that other IO programs may be able to use it as a template to further their own progress, working collaboratively toward the ultimate goal of advancing evidence-based, comprehensive, integrative healthcare to improve the lives of people affected by cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.129 | 0.074 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.015 | 0.045 |
| Scholarly communication | 0.024 | 0.019 |
| Open science | 0.009 | 0.043 |
| Research integrity | 0.014 | 0.018 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".