Patient and Medical Oncologists’ Perspectives on Prescribed Lifestyle Intervention—Experiences of Women with Breast Cancer and Providers
Bibliographic record
Abstract
This study explored the perspectives and experiences of breast cancer patients and medical oncologists with regards to participation in a lifestyle intervention at a tertiary cancer treatment center. A thematic approach was used to understand the context within which a lifestyle intervention was recommended and experienced, to inform future lifestyle programming and promote uptake. Twelve women with breast cancer receiving adjuvant chemotherapy and eight medical oncologists completed interviews. Findings suggest receiving a prescription for a lifestyle intervention from a trusted health professional was influential to women with breast cancer. The intervention offered physical, psychological, emotional, social, and informational benefits to the women and oncologists perceived both physiological and relational benefit to prescribing the intervention. Challenges focused on program access and tailored interventions. Lifestyle prescriptions are perceived by women with breast cancer to have numerous benefits and may promote lifestyle interventions and build rapport between oncologists and women. Oncology healthcare professionals play a pivotal role in motivating women's participation in lifestyle interventions during breast cancer treatment. Maintenance programs that transition patients into community settings and provide on-going information and follow-up are needed.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".