Nutrition services for men with prostate cancer: A health professional survey.
Bibliographic record
Abstract
25 Background: Nutrition is a key part of prostate cancer (PC) survivorship for management of PC, treatment side effects, and overall health. The Prostate Cancer Supportive Care (PCSC) Program is one of only a few PC survivorship programs in Canada that provide nutrition support as part of standard care. A survey was conducted as part of a broader needs assessment to understand health care professionals’ (HCPs) perspectives on nutrition services for men with PC and inform nutrition programs. Methods: An online survey was administered to British Columbia (BC) HCPs caring for men with PC including urologists, radiation oncologists, medical oncologists, registered dietitians and researchers. We used purposive sampling to identify relevant HCPs. HCPs were asked about the importance of oncological nutrition services and how they should be delivered to men with PC. We summarized the percent agreement for each question and across professions then thematically analyzed qualitative data. Results: Of the 56 HCPs invited to participate in the survey, 38 (68%) responded. The majority (61%) agreed that men with PC require more nutritional support. HCPs indicated nutrition services should be offered multiple times throughout survivorship and facilitated through online resources, individual consultations with registered dietitians and consecutive group education sessions. Most (75%) urologists, radiation oncologists and medical oncologists responded that weight management should be the focus for nutrition services, whereas 90% of dietitians responded that nutrition for reducing the risk of PC progression should be the focus. The main themes that arose from the survey suggested that nutrition services should be available in different forms to facilitate individual needs and adapted based on cultural and community settings. Conclusions: HCPs confirm that there is an unmet need for nutrition services for men with PC in BC as existing services prioritize and offer services for cancer-related weight loss. Special consideration should be given to the focus of nutrition service provided, and when and how it is offered. These results will inform the development of additional resources for men with PC to support their nutritional needs.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".