Physical activity and breast cancer: Results of a focus group to devise novel exercise interventions for women with breast cancer
Bibliographic record
Abstract
Objective: To determine, from the diverse perspective of vested members of the health care team, novel exercise intervention strategies to implement within the cancer care institution in order to overcome barriers to exercise participation and promotion for women with breast cancer (BC).Methods: Design: Qualitative descriptive study. Setting: Cancer care institution. Participants: Health care professionals (HCPs) who work with women with BC. Intervention: A focus group was used to answer the research question. A moderator guided the focus group using a semi-structured script. Measurements: The focus group was recorded and transcribed. The transcript was coded independently using topic and analytical coding.Results: Three main issues came forth during analysis. These included a lack of (1) exercise programming and equipment available within the cancer care institution (2) communication with rehabilitation professionals, and (3) effective exercise education strategies available for patients with BC. Specific strategies were suggested to overcome each issue. Limitations: As purposeful sampling was used for recruitment, it is possible that participants agreed to be in this study because they had positive views on the need to incorporate exercise more effectively into practice.Conclusions: To our knowledge this is the first study to include a multidisciplinary team to come to a consensus on a knowledge translation exercise strategy. Findings show that future exercise interventions should implement active interventions within the cancer institution, include rehabilitation professionals as part of the health care team, and use technology to educate patients.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".