“I Got My Trophy”: The Story of Implementing a Neuro-Oncology Exercise Program from the Patient and Caregiver Lens—A Qualitative Study
Bibliographic record
Abstract
The purpose of this study was to gather patient and caregiver perspectives of adult neuro-oncology patients participating in a 12-week exercise program (i.e., the Alberta Cancer Exercise-Neuro-Oncology; ACE-Neuro study). Patients and their caregivers were invited to participate in semi-structured interviews across study delivery. A qualitative photo elicitation methodology within a patient-oriented research approach was used. Interpretive description and a constructivist philosophy guided the investigation, analysis, and dissemination of findings. A patient partner was included as a member of the research team. N = 51 patients completed the ACE-Neuro study, of which 28 patients and nine caregivers participated in interviews (n = 37). Working with the patient partner, five themes were created and are presented as a story of neuro-oncology patients on their journey to accessing and participating in ACE-Neuro: (1) The Exposition: I Have Cancer…Now What?; (2) The Rising Action: Trials and Triumphs of Participation; (3) The Pivotal Moment: It’s More Than Exercise; (4) The Resolution: Tailored Not Templated…The Ideal Program for Me; and (5) The Epilogue: Key Factors for Sustained Delivery. The findings from this work address the lack of qualitative exploration for understanding the neuro-oncology exercise experience and will inform the sustainable implementation of programming to meet patients’ needs.
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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.014 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.007 |
| 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".