Canadian oncology physiotherapists’ perspectives of physical activity in people with advanced cancer: a mixed-methods study
Bibliographic record
Abstract
BACKGROUND: Individuals with advanced cancer can benefit from physical activity (PA), but face barriers to PA participation. Physiotherapists can be well-positioned to support this patient population. OBJECTIVE: Our objective was to describe the perspectives, practices, knowledge, and skills of oncology physiotherapists related to PA in people with advanced cancer. METHODS: In this mixed-methods study, we recruited Canadian physiotherapists with current or recent clinical experience with advanced cancer. Phase I consisted of an online survey about views toward PA in advanced cancer and activity-related recommendations and concerns for two case scenarios. Phase II involved individual, semi-structured interviews about perspectives related to working with advanced cancer. RESULTS: Sixty-two physiotherapists participated in the survey, of which 13 participated in interviews. Most respondents (> 85%) agreed or strongly agreed PA is important and safe for individuals with advanced cancer. Case responses highlighted cancer-related considerations (e.g. bone metastases) tailored activity recommendations, and patient-centered, interprofessional care. Interview themes included: 1) situating PA within individually meaningful goals; 2) tailored strategies to promote PA; 3) overarching roles in functional optimization and symptom management; and 4) generalized lack of awareness regarding physiotherapy. CONCLUSION: Our findings indicate Canadian oncology physiotherapists describe knowledge of the safety and importance of PA, as well as key considerations in advanced cancer. Moreover, they highlight the importance of a patient-centered approach to support this population, particularly in facilitating safe and meaningful PA, as well as optimizing function and alleviating symptom burden. Further efforts are needed to investigate the development and integration of physiotherapy within cancer care.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".