Telehealth coaching for rural-living young adult cancer survivors: A protocol
Bibliographic record
Abstract
Objective: Young adult cancer survivors living in rural areas have reported barriers to participating in health behaviours due to their geographical location and the developmental milestones associated with their age. Existing health behaviour change interventions have generally been delivered face-to-face and have not been tailored to the preferences of young adults living in rural areas, thus not adequately addressing the needs of this population. To address these limitations, this trial aims to examine the feasibility and acceptability of a 12-week telehealth intervention drawing on self-determination theory to promote physical activity participation and fruit and vegetable consumption. Design: The intervention will be tested with young adults who are between the ages of 20 and 39 years, have completed primary treatment, live in an area with fewer than 35,000 inhabitants, are not currently meeting physical activity and fruit and vegetable consumption guidelines, have access to the Internet and audio-visual devices, are ambulatory and are able and willing to provide informed consent. The target sample size is 15. Method: Feasibility data will be collected by recording recommended outcomes throughout the trial. Additional feasibility data as well as acceptability data will be collected using an online questionnaire administered pre- and post-intervention and a semi-structured interview. Results: Results may inform the design and implementation of supportive care services for young adults, and potentially other adults living in rural areas who experience similar barriers to participating in health-promoting behaviours. Conclusion: This trial is one of the first to explore the feasibility and acceptability of a theory-based telehealth behaviour change intervention targeting young adult cancer survivors living in rural areas in order to mitigate the disease burden.
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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 | 0.030 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.061 | 0.013 |
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".