Embedding lifestyle interventions into cancer care: has telehealth narrowed the equity gap?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lifestyle interventions targeting energy balance (ie, diet, exercise) are critical for optimizing the health and well-being of cancer survivors. Despite their benefits, access to these interventions is limited, especially in underserved populations, including older people, minority populations and those living in rural and remote areas. Telehealth has the potential to improve equity and increase access. This article outlines the advantages and challenges of using telehealth to support the integration of lifestyle interventions into cancer care. We describe 2 recent studies, GO-EXCAP and weSurvive, as examples of telehealth lifestyle intervention in underserved populations (older people and rural cancer survivors) and offer practical recommendations for future implementation. Innovative approaches to the use of telehealth-delivered lifestyle intervention during cancer survivorship offer great potential to reduce cancer burden.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 it