Healthy Living after Cancer: A dissemination and implementation study evaluating a telephone-delivered healthy lifestyle program for cancer survivors
Bibliographic record
Abstract
BACKGROUND: Given evidence shows physical activity, a healthful diet and weight management can improve cancer outcomes and reduce chronic disease risk, the major cancer organisations and health authorities have endorsed related guidelines for cancer survivors. Despite these, and a growing evidence base on effective lifestyle interventions, there is limited uptake into survivorship care. METHODS/DESIGN: Healthy Living after Cancer (HLaC) is a national dissemination and implementation study that will evaluate the integration of an evidence-based lifestyle intervention for cancer survivors into an existing telephone cancer information and support service delivered by Australian state-based Cancer Councils. Eligible participants (adults having completed cancer treatment with curative intent) will receive 12 health coaching calls over 6 months from Cancer Council nurses/allied health professionals targeting national guidelines for physical activity, healthy eating and weight control. Using the RE-AIM evaluation framework, primary outcomes are service-level indicators of program reach, adoption, implementation/costs and maintenance, with secondary (effectiveness) outcomes of patient-reported anthropometric, behavioural and psychosocial variables collected at pre- and post-program completion. The total participant accrual target across four participating Cancer Councils is 900 over 3 years. DISCUSSION: The national scope of the project and broad inclusion of cancer survivors, alongside evaluation of service-level indicators, associated costs and patient-reported outcomes, will provide the necessary practice-based evidence needed to inform future allocation of resources to support healthy living among cancer survivors. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry (ANZCTR) - ACTRN12615000882527 (registered on 24/08/2015).
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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 | 0.020 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".