Assessing the feasibility, acceptability, and preliminary health behavior outcomes of a community-based virtual group health coaching for cancer survivors program
Bibliographic record
Abstract
PURPOSE: The primary purpose was to assess the feasibility and acceptability of a group health coaching (GHC) program with cancer patients and survivors; secondarily, to determine the preliminary effects of GHC on several behavioral lifestyle factors. METHODS: GHC was provided to people diagnosed with cancer via videoconference by trained health coaches across six GHC sessions over a 3-month period. Qualitative and quantitative data were collected. Data on recruitment, attrition, attendance, fidelity, retention, safety, and barriers and facilitators to implementation were assessed. Participant-reported outcomes collected via surveys included physical activity, eating habits, perceived stress, anxiety, depression, sleep, and quality of life, followed by post-program focus groups and in-depth interviews. Survey results were analyzed using repeated measures multilevel modeling. Qualitative data was analyzed using inductive thematic analysis. RESULTS: Overall, 26 participants with a variety of cancer types attended an average of 74% of coaching sessions. The intervention was feasible to implement and found acceptable by participants and health coaches. Over the course of the intervention, there was a moderate increase in total weekly physical activity minutes (baseline = 365.25, follow-up = 510.30, p = 0.032, d = 0.50), and a small increase in weekly moderate-vigorous physical activity frequency (baseline = 4.07 bouts, follow-up = 5.44 bouts, p = 0.045, d = 0.39). Additionally, a moderate increase was found in functional well-being (baseline = 16.30, follow-up = 18.93, p < 0.001, d = 0.50). CONCLUSIONS AND IMPLICATIONS: GHC may be a feasible and acceptable way to promote behavior change for physical activity in cancer patients and survivors, reducing cancer burden and enhancing functional well-being.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".