Utilizing RE-AIM to examine the translational potential of Project MOVE, a novel intervention for increasing physical activity levels in breast cancer survivors
Bibliographic record
Abstract
Translating effective research into community practice is critical for improving breast cancer (BC) survivor health. The purpose of this study is to utilize the RE-AIM framework to evaluate the translational potential of Project MOVE, an innovative intervention focused on increasing physical activity (PA) in BC survivors. A mixed-methods design, including a self-report questionnaire, accelerometry, focus groups, and interviews, was used to inform each RE-AIM dimension. Reach was evaluated by the representativeness of participants. Effectiveness was reflected by change in PA levels and perceptions of satisfaction and acceptability. Adoption was examined using participants' perceived barriers/facilitators to program uptake. Implementation was examined by participants' perceived barriers/facilitators to implementing the program. Maintenance was assessed by participant retention. Assessments occurred at baseline and 6-months. Mixed analysis of variance and content analysis were used to analyze the data. A total of 87 participants participated in Project MOVE and were demographically comparable to similar studies (Reach). Participants indicated high levels of program satisfaction (88%) and previously inactive survivors' significantly increased PA levels from baseline to 6-month follow-up (Effectiveness). Participants reported that a program focused on PA rather than disease helped them overcome barriers to PA (Adoption) and having leaders with BC and exercise expertise was essential to accommodate population specific barriers (Implementation). At 6-months, participant retention was 83% (Maintenance). Project MOVE is an acceptable, practical, and effective program for engaging BC survivors in PA and has the potential to be highly transferable to other populations and regions.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".