Determinants and Factors of Physical Activity After Oncology Treatments (DEFACTO) in Metropolitan France: Protocol of a Mixed Methods Study and Intervention
Bibliographic record
Abstract
BACKGROUND: While the scientific community widely recognizes the benefits of physical activity (PA) in oncology supportive care, cancer survivors who have undergone chemo- or radio-immunotherapy treatments struggle to meet PA recommendations. This underscores the importance of identifying factors influencing active lifestyle adoption and maintenance and proposing a multilevel model (micro-, meso-, and macrolevel) to better understand facilitators and barriers. Currently, no socioecological model explains an active lifestyle in the posttreatment phase of breast, colorectal, prostate, and lung cancers. OBJECTIVE: The objective is to identify factors influencing an active lifestyle in cancer survivorship and assess the feasibility of an individualized program targeting an active lifestyle. The objectives will be addressed in 3 stages. Stage 1 aims to elucidate factors associated with the active lifestyle of cancer survivors. Stage 2 involves developing an explanatory model based on previously identified factors to create a tailored health education program for an active lifestyle after oncology treatments. Stage 3 aims to evaluate the feasibility and potential effects of this personalized health education program after its national implementation. METHODS: First, the exploration of factors influencing PA (stage 1) will be based on a mixed methods approach, using an explanatory sequential design and multilevel analysis. The quantitative phase involves completing a questionnaire from a socioecological perspective. Subsequently, a subset of respondents will engage in semistructured interviews to aid in interpreting the quantitative results. This phase aims to construct a model of the factors influencing an active lifestyle and develop an individualized 12-week program based on our earlier findings (stage 2). In stage 3, we will implement our multicenter, multimodal program for 150 physically inactive and sedentary cancer survivors across metropolitan France. Program feasibility will be evaluated. Measured PA level by connected device and multidimensional variables such as declared PA and sedentary behaviors, PA readiness, motivation, PA preferences, PA knowledge and skills, and barriers and facilitators will be assessed before and during the program and 52 weeks afterward. RESULTS: The institutional review board approved the mixed methods study (phase 1) in April 2020, and the intervention (phase 3) was approved in March 2022. Recruitment and data collection commenced in April 2022, with intervention implementation concluded in May 2023. Data collection and full analysis are expected to be finalized by July 2024. CONCLUSIONS: The Determinants and Factors of Physical Activity After Oncology Treatments (DEFACTO) study seeks to enhance our understanding, within our socioecological model, of factors influencing an active lifestyle among cancer survivors and to assess whether a tailored intervention based on this model can support an active lifestyle. TRIAL REGISTRATION: ClinicalTrials.gov NCT05354882; https://www.clinicaltrials.gov/study/NCT05354882. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52274.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".