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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http://dx.doi.org/10.2196/52274 | DOI Listing |
BMC Public Health
January 2025
School of Basic Medical Sciences, Zhejiang Chinese Medical University, No. 548 Binwen Road, Binjiang District, Hangzhou, 310053, China.
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January 2025
Section Sports Medicine, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa.
This study aimed to establish consensus on injury risk factors in netball via a combined systematic review and Delphi method approach. A systematic search of databases (PubMed, Scopus, MEDLINE, SPORTDiscus and CINAHL) was conducted from inception until June 2023. Twenty-four risk factors were extracted from 17 studies and combined with a three-round Delphi approach to achieve consensus.
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December 2024
Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China (Hong Kong).
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January 2025
Student Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran. Electronic address:
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View Article and Find Full Text PDFHealth Place
January 2025
Department of Economics, Korea University, South Korea. Electronic address:
In response to the growing demand for healthier food, online fresh food platforms have emerged as a convenient solution, aiming to meet this need. This study employs a difference-in-differences design and an imputation method to evaluate the impact of online fresh food platforms on population health. These methodological approaches enable the identification of causal effects, offering insights into how these platforms influence health outcomes across different demographic groups.
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