Exploring Theoretical Models and Frameworks Used to Explain Factors Influencing Breast Cancer Screening Participation: A Scoping Review
Issued Date
2025-01-01
Resource Type
eISSN
11791411
Scopus ID
2-s2.0-105026776150
Journal Title
International Journal of Women S Health
Volume
17
Start Page
5639
End Page
5656
Rights Holder(s)
SCOPUS
Bibliographic Citation
International Journal of Women S Health Vol.17 (2025) , 5639-5656
Suggested Citation
Zheng D., Lekdamrongkul P., Gao X., Sriyuktasuth A. Exploring Theoretical Models and Frameworks Used to Explain Factors Influencing Breast Cancer Screening Participation: A Scoping Review. International Journal of Women S Health Vol.17 (2025) , 5639-5656. 5656. doi:10.2147/IJWH.S553089 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/114018
Title
Exploring Theoretical Models and Frameworks Used to Explain Factors Influencing Breast Cancer Screening Participation: A Scoping Review
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Author's Affiliation
Corresponding Author(s)
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Abstract
Objective: The purpose of this study was to explore theoretical models and frameworks used to guide research studies that explain factors influencing participation in breast cancer screening (BCS). Methods: This study was conducted according to the framework developed by Arksey and O’Malley and reported in line with the PRISMA-ScR guidelines. A comprehensive search was performed across six databases: PubMed, Embase, CNKI, Scopus, EBSCO, and the Cochrane Library. Two researchers independently screened titles and abstracts. Data extraction and cross-checking were conducted on included studies, with a third researcher facilitating consensus in cases of disagreement. Extracted information included author, publication year, country, research methods, sample size, age, theoretical framework, and outcomes. A pre-designed form ensured consistency and accuracy in data extraction. Results: A total of 70 studies were included. The studies were primarily cross-sectional (66/70, 94.29%), with the largest geographical locations being the United States (16/70, 22.86%), Iran (15/70, 21.43%), and China (9/70, 12.86%). The review identified 13 models, with Health Belief Model being the most commonly used (21/70, 30.0%), followed by Andersen’s Behavioral Model (11/70, 15.71%) and Theory of Planned Behavior (8/70, 11.43%). The Health Belief Model emerged as the most empirically supported framework across all studies, particularly effective in identifying economic barriers and trust issues within healthcare systems among low-income and low-health literacy populations. This model has also been incorporated into more comprehensive frameworks, demonstrating strong predictive power and practical applicability with additional variables. All models offer distinct strengths, but their predictive power largely depends on research contexts and target populations. These variations may result in an incomplete or unreliable understanding of factors influencing BCS behavior. Conclusion: The findings provide a comprehensive summary of the models and frameworks employed to investigate factors influencing BCS over the past decade. These insights have significant implications for designing targeted healthcare interventions and informing policy changes to enhance global BCS participation and reduce disparities. Future refinements of these models are expected to improve their applicability and effectiveness across diverse populations and settings.